Robot-Arm Dynamic Control by Computer

NASA Technical Reports Server (NTRS)

Bejczy, Antal K.; Tarn, Tzyh J.; Chen, Yilong J.

1987-01-01

Feedforward and feedback schemes linearize responses to control inputs. Method for control of robot arm based on computed nonlinear feedback and state tranformations to linearize system and decouple robot end-effector motions along each of cartesian axes augmented with optimal scheme for correction of errors in workspace. Major new feature of control method is: optimal error-correction loop directly operates on task level and not on joint-servocontrol level.

Minimal complexity control law synthesis

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Haddad, Wassim M.; Nett, Carl N.

1989-01-01

A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.

A direct method for synthesizing low-order optimal feedback control laws with application to flutter suppression

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Newsom, J. R.; Abel, I.

1980-01-01

A direct method of synthesizing a low-order optimal feedback control law for a high order system is presented. A nonlinear programming algorithm is employed to search for the control law design variables that minimize a performance index defined by a weighted sum of mean square steady state responses and control inputs. The controller is shown to be equivalent to a partial state estimator. The method is applied to the problem of active flutter suppression. Numerical results are presented for a 20th order system representing an aeroelastic wind-tunnel wing model. Low-order controllers (fourth and sixth order) are compared with a full order (20th order) optimal controller and found to provide near optimal performance with adequate stability margins.

Fast cooling for a system of stochastic oscillators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yongxin, E-mail: chen2468@umn.edu; Georgiou, Tryphon T., E-mail: tryphon@umn.edu; Pavon, Michele, E-mail: pavon@math.unipd.it

2015-11-15

We study feedback control of coupled nonlinear stochastic oscillators in a force field. We first consider the problem of asymptotically driving the system to a desired steady state corresponding to reduced thermal noise. Among the feedback controls achieving the desired asymptotic transfer, we find that the most efficient one from an energy point of view is characterized by time-reversibility. We also extend the theory of Schrödinger bridges to this model, thereby steering the system in finite time and with minimum effort to a target steady-state distribution. The system can then be maintained in this state through the optimal steady-state feedbackmore » control. The solution, in the finite-horizon case, involves a space-time harmonic function φ, and −logφ plays the role of an artificial, time-varying potential in which the desired evolution occurs. This framework appears extremely general and flexible and can be viewed as a considerable generalization of existing active control strategies such as macromolecular cooling. In the case of a quadratic potential, the results assume a form particularly attractive from the algorithmic viewpoint as the optimal control can be computed via deterministic matricial differential equations. An example involving inertial particles illustrates both transient and steady state optimal feedback control.« less

Full State Feedback Control for Virtual Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Jay Tillay

This report presents an object-oriented implementation of full state feedback control for virtual power plants (VPP). The components of the VPP full state feedback control are (1) objectoriented high-fidelity modeling for all devices in the VPP; (2) Distribution System Distributed Quasi-Dynamic State Estimation (DS-DQSE) that enables full observability of the VPP by augmenting actual measurements with virtual, derived and pseudo measurements and performing the Quasi-Dynamic State Estimation (QSE) in a distributed manner, and (3) automated formulation of the Optimal Power Flow (OPF) in real time using the output of the DS-DQSE, and solving the distributed OPF to provide the optimalmore » control commands to the DERs of the VPP.« less

Control design based on a linear state function observer

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1992-01-01

An approach to the design of low-order controllers for large scale systems is proposed. The method is derived from the theory of linear state function observers. First, the realization of a state feedback control law is interpreted as the observation of a linear function of the state vector. The linear state function to be reconstructed is the given control law. Then, based on the derivation for linear state function observers, the observer design is formulated as a parameter optimization problem. The optimization objective is to generate a matrix that is close to the given feedback gain matrix. Based on that matrix, the form of the observer and a new control law can be determined. A four-disk system and a lightly damped beam are presented as examples to demonstrate the applicability and efficacy of the proposed method.

Modeling the optimal central carbon metabolic pathways under feedback inhibition using flux balance analysis.

PubMed

De, Rajat K; Tomar, Namrata

2012-12-01

Metabolism is a complex process for energy production for cellular activity. It consists of a cascade of reactions that form a highly branched network in which the product of one reaction is the reactant of the next reaction. Metabolic pathways efficiently produce maximal amount of biomass while maintaining a steady-state behavior. The steady-state activity of such biochemical pathways necessarily incorporates feedback inhibition of the enzymes. This observation motivates us to incorporate feedback inhibition for modeling the optimal activity of metabolic pathways using flux balance analysis (FBA). We demonstrate the effectiveness of the methodology on a synthetic pathway with and without feedback inhibition. Similarly, for the first time, the Central Carbon Metabolic (CCM) pathways of Saccharomyces cerevisiae and Homo sapiens have been modeled and compared based on the above understanding. The optimal pathway, which maximizes the amount of the target product(s), is selected from all those obtained by the proposed method. For this, we have observed the concentration of the product inhibited enzymes of CCM pathway and its influence on its corresponding metabolite/substrate. We have also studied the concentration of the enzymes which are responsible for the synthesis of target products. We further hypothesize that an optimal pathway would opt for higher flux rate reactions. In light of these observations, we can say that an optimal pathway should have lower enzyme concentration and higher flux rates. Finally, we demonstrate the superiority of the proposed method by comparing it with the extreme pathway analysis.

Reliability-Based Control Design for Uncertain Systems

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.

2005-01-01

This paper presents a robust control design methodology for systems with probabilistic parametric uncertainty. Control design is carried out by solving a reliability-based multi-objective optimization problem where the probability of violating design requirements is minimized. Simultaneously, failure domains are optimally enlarged to enable global improvements in the closed-loop performance. To enable an efficient numerical implementation, a hybrid approach for estimating reliability metrics is developed. This approach, which integrates deterministic sampling and asymptotic approximations, greatly reduces the numerical burden associated with complex probabilistic computations without compromising the accuracy of the results. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.

Comparative study of flare control laws. [optimal control of b-737 aircraft approach and landing

NASA Technical Reports Server (NTRS)

Nadkarni, A. A.; Breedlove, W. J., Jr.

1979-01-01

A digital 3-D automatic control law was developed to achieve an optimal transition of a B-737 aircraft between various initial glid slope conditions and the desired final touchdown condition. A discrete, time-invariant, optimal, closed-loop control law presented for a linear regulator problem, was extended to include a system being acted upon by a constant disturbance. Two forms of control laws were derived to solve this problem. One method utilized the feedback of integral states defined appropriately and augmented with the original system equations. The second method formulated the problem as a control variable constraint, and the control variables were augmented with the original system. The control variable constraint control law yielded a better performance compared to feedback control law for the integral states chosen.

Pointing and Jitter Control for the USNA Multi-Beam Combining System

DTIC Science & Technology

2013-05-10

previous work, an adaptive H-infinity optimal controller has been developed to control a single beam using a beam position detector for feedback... turbulence and airborne particles, platform jitter, lack of feedback from the target , and current laser technology represent just a few of these...lasers. Solid state lasers, however, cannot currently provide high enough power levels to destroy a target using a single beam. On solid-state

Further Results on the Disturbance Response of a Double Integrator Controlled by Saturating Linear Static State Feedback

DTIC Science & Technology

2011-07-13

Anton A. Stoorvogel b, Håvard Fjær Grip a aSchool of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164-2752...utwente.nl ( Anton A. Stoorvogel), grip@ieee.org (Håvard Fjær Grip). of a double integrator controlled by a saturating linear static state feedback...References Chitour, Y., 2001. On the Lp stabilization of the double integrator subject to input saturation. ESAIM: Control, Optimization and Calculus

Deterministic generation of remote entanglement with active quantum feedback

DOE PAGES

Martin, Leigh; Motzoi, Felix; Li, Hanhan; ...

2015-12-10

We develop and study protocols for deterministic remote entanglement generation using quantum feedback, without relying on an entangling Hamiltonian. In order to formulate the most effective experimentally feasible protocol, we introduce the notion of average-sense locally optimal feedback protocols, which do not require real-time quantum state estimation, a difficult component of real-time quantum feedback control. We use this notion of optimality to construct two protocols that can deterministically create maximal entanglement: a semiclassical feedback protocol for low-efficiency measurements and a quantum feedback protocol for high-efficiency measurements. The latter reduces to direct feedback in the continuous-time limit, whose dynamics can bemore » modeled by a Wiseman-Milburn feedback master equation, which yields an analytic solution in the limit of unit measurement efficiency. Our formalism can smoothly interpolate between continuous-time and discrete-time descriptions of feedback dynamics and we exploit this feature to derive a superior hybrid protocol for arbitrary nonunit measurement efficiency that switches between quantum and semiclassical protocols. Lastly, we show using simulations incorporating experimental imperfections that deterministic entanglement of remote superconducting qubits may be achieved with current technology using the continuous-time feedback protocol alone.« less

Optimization of Closed Loop Eigenvalues: Maneuvering, Vibration Control, and Structure/Control Design Iteration for Flexible Spacecraft.

DTIC Science & Technology

1986-05-31

Nonlinear Feedback Control 8-16 for Spacecraft Attitude Maneuvers" 2. " Spacecraft Attitude Control Using 17-35... nonlinear state feedback control laws are developed for space- craft attitude control using the Euler parameters and conjugate angular momenta. Time... Nonlinear Feedback Control for Spacecraft Attitude Maneuvers," to appear in AIAA J. of Guidance, Control, and Dynamics, (AIAA Paper No. 83-2230-CP,

Research on output feedback control

NASA Technical Reports Server (NTRS)

Calise, A. J.; Kramer, F. S.

1985-01-01

In designing fixed order compensators, an output feedback formulation has been adopted by suitably augmenting the system description to include the compensator states. However, the minimization of the performance index over the range of possible compensator descriptions was impeded due to the nonuniqueness of the compensator transfer function. A controller canonical form of the compensator was chosen to reduce the number of free parameters to its minimal number in the optimization. In the MIMO case, the controller form requires a prespecified set of ascending controllability indices. This constraint on the compensator structure is rather innocuous in relation to the increase in convergence rate of the optimization. Moreover, the controller form is easily relatable to a unique controller transfer function description. This structure of the compensator does not require penalizing the compensator states for a nonzero or coupled solution, a problem that occurs when following a standard output feedback synthesis formulation.

Application of modern control theory to the design of optimum aircraft controllers

NASA Technical Reports Server (NTRS)

Power, L. J.

1973-01-01

The synthesis procedure presented is based on the solution of the output regulator problem of linear optimal control theory for time-invariant systems. By this technique, solution of the matrix Riccati equation leads to a constant linear feedback control law for an output regulator which will maintain a plant in a particular equilibrium condition in the presence of impulse disturbances. Two simple algorithms are presented that can be used in an automatic synthesis procedure for the design of maneuverable output regulators requiring only selected state variables for feedback. The first algorithm is for the construction of optimal feedforward control laws that can be superimposed upon a Kalman output regulator and that will drive the output of a plant to a desired constant value on command. The second algorithm is for the construction of optimal Luenberger observers that can be used to obtain feedback control laws for the output regulator requiring measurement of only part of the state vector. This algorithm constructs observers which have minimum response time under the constraint that the magnitude of the gains in the observer filter be less than some arbitrary limit.

Linear state feedback, quadratic weights, and closed loop eigenstructures. M.S. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1980-01-01

Equations are derived for the angles of general multivariable root loci and linear quadratic optimal root loci, including angles of departure and approach. The generalized eigenvalue problem is used to compute angles of approach. Equations are also derived to find the sensitivity of closed loop eigenvalue and the directional derivatives of closed loop eigenvectors. An equivalence class of quadratic weights that produce the same asymptotic eigenstructure is defined, a canonical element is defined, and an algorithm to find it is given. The behavior of the optimal root locus in the nonasymptotic region is shown to be different for quadratic weights with the same asymptotic properties. An algorithm is presented that can be used to select a feedback gain matrix for the linear state feedback problem which produces a specified asymptotic eigenstructure. Another algorithm is given to compute the asymptotic eigenstructure properties inherent in a given set of quadratic weights. Finally, it is shown that optimal root loci for nongeneric problems can be approximated by generic ones in the nonasymptotic region.

Feedback control of nonlinear quantum systems: a rule of thumb.

PubMed

Jacobs, Kurt; Lund, Austin P

2007-07-13

We show that in the regime in which feedback control is most effective - when measurements are relatively efficient, and feedback is relatively strong - then, in the absence of any sharp inhomogeneity in the noise, it is always best to measure in a basis that does not commute with the system density matrix than one that does. That is, it is optimal to make measurements that disturb the state one is attempting to stabilize.

Approximating the linear quadratic optimal control law for hereditary systems with delays in the control

NASA Technical Reports Server (NTRS)

Milman, Mark H.

1987-01-01

The fundamental control synthesis issue of establishing a priori convergence rates of approximation schemes for feedback controllers for a class of distributed parameter systems is addressed within the context of hereditary systems. Specifically, a factorization approach is presented for deriving approximations to the optimal feedback gains for the linear regulator-quadratic cost problem associated with time-varying functional differential equations with control delays. The approach is based on a discretization of the state penalty which leads to a simple structure for the feedback control law. General properties of the Volterra factors of Hilbert-Schmidt operators are then used to obtain convergence results for the controls, trajectories and feedback kernels. Two algorithms are derived from the basic approximation scheme, including a fast algorithm, in the time-invariant case. A numerical example is also considered.

Approximating the linear quadratic optimal control law for hereditary systems with delays in the control

NASA Technical Reports Server (NTRS)

Milman, Mark H.

1988-01-01

The fundamental control synthesis issue of establishing a priori convergence rates of approximation schemes for feedback controllers for a class of distributed parameter systems is addressed within the context of hereditary schemes. Specifically, a factorization approach is presented for deriving approximations to the optimal feedback gains for the linear regulator-quadratic cost problem associated with time-varying functional differential equations with control delays. The approach is based on a discretization of the state penalty which leads to a simple structure for the feedback control law. General properties of the Volterra factors of Hilbert-Schmidt operators are then used to obtain convergence results for the controls, trajectories and feedback kernels. Two algorithms are derived from the basic approximation scheme, including a fast algorithm, in the time-invariant case. A numerical example is also considered.

A study of the application of singular perturbation theory. [development of a real time algorithm for optimal three dimensional aircraft maneuvers

NASA Technical Reports Server (NTRS)

Mehra, R. K.; Washburn, R. B.; Sajan, S.; Carroll, J. V.

1979-01-01

A hierarchical real time algorithm for optimal three dimensional control of aircraft is described. Systematic methods are developed for real time computation of nonlinear feedback controls by means of singular perturbation theory. The results are applied to a six state, three control variable, point mass model of an F-4 aircraft. Nonlinear feedback laws are presented for computing the optimal control of throttle, bank angle, and angle of attack. Real Time capability is assessed on a TI 9900 microcomputer. The breakdown of the singular perturbation approximation near the terminal point is examined Continuation methods are examined to obtain exact optimal trajectories starting from the singular perturbation solutions.

Energy management of three-dimensional minimum-time intercept. [for aircraft flight optimization

NASA Technical Reports Server (NTRS)

Kelley, H. J.; Cliff, E. M.; Visser, H. G.

1985-01-01

A real-time computer algorithm to control and optimize aircraft flight profiles is described and applied to a three-dimensional minimum-time intercept mission. The proposed scheme has roots in two well known techniques: singular perturbations and neighboring-optimal guidance. Use of singular-perturbation ideas is made in terms of the assumed trajectory-family structure. A heading/energy family of prestored point-mass-model state-Euler solutions is used as the baseline in this scheme. The next step is to generate a near-optimal guidance law that will transfer the aircraft to the vicinity of this reference family. The control commands fed to the autopilot (bank angle and load factor) consist of the reference controls plus correction terms which are linear combinations of the altitude and path-angle deviations from reference values, weighted by a set of precalculated gains. In this respect the proposed scheme resembles neighboring-optimal guidance. However, in contrast to the neighboring-optimal guidance scheme, the reference control and state variables as well as the feedback gains are stored as functions of energy and heading in the present approach. Some numerical results comparing open-loop optimal and approximate feedback solutions are presented.

A Real-Time Brain-Machine Interface Combining Motor Target and Trajectory Intent Using an Optimal Feedback Control Design

PubMed Central

Shanechi, Maryam M.; Williams, Ziv M.; Wornell, Gregory W.; Hu, Rollin C.; Powers, Marissa; Brown, Emery N.

2013-01-01

Real-time brain-machine interfaces (BMI) have focused on either estimating the continuous movement trajectory or target intent. However, natural movement often incorporates both. Additionally, BMIs can be modeled as a feedback control system in which the subject modulates the neural activity to move the prosthetic device towards a desired target while receiving real-time sensory feedback of the state of the movement. We develop a novel real-time BMI using an optimal feedback control design that jointly estimates the movement target and trajectory of monkeys in two stages. First, the target is decoded from neural spiking activity before movement initiation. Second, the trajectory is decoded by combining the decoded target with the peri-movement spiking activity using an optimal feedback control design. This design exploits a recursive Bayesian decoder that uses an optimal feedback control model of the sensorimotor system to take into account the intended target location and the sensory feedback in its trajectory estimation from spiking activity. The real-time BMI processes the spiking activity directly using point process modeling. We implement the BMI in experiments consisting of an instructed-delay center-out task in which monkeys are presented with a target location on the screen during a delay period and then have to move a cursor to it without touching the incorrect targets. We show that the two-stage BMI performs more accurately than either stage alone. Correct target prediction can compensate for inaccurate trajectory estimation and vice versa. The optimal feedback control design also results in trajectories that are smoother and have lower estimation error. The two-stage decoder also performs better than linear regression approaches in offline cross-validation analyses. Our results demonstrate the advantage of a BMI design that jointly estimates the target and trajectory of movement and more closely mimics the sensorimotor control system. PMID:23593130

Computation of output feedback gains for linear stochastic systems using the Zangwill-Powell method

NASA Technical Reports Server (NTRS)

Kaufman, H.

1977-01-01

Because conventional optimal linear regulator theory results in a controller which requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. To this effect a stochastic linear model has been developed that accounts for process parameter and initial uncertainty, measurement noise, and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was then performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

PubMed

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Computation of the target state and feedback controls for time optimal consensus in multi-agent systems

NASA Astrophysics Data System (ADS)

Mulla, Ameer K.; Patil, Deepak U.; Chakraborty, Debraj

2018-02-01

N identical agents with bounded inputs aim to reach a common target state (consensus) in the minimum possible time. Algorithms for computing this time-optimal consensus point, the control law to be used by each agent and the time taken for the consensus to occur, are proposed. Two types of multi-agent systems are considered, namely (1) coupled single-integrator agents on a plane and, (2) double-integrator agents on a line. At the initial time instant, each agent is assumed to have access to the state information of all the other agents. An algorithm, using convexity of attainable sets and Helly's theorem, is proposed, to compute the final consensus target state and the minimum time to achieve this consensus. Further, parts of the computation are parallelised amongst the agents such that each agent has to perform computations of O(N2) run time complexity. Finally, local feedback time-optimal control laws are synthesised to drive each agent to the target point in minimum time. During this part of the operation, the controller for each agent uses measurements of only its own states and does not need to communicate with any neighbouring agents.

A combined stochastic feedforward and feedback control design methodology with application to autoland design

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1987-01-01

A combined stochastic feedforward and feedback control design methodology was developed. The objective of the feedforward control law is to track the commanded trajectory, whereas the feedback control law tries to maintain the plant state near the desired trajectory in the presence of disturbances and uncertainties about the plant. The feedforward control law design is formulated as a stochastic optimization problem and is embedded into the stochastic output feedback problem where the plant contains unstable and uncontrollable modes. An algorithm to compute the optimal feedforward is developed. In this approach, the use of error integral feedback, dynamic compensation, control rate command structures are an integral part of the methodology. An incremental implementation is recommended. Results on the eigenvalues of the implemented versus designed control laws are presented. The stochastic feedforward/feedback control methodology is used to design a digital automatic landing system for the ATOPS Research Vehicle, a Boeing 737-100 aircraft. The system control modes include localizer and glideslope capture and track, and flare to touchdown. Results of a detailed nonlinear simulation of the digital control laws, actuator systems, and aircraft aerodynamics are presented.

Closed-loop control of anesthesia: a primer for anesthesiologists.

PubMed

Dumont, Guy A; Ansermino, J Mark

2013-11-01

Feedback control is ubiquitous in nature and engineering and has revolutionized safety in fields from space travel to the automobile. In anesthesia, automated feedback control holds the promise of limiting the effects on performance of individual patient variability, optimizing the workload of the anesthesiologist, increasing the time spent in a more desirable clinical state, and ultimately improving the safety and quality of anesthesia care. The benefits of control systems will not be realized without widespread support from the health care team in close collaboration with industrial partners. In this review, we provide an introduction to the established field of control systems research for the everyday anesthesiologist. We introduce important concepts such as feedback and modeling specific to control problems and provide insight into design requirements for guaranteeing the safety and performance of feedback control systems. We focus our discussion on the optimization of anesthetic drug administration.

A device-oriented optimizer for solving ground state problems on an approximate quantum computer, Part II: Experiments for interacting spin and molecular systems

NASA Astrophysics Data System (ADS)

Kandala, Abhinav; Mezzacapo, Antonio; Temme, Kristan; Bravyi, Sergey; Takita, Maika; Chavez-Garcia, Jose; Córcoles, Antonio; Smolin, John; Chow, Jerry; Gambetta, Jay

Hybrid quantum-classical algorithms can be used to find variational solutions to generic quantum problems. Here, we present an experimental implementation of a device-oriented optimizer that uses superconducting quantum hardware. The experiment relies on feedback between the quantum device and classical optimization software which is robust to measurement noise. Our device-oriented approach uses naturally available interactions for the preparation of trial states. We demonstrate the application of this technique for solving interacting spin and molecular structure problems.

Distortion outage minimization in Nakagami fading using limited feedback

NASA Astrophysics Data System (ADS)

Wang, Chih-Hong; Dey, Subhrakanti

2011-12-01

We focus on a decentralized estimation problem via a clustered wireless sensor network measuring a random Gaussian source where the clusterheads amplify and forward their received signals (from the intra-cluster sensors) over orthogonal independent stationary Nakagami fading channels to a remote fusion center that reconstructs an estimate of the original source. The objective of this paper is to design clusterhead transmit power allocation policies to minimize the distortion outage probability at the fusion center, subject to an expected sum transmit power constraint. In the case when full channel state information (CSI) is available at the clusterhead transmitters, the optimization problem can be shown to be convex and is solved exactly. When only rate-limited channel feedback is available, we design a number of computationally efficient sub-optimal power allocation algorithms to solve the associated non-convex optimization problem. We also derive an approximation for the diversity order of the distortion outage probability in the limit when the average transmission power goes to infinity. Numerical results illustrate that the sub-optimal power allocation algorithms perform very well and can close the outage probability gap between the constant power allocation (no CSI) and full CSI-based optimal power allocation with only 3-4 bits of channel feedback.

Adaptive control of stochastic linear systems with unknown parameters. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ku, R. T.

1972-01-01

The problem of optimal control of linear discrete-time stochastic dynamical system with unknown and, possibly, stochastically varying parameters is considered on the basis of noisy measurements. It is desired to minimize the expected value of a quadratic cost functional. Since the simultaneous estimation of the state and plant parameters is a nonlinear filtering problem, the extended Kalman filter algorithm is used. Several qualitative and asymptotic properties of the open loop feedback optimal control and the enforced separation scheme are discussed. Simulation results via Monte Carlo method show that, in terms of the performance measure, for stable systems the open loop feedback optimal control system is slightly better than the enforced separation scheme, while for unstable systems the latter scheme is far better.

Aeroassisted orbital maneuvering using Lyapunov optimal feedback control

NASA Technical Reports Server (NTRS)

Grantham, Walter J.; Lee, Byoung-Soo

1987-01-01

A Liapunov optimal feedback controller incorporating a preferred direction of motion at each state of the system which is opposite to the gradient of a specified descent function is developed for aeroassisted orbital transfer from high-earth orbit to LEO. The performances of the Liapunov controller and a calculus-of-variations open-loop minimum-fuel controller, both of which are based on the 1962 U.S. Standard Atmosphere, are simulated using both the 1962 U.S. Standard Atmosphere and an atmosphere corresponding to the STS-6 Space Shuttle flight. In the STS-6 atmosphere, the calculus-of-variations open-loop controller fails to exit the atmosphere, while the Liapunov controller achieves the optimal minimum-fuel conditions, despite the + or - 40 percent fluctuations in the STS-6 atmosphere.

A feedback linearization approach to spacecraft control using momentum exchange devices. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Dzielski, John Edward

1988-01-01

Recent developments in the area of nonlinear control theory have shown how coordiante changes in the state and input spaces can be used with nonlinear feedback to transform certain nonlinear ordinary differential equations into equivalent linear equations. These feedback linearization techniques are applied to resolve two problems arising in the control of spacecraft equipped with control moment gyroscopes (CMGs). The first application involves the computation of rate commands for the gimbals that rotate the individual gyroscopes to produce commanded torques on the spacecraft. The second application is to the long-term management of stored momentum in the system of control moment gyroscopes using environmental torques acting on the vehicle. An approach to distributing control effort among a group of redundant actuators is described that uses feedback linearization techniques to parameterize sets of controls which influence a specified subsystem in a desired way. The approach is adapted for use in spacecraft control with double-gimballed gyroscopes to produce an algorithm that avoids problematic gimbal configurations by approximating sets of gimbal rates that drive CMG rotors into desirable configurations. The momentum management problem is stated as a trajectory optimization problem with a nonlinear dynamical constraint. Feedback linearization and collocation are used to transform this problem into an unconstrainted nonlinear program. The approach to trajectory optimization is fast and robust. A number of examples are presented showing applications to the proposed NASA space station.

Scale-dependent feedbacks between patch size and plant reproduction in desert grassland

USGS Publications Warehouse

Svejcar, Lauren N.; Bestelmeyer, Brandon T.; Duniway, Michael C.; James, Darren K.

2015-01-01

Theoretical models suggest that scale-dependent feedbacks between plant reproductive success and plant patch size govern transitions from highly to sparsely vegetated states in drylands, yet there is scant empirical evidence for these mechanisms. Scale-dependent feedback models suggest that an optimal patch size exists for growth and reproduction of plants and that a threshold patch organization exists below which positive feedbacks between vegetation and resources can break down, leading to critical transitions. We examined the relationship between patch size and plant reproduction using an experiment in a Chihuahuan Desert grassland. We tested the hypothesis that reproductive effort and success of a dominant grass (Bouteloua eriopoda) would vary predictably with patch size. We found that focal plants in medium-sized patches featured higher rates of grass reproductive success than when plants occupied either large patch interiors or small patches. These patterns support the existence of scale-dependent feedbacks in Chihuahuan Desert grasslands and indicate an optimal patch size for reproductive effort and success in B. eriopoda. We discuss the implications of these results for detecting ecological thresholds in desert grasslands.

Feedback stabilization of an oscillating vertical cylinder by POD Reduced-Order Model

NASA Astrophysics Data System (ADS)

Tissot, Gilles; Cordier, Laurent; Noack, Bernd R.

2015-01-01

The objective is to demonstrate the use of reduced-order models (ROM) based on proper orthogonal decomposition (POD) to stabilize the flow over a vertically oscillating circular cylinder in the laminar regime (Reynolds number equal to 60). The 2D Navier-Stokes equations are first solved with a finite element method, in which the moving cylinder is introduced via an ALE method. Since in fluid-structure interaction, the POD algorithm cannot be applied directly, we implemented the fictitious domain method of Glowinski et al. [1] where the solid domain is treated as a fluid undergoing an additional constraint. The POD-ROM is classically obtained by projecting the Navier-Stokes equations onto the first POD modes. At this level, the cylinder displacement is enforced in the POD-ROM through the introduction of Lagrange multipliers. For determining the optimal vertical velocity of the cylinder, a linear quadratic regulator framework is employed. After linearization of the POD-ROM around the steady flow state, the optimal linear feedback gain is obtained as solution of a generalized algebraic Riccati equation. Finally, when the optimal feedback control is applied, it is shown that the flow converges rapidly to the steady state. In addition, a vanishing control is obtained proving the efficiency of the control approach.

Optimal control of multiphoton ionization dynamics of small alkali aggregates

NASA Astrophysics Data System (ADS)

Lindinger, A.; Bartelt, A.; Lupulescu, C.; Vajda, S.; Woste, Ludger

2003-11-01

We have performed transient multi-photon ionization experiments on small alkali clusters of different size in order to probe their wave packet dynamics, structural reorientations, charge transfers and dissociative events in different vibrationally excited electronic states including their ground state. The observed processes were highly dependent on the irradiated pulse parameters like wavelength range or its phase and amplitude; an emphasis to employ a feedback control system for generating the optimum pulse shapes. Their spectral and temporal behavior reflects interesting properties about the investigated system and the irradiated photo-chemical process. First, we present the vibrational dynamics of bound electronically excited states of alkali dimers and trimers. The scheme for observing the wave packet dynamics in the electronic ground state using stimulated Raman-pumping is shown. Since the employed pulse parameters significantly influence the efficiency of the irradiated dynamic pathways photo-induced ioniziation experiments were carried out. The controllability of 3-photon ionization pathways is investigated on the model-like systems NaK and K2. A closed learning loop for adaptive feedback control is used to find the optimal fs pulse shape. Sinusoidal parameterizations of the spectral phase modulation are investigated in regard to the obtained optimal field. By reducing the number of parameters and thereby the complexity of the phase moduation, optimal pulse shapes can be generated that carry fingerprints of the molecule's dynamical properties. This enables to find "understandable" optimal pulse forms and offers the possiblity to gain insight into the photo-induced control process. Characteristic motions of the involved wave packets are proposed to explain the optimized dynamic dissociation pathways.

Towards Quantum Cybernetics:. Optimal Feedback Control in Quantum Bio Informatics

NASA Astrophysics Data System (ADS)

Belavkin, V. P.

2009-02-01

A brief account of the quantum information dynamics and dynamical programming methods for the purpose of optimal control in quantum cybernetics with convex constraints and cońcave cost and bequest functions of the quantum state is given. Consideration is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme with continuous observations we exploit the separation theorem of filtering and control aspects for quantum stochastic micro-dynamics of the total system. This allows to start with the Belavkin quantum filtering equation and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to only Hamiltonian terms in the filtering equation. A controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.

Computation of output feedback gains for linear stochastic systems using the Zangnill-Powell Method

NASA Technical Reports Server (NTRS)

Kaufman, H.

1975-01-01

Because conventional optimal linear regulator theory results in a controller which requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. To this effect a stochastic linear model has been developed that accounts for process parameter and initial uncertainty, measurement noise, and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was then performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell. Results using a seventh order process show the proposed procedures to be very effective.

Optimal output fast feedback in two-time scale control of flexible arms

NASA Technical Reports Server (NTRS)

Siciliano, B.; Calise, A. J.; Jonnalagadda, V. R. P.

1986-01-01

Control of lightweight flexible arms moving along predefined paths can be successfully synthesized on the basis of a two-time scale approach. A model following control can be designed for the reduced order slow subsystem. The fast subsystem is a linear system in which the slow variables act as parameters. The flexible fast variables which model the deflections of the arm along the trajectory can be sensed through strain gage measurements. For full state feedback design the derivatives of the deflections need to be estimated. The main contribution of this work is the design of an output feedback controller which includes a fixed order dynamic compensator, based on a recent convergent numerical algorithm for calculating LQ optimal gains. The design procedure is tested by means of simulation results for the one link flexible arm prototype in the laboratory.

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2018-01-01

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Stochastic Adaptive Particle Beam Tracker Using Meer Filter Feedback.

DTIC Science & Technology

1986-12-01

breakthrough required in controlling the beam location. In 1983, Zicker (27] conducted a feasibility study of a simple proportional gain controller... Zicker synthesized his stochastic controller designs from a deterministic optimal LQ controller assuming full state feedback. An LQ controller is a...34Merge" Method 2.5 Simlifying the eer Filter a Zicker ran a performance analysis on the Meer filter and found the Meer filter virtually insensitive to

A disturbance based control/structure design algorithm

NASA Technical Reports Server (NTRS)

Mclaren, Mark D.; Slater, Gary L.

1989-01-01

Some authors take a classical approach to the simultaneous structure/control optimization by attempting to simultaneously minimize the weighted sum of the total mass and a quadratic form, subject to all of the structural and control constraints. Here, the optimization will be based on the dynamic response of a structure to an external unknown stochastic disturbance environment. Such a response to excitation approach is common to both the structural and control design phases, and hence represents a more natural control/structure optimization strategy than relying on artificial and vague control penalties. The design objective is to find the structure and controller of minimum mass such that all the prescribed constraints are satisfied. Two alternative solution algorithms are presented which have been applied to this problem. Each algorithm handles the optimization strategy and the imposition of the nonlinear constraints in a different manner. Two controller methodologies, and their effect on the solution algorithm, will be considered. These are full state feedback and direct output feedback, although the problem formulation is not restricted solely to these forms of controller. In fact, although full state feedback is a popular choice among researchers in this field (for reasons that will become apparent), its practical application is severely limited. The controller/structure interaction is inserted by the imposition of appropriate closed-loop constraints, such as closed-loop output response and control effort constraints. Numerical results will be obtained for a representative flexible structure model to illustrate the effectiveness of the solution algorithms.

Modeling of endoluminal and interstitial ultrasound hyperthermia and thermal ablation: applications to device design, feedback control, and treatment planning

PubMed Central

Prakash, Punit; Salgaonkar, Vasant A.; Diederich, Chris J.

2014-01-01

Endoluminal and catheter-based ultrasound applicators are currently under development and are in clinical use for minimally invasive hyperthermia and thermal ablation of various tissue targets. Computational models play a critical role in in device design and optimization, assessment of therapeutic feasibility and safety, devising treatment monitoring and feedback control strategies, and performing patient-specific treatment planning with this technology. The critical aspects of theoretical modeling, applied specifically to endoluminal and interstitial ultrasound thermotherapy, are reviewed. Principles and practical techniques for modeling acoustic energy deposition, bioheat transfer, thermal tissue damage, and dynamic changes in the physical and physiological state of tissue are reviewed. The integration of these models and applications of simulation techniques in identification of device design parameters, development of real time feedback-control platforms, assessing the quality and safety of treatment delivery strategies, and optimization of inverse treatment plans are presented. PMID:23738697

Enhancing synchronization stability in a multi-area power grid

PubMed Central

Wang, Bing; Suzuki, Hideyuki; Aihara, Kazuyuki

2016-01-01

Maintaining a synchronous state of generators is of central importance to the normal operation of power grids, in which many networks are generally interconnected. In order to understand the condition under which the stability can be optimized, it is important to relate network stability with feedback control strategies as well as network structure. Here, we present a stability analysis on a multi-area power grid by relating it with several control strategies and topological design of network structure. We clarify the minimal feedback gain in the self-feedback control, and build the optimal communication network for the local and global control strategies. Finally, we consider relationship between the interconnection pattern and the synchronization stability; by optimizing the network interlinks, the obtained network shows better synchronization stability than the original network does, in particular, at a high power demand. Our analysis shows that interlinks between spatially distant nodes will improve the synchronization stability. The results seem unfeasible to be implemented in real systems but provide a potential guide for the design of stable power systems. PMID:27225708

Improving stability margins in discrete-time LQG controllers

NASA Technical Reports Server (NTRS)

Oranc, B. Tarik; Phillips, Charles L.

1987-01-01

Some of the problems are discussed which are encountered in the design of discrete-time stochastic controllers for problems that may adequately be described by the Linear Quadratic Gaussian (LQG) assumptions; namely, the problems of obtaining acceptable relative stability, robustness, and disturbance rejection properties. A dynamic compensator is proposed to replace the optimal full state feedback regulator gains at steady state, provided that all states are measurable. The compensator increases the stability margins at the plant input, which may possibly be inadequate in practical applications. Though the optimal regulator has desirable properties the observer based controller as implemented with a Kalman filter, in a noisy environment, has inadequate stability margins. The proposed compensator is designed to match the return difference matrix at the plant input to that of the optimal regulator while maintaining the optimality of the state estimates as directed by the measurement noise characteristics.

Data-driven model reference control of MIMO vertical tank systems with model-free VRFT and Q-Learning.

PubMed

Radac, Mircea-Bogdan; Precup, Radu-Emil; Roman, Raul-Cristian

2018-02-01

This paper proposes a combined Virtual Reference Feedback Tuning-Q-learning model-free control approach, which tunes nonlinear static state feedback controllers to achieve output model reference tracking in an optimal control framework. The novel iterative Batch Fitted Q-learning strategy uses two neural networks to represent the value function (critic) and the controller (actor), and it is referred to as a mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach. Learning convergence of the Q-learning schemes generally depends, among other settings, on the efficient exploration of the state-action space. Handcrafting test signals for efficient exploration is difficult even for input-output stable unknown processes. Virtual Reference Feedback Tuning can ensure an initial stabilizing controller to be learned from few input-output data and it can be next used to collect substantially more input-state data in a controlled mode, in a constrained environment, by compensating the process dynamics. This data is used to learn significantly superior nonlinear state feedback neural networks controllers for model reference tracking, using the proposed Batch Fitted Q-learning iterative tuning strategy, motivating the original combination of the two techniques. The mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach is experimentally validated for water level control of a multi input-multi output nonlinear constrained coupled two-tank system. Discussions on the observed control behavior are offered. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Dissipative Quantum Control of a Spin Chain

NASA Astrophysics Data System (ADS)

Morigi, Giovanna; Eschner, Jürgen; Cormick, Cecilia; Lin, Yiheng; Leibfried, Dietrich; Wineland, David J.

2015-11-01

A protocol is discussed for preparing a spin chain in a generic many-body state in the asymptotic limit of tailored nonunitary dynamics. The dynamics require the spectral resolution of the target state, optimized coherent pulses, engineered dissipation, and feedback. As an example, we discuss the preparation of an entangled antiferromagnetic state, and argue that the procedure can be applied to chains of trapped ions or Rydberg atoms.

CSI Feedback Reduction for MIMO Interference Alignment

NASA Astrophysics Data System (ADS)

Rao, Xiongbin; Ruan, Liangzhong; Lau, Vincent K. N.

2013-09-01

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. Most of the existing IA designs require full channel state information (CSI) at the transmitters, which induces a huge CSI signaling cost. Hence it is desirable to improve the feedback efficiency for IA and in this paper, we propose a novel IA scheme with a significantly reduced CSI feedback. To quantify the CSI feedback cost, we introduce a novel metric, namely the feedback dimension. This metric serves as a first-order measurement of CSI feedback overhead. Due to the partial CSI feedback constraint, conventional IA schemes can not be applied and hence, we develop a novel IA precoder / decorrelator design and establish new IA feasibility conditions. Via dynamic feedback profile design, the proposed IA scheme can also achieve a flexible tradeoff between the degree of freedom (DoF) requirements for data streams, the antenna resources and the CSI feedback cost. We show by analysis and simulations that the proposed scheme achieves substantial reductions of CSI feedback overhead under the same DoF requirement in MIMO interference networks.

Performance Assessment of Model-Based Optimal Feedforward and Feedback Current Profile Control in NSTX-U using the TRANSP Code

NASA Astrophysics Data System (ADS)

Ilhan, Z.; Wehner, W. P.; Schuster, E.; Boyer, M. D.; Gates, D. A.; Gerhardt, S.; Menard, J.

2015-11-01

Active control of the toroidal current density profile is crucial to achieve and maintain high-performance, MHD-stable plasma operation in NSTX-U. A first-principles-driven, control-oriented model describing the temporal evolution of the current profile has been proposed earlier by combining the magnetic diffusion equation with empirical correlations obtained at NSTX-U for the electron density, electron temperature, and non-inductive current drives. A feedforward + feedback control scheme for the requlation of the current profile is constructed by embedding the proposed nonlinear, physics-based model into the control design process. Firstly, nonlinear optimization techniques are used to design feedforward actuator trajectories that steer the plasma to a desired operating state with the objective of supporting the traditional trial-and-error experimental process of advanced scenario planning. Secondly, a feedback control algorithm to track a desired current profile evolution is developed with the goal of adding robustness to the overall control scheme. The effectiveness of the combined feedforward + feedback control algorithm for current profile regulation is tested in predictive simulations carried out in TRANSP. Supported by PPPL.

Distributed Wireless Power Transfer With Energy Feedback

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Zhang, Rui

2017-04-01

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they can be constructively combined at the energy receiver (ER) to achieve an EB gain that scales with the number of ETs. However, the optimal design of EB waveforms requires accurate channel state information (CSI) at the ETs, which is challenging to obtain practically, especially in a distributed system with ETs at separate locations. In this paper, we study practical and efficient channel training methods to achieve optimal EB in a distributed WET system. We propose two protocols with and without centralized coordination, respectively, where distributed ETs either sequentially or in parallel adapt their transmit phases based on a low-complexity energy feedback from the ER. The energy feedback only depends on the received power level at the ER, where each feedback indicates one particular transmit phase that results in the maximum harvested power over a set of previously used phases. Simulation results show that the two proposed training protocols converge very fast in practical WET systems even with a large number of distributed ETs, while the protocol with sequential ET phase adaptation is also analytically shown to converge to the optimal EB design with perfect CSI by increasing the training time. Numerical results are also provided to evaluate the performance of the proposed distributed EB and training designs as compared to other benchmark schemes.

Influence of the optimization methods on neural state estimation quality of the drive system with elasticity.

PubMed

Orlowska-Kowalska, Teresa; Kaminski, Marcin

2014-01-01

The paper deals with the implementation of optimized neural networks (NNs) for state variable estimation of the drive system with an elastic joint. The signals estimated by NNs are used in the control structure with a state-space controller and additional feedbacks from the shaft torque and the load speed. High estimation quality is very important for the correct operation of a closed-loop system. The precision of state variables estimation depends on the generalization properties of NNs. A short review of optimization methods of the NN is presented. Two techniques typical for regularization and pruning methods are described and tested in detail: the Bayesian regularization and the Optimal Brain Damage methods. Simulation results show good precision of both optimized neural estimators for a wide range of changes of the load speed and the load torque, not only for nominal but also changed parameters of the drive system. The simulation results are verified in a laboratory setup.

Control of wavepacket dynamics in mixed alkali metal clusters by optimally shaped fs pulses

NASA Astrophysics Data System (ADS)

Bartelt, A.; Minemoto, S.; Lupulescu, C.; Vajda, Š.; Wöste, L.

We have performed adaptive feedback optimization of phase-shaped femtosecond laser pulses to control the wavepacket dynamics of small mixed alkali-metal clusters. An optimization algorithm based on Evolutionary Strategies was used to maximize the ion intensities. The optimized pulses for NaK and Na2K converged to pulse trains consisting of numerous peaks. The timing of the elements of the pulse trains corresponds to integer and half integer numbers of the vibrational periods of the molecules, reflecting the wavepacket dynamics in their excited states.

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

A stochastic regulator for integrated communication and control systems. I - Formulation of control law. II - Numerical analysis and simulation

NASA Technical Reports Server (NTRS)

Liou, Luen-Woei; Ray, Asok

1991-01-01

A state feedback control law for integrated communication and control systems (ICCS) is formulated by using the dynamic programming and optimality principle on a finite-time horizon. The control law is derived on the basis of a stochastic model of the plant which is augmented in state space to allow for the effects of randomly varying delays in the feedback loop. A numerical procedure for synthesizing the control parameters is then presented, and the performance of the control law is evaluated by simulating the flight dynamics model of an advanced aircraft. Finally, recommendations for future work are made.

Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.

PubMed

Mazandarani, Mehran; Pariz, Naser

2018-05-01

This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Consensus for multi-agent systems with time-varying input delays

NASA Astrophysics Data System (ADS)

Yuan, Chengzhi; Wu, Fen

2017-10-01

This paper addresses the consensus control problem for linear multi-agent systems subject to uniform time-varying input delays and external disturbance. A novel state-feedback consensus protocol is proposed under the integral quadratic constraint (IQC) framework, which utilises not only the relative state information from neighbouring agents but also the real-time information of delays by means of the dynamic IQC system states for feedback control. Based on this new consensus protocol, the associated IQC-based control synthesis conditions are established and fully characterised as linear matrix inequalities (LMIs), such that the consensus control solution with optimal ? disturbance attenuation performance can be synthesised efficiently via convex optimisation. A numerical example is used to demonstrate the proposed approach.

Capacity of optical communications over a lossy bosonic channel with a receiver employing the most general coherent electro-optic feedback control

NASA Astrophysics Data System (ADS)

Chung, Hye Won; Guha, Saikat; Zheng, Lizhong

2017-07-01

We study the problem of designing optical receivers to discriminate between multiple coherent states using coherent processing receivers—i.e., one that uses arbitrary coherent feedback control and quantum-noise-limited direct detection—which was shown by Dolinar to achieve the minimum error probability in discriminating any two coherent states. We first derive and reinterpret Dolinar's binary-hypothesis minimum-probability-of-error receiver as the one that optimizes the information efficiency at each time instant, based on recursive Bayesian updates within the receiver. Using this viewpoint, we propose a natural generalization of Dolinar's receiver design to discriminate M coherent states, each of which could now be a codeword, i.e., a sequence of N coherent states, each drawn from a modulation alphabet. We analyze the channel capacity of the pure-loss optical channel with a general coherent-processing receiver in the low-photon number regime and compare it with the capacity achievable with direct detection and the Holevo limit (achieving the latter would require a quantum joint-detection receiver). We show compelling evidence that despite the optimal performance of Dolinar's receiver for the binary coherent-state hypothesis test (either in error probability or mutual information), the asymptotic communication rate achievable by such a coherent-processing receiver is only as good as direct detection. This suggests that in the infinitely long codeword limit, all potential benefits of coherent processing at the receiver can be obtained by designing a good code and direct detection, with no feedback within the receiver.

A Nonlinear Physics-Based Optimal Control Method for Magnetostrictive Actuators

NASA Technical Reports Server (NTRS)

Smith, Ralph C.

1998-01-01

This paper addresses the development of a nonlinear optimal control methodology for magnetostrictive actuators. At moderate to high drive levels, the output from these actuators is highly nonlinear and contains significant magnetic and magnetomechanical hysteresis. These dynamics must be accommodated by models and control laws to utilize the full capabilities of the actuators. A characterization based upon ferromagnetic mean field theory provides a model which accurately quantifies both transient and steady state actuator dynamics under a variety of operating conditions. The control method consists of a linear perturbation feedback law used in combination with an optimal open loop nonlinear control. The nonlinear control incorporates the hysteresis and nonlinearities inherent to the transducer and can be computed offline. The feedback control is constructed through linearization of the perturbed system about the optimal system and is efficient for online implementation. As demonstrated through numerical examples, the combined hybrid control is robust and can be readily implemented in linear PDE-based structural models.

Small Body GN&C Research Report: A Robust Model Predictive Control Algorithm with Guaranteed Resolvability

NASA Technical Reports Server (NTRS)

Acikmese, Behcet A.; Carson, John M., III

2005-01-01

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.

A robust model predictive control algorithm for uncertain nonlinear systems that guarantees resolvability

NASA Technical Reports Server (NTRS)

Acikmese, Ahmet Behcet; Carson, John M., III

2006-01-01

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.

Microgravity vibration isolation: An optimal control law for the one-dimensional case

NASA Technical Reports Server (NTRS)

Hampton, Richard D.; Grodsinsky, Carlos M.; Allaire, Paul E.; Lewis, David W.; Knospe, Carl R.

1991-01-01

Certain experiments contemplated for space platforms must be isolated from the accelerations of the platform. An optimal active control is developed for microgravity vibration isolation, using constant state feedback gains (identical to those obtained from the Linear Quadratic Regulator (LQR) approach) along with constant feedforward gains. The quadratic cost function for this control algorithm effectively weights external accelerations of the platform disturbances by a factor proportional to (1/omega) exp 4. Low frequency accelerations are attenuated by greater than two orders of magnitude. The control relies on the absolute position and velocity feedback of the experiment and the absolute position and velocity feedforward of the platform, and generally derives the stability robustness characteristics guaranteed by the LQR approach to optimality. The method as derived is extendable to the case in which only the relative positions and velocities and the absolute accelerations of the experiment and space platform are available.

Microgravity vibration isolation: An optimal control law for the one-dimensional case

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Grodsinsky, C. M.; Allaire, P. E.; Lewis, D. W.; Knospe, C. R.

1991-01-01

Certain experiments contemplated for space platforms must be isolated from the accelerations of the platforms. An optimal active control is developed for microgravity vibration isolation, using constant state feedback gains (identical to those obtained from the Linear Quadratic Regulator (LQR) approach) along with constant feedforward (preview) gains. The quadratic cost function for this control algorithm effectively weights external accelerations of the platform disturbances by a factor proportional to (1/omega)(exp 4). Low frequency accelerations (less than 50 Hz) are attenuated by greater than two orders of magnitude. The control relies on the absolute position and velocity feedback of the experiment and the absolute position and velocity feedforward of the platform, and generally derives the stability robustness characteristics guaranteed by the LQR approach to optimality. The method as derived is extendable to the case in which only the relative positions and velocities and the absolute accelerations of the experiment and space platform are available.

Optimal design of tweezer control for chimera states

NASA Astrophysics Data System (ADS)

Omelchenko, Iryna; Omel'chenko, Oleh E.; Zakharova, Anna; Schöll, Eckehard

2018-01-01

Chimera states are complex spatio-temporal patterns which consist of coexisting domains of spatially coherent and incoherent dynamics in systems of coupled oscillators. In small networks, chimera states usually exhibit short lifetimes and erratic drifting of the spatial position of the incoherent domain. A tweezer feedback control scheme can stabilize and fix the position of chimera states. We analyze the action of the tweezer control in small nonlocally coupled networks of Van der Pol and FitzHugh-Nagumo oscillators, and determine the ranges of optimal control parameters. We demonstrate that the tweezer control scheme allows for stabilization of chimera states with different shapes, and can be used as an instrument for controlling the coherent domains size, as well as the maximum average frequency difference of the oscillators.

Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

PubMed

Heydari, Ali; Balakrishnan, Sivasubramanya N

2013-01-01

To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.

Simultaneous deterministic control of distant qubits in two semiconductor quantum dots.

PubMed

Gamouras, A; Mathew, R; Freisem, S; Deppe, D G; Hall, K C

2013-10-09

In optimal quantum control (OQC), a target quantum state of matter is achieved by tailoring the phase and amplitude of the control Hamiltonian through femtosecond pulse-shaping techniques and powerful adaptive feedback algorithms. Motivated by recent applications of OQC in quantum information science as an approach to optimizing quantum gates in atomic and molecular systems, here we report the experimental implementation of OQC in a solid-state system consisting of distinguishable semiconductor quantum dots. We demonstrate simultaneous high-fidelity π and 2π single qubit gates in two different quantum dots using a single engineered infrared femtosecond pulse. These experiments enhance the scalability of semiconductor-based quantum hardware and lay the foundation for applications of pulse shaping to optimize quantum gates in other solid-state systems.

Protograph-Based Raptor-Like Codes

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Chen, Tsung-Yi; Wang, Jiadong; Wesel, Richard D.

2014-01-01

Theoretical analysis has long indicated that feedback improves the error exponent but not the capacity of pointto- point memoryless channels. The analytic and empirical results indicate that at short blocklength regime, practical rate-compatible punctured convolutional (RCPC) codes achieve low latency with the use of noiseless feedback. In 3GPP, standard rate-compatible turbo codes (RCPT) did not outperform the convolutional codes in the short blocklength regime. The reason is the convolutional codes for low number of states can be decoded optimally using Viterbi decoder. Despite excellent performance of convolutional codes at very short blocklengths, the strength of convolutional codes does not scale with the blocklength for a fixed number of states in its trellis.

Vibration control of rotor shaft

NASA Technical Reports Server (NTRS)

Nonami, K.

1985-01-01

Suppression of flexural forced vibration or the self-excited vibration of a rotating shaft system not by passive elements but by active elements is described. The distinctive feature of this method is not to dissipate the vibration energy but to provide the force cancelling the vibration displacement and the vibration velocity through the bearing housing in rotation. Therefore the bearings of this kind are appropriately named Active Control Bearings. A simple rotor system having one disk at the center of the span on flexible supports is investigated in this paper. The actuators of the electrodynamic transducer are inserted in the sections of the bearing housing. First, applying the optimal regulator of optimal control theory, the flexural vibration control of the rotating shaft and the vibration control of support systems are performed by the optimal state feedback system using these actuators. Next, the quasi-modal control based on a modal analysis is applied to this rotor system. This quasi-modal control system is constructed by means of optimal velocity feedback loops. The differences between optimal control and quasi-modal control are discussed and their merits and demerits are made clear. Finally, the experiments are described concerning only the optimal regulator method.

Numerical approximation for the infinite-dimensional discrete-time optimal linear-quadratic regulator problem

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Rosen, I. G.

1986-01-01

An abstract approximation framework is developed for the finite and infinite time horizon discrete-time linear-quadratic regulator problem for systems whose state dynamics are described by a linear semigroup of operators on an infinite dimensional Hilbert space. The schemes included the framework yield finite dimensional approximations to the linear state feedback gains which determine the optimal control law. Convergence arguments are given. Examples involving hereditary and parabolic systems and the vibration of a flexible beam are considered. Spline-based finite element schemes for these classes of problems, together with numerical results, are presented and discussed.

Closed-loop stability of linear quadratic optimal systems in the presence of modeling errors

NASA Technical Reports Server (NTRS)

Toda, M.; Patel, R.; Sridhar, B.

1976-01-01

The well-known stabilizing property of linear quadratic state feedback design is utilized to evaluate the robustness of a linear quadratic feedback design in the presence of modeling errors. Two general conditions are obtained for allowable modeling errors such that the resulting closed-loop system remains stable. One of these conditions is applied to obtain two more particular conditions which are readily applicable to practical situations where a designer has information on the bounds of modeling errors. Relations are established between the allowable parameter uncertainty and the weighting matrices of the quadratic performance index, thereby enabling the designer to select appropriate weighting matrices to attain a robust feedback design.

Inverse optimal design of input-to-state stabilisation for affine nonlinear systems with input delays

NASA Astrophysics Data System (ADS)

Cai, Xiushan; Meng, Lingxin; Zhang, Wei; Liu, Leipo

2018-03-01

We establish robustness of the predictor feedback control law to perturbations appearing at the system input for affine nonlinear systems with time-varying input delay and additive disturbances. Furthermore, it is shown that it is inverse optimal with respect to a differential game problem. All of the stability and inverse optimality proofs are based on the infinite-dimensional backstepping transformation and an appropriate Lyapunov functional. A single-link manipulator subject to input delays and disturbances is given to illustrate the validity of the proposed method.

Optimal estimation and scheduling in aquifer management using the rapid feedback control method

NASA Astrophysics Data System (ADS)

Ghorbanidehno, Hojat; Kokkinaki, Amalia; Kitanidis, Peter K.; Darve, Eric

2017-12-01

Management of water resources systems often involves a large number of parameters, as in the case of large, spatially heterogeneous aquifers, and a large number of "noisy" observations, as in the case of pressure observation in wells. Optimizing the operation of such systems requires both searching among many possible solutions and utilizing new information as it becomes available. However, the computational cost of this task increases rapidly with the size of the problem to the extent that textbook optimization methods are practically impossible to apply. In this paper, we present a new computationally efficient technique as a practical alternative for optimally operating large-scale dynamical systems. The proposed method, which we term Rapid Feedback Controller (RFC), provides a practical approach for combined monitoring, parameter estimation, uncertainty quantification, and optimal control for linear and nonlinear systems with a quadratic cost function. For illustration, we consider the case of a weakly nonlinear uncertain dynamical system with a quadratic objective function, specifically a two-dimensional heterogeneous aquifer management problem. To validate our method, we compare our results with the linear quadratic Gaussian (LQG) method, which is the basic approach for feedback control. We show that the computational cost of the RFC scales only linearly with the number of unknowns, a great improvement compared to the basic LQG control with a computational cost that scales quadratically. We demonstrate that the RFC method can obtain the optimal control values at a greatly reduced computational cost compared to the conventional LQG algorithm with small and controllable losses in the accuracy of the state and parameter estimation.

Model-based Optimization and Feedback Control of the Current Density Profile Evolution in NSTX-U

NASA Astrophysics Data System (ADS)

Ilhan, Zeki Okan

Nuclear fusion research is a highly challenging, multidisciplinary field seeking contributions from both plasma physics and multiple engineering areas. As an application of plasma control engineering, this dissertation mainly explores methods to control the current density profile evolution within the National Spherical Torus eXperiment-Upgrade (NSTX-U), which is a substantial upgrade based on the NSTX device, which is located in Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ. Active control of the toroidal current density profile is among those plasma control milestones that the NSTX-U program must achieve to realize its next-step operational goals, which are characterized by high-performance, long-pulse, MHD-stable plasma operation with neutral beam heating. Therefore, the aim of this work is to develop model-based, feedforward and feedback controllers that can enable time regulation of the current density profile in NSTX-U by actuating the total plasma current, electron density, and the powers of the individual neutral beam injectors. Motivated by the coupled, nonlinear, multivariable, distributed-parameter plasma dynamics, the first step towards control design is the development of a physics-based, control-oriented model for the current profile evolution in NSTX-U in response to non-inductive current drives and heating systems. Numerical simulations of the proposed control-oriented model show qualitative agreement with the high-fidelity physics code TRANSP. The next step is to utilize the proposed control-oriented model to design an open-loop actuator trajectory optimizer. Given a desired operating state, the optimizer produces the actuator trajectories that can steer the plasma to such state. The objective of the feedforward control design is to provide a more systematic approach to advanced scenario planning in NSTX-U since the development of such scenarios is conventionally carried out experimentally by modifying the tokamak's actuator trajectories and analyzing the resulting plasma evolution. Finally, the proposed control-oriented model is embedded in feedback control schemes based on optimal control and Model Predictive Control (MPC) approaches. Integrators are added to the standard Linear Quadratic Gaussian (LQG) and MPC formulations to provide robustness against various modeling uncertainties and external disturbances. The effectiveness of the proposed feedback controllers in regulating the current density profile in NSTX-U is demonstrated in closed-loop nonlinear simulations. Moreover, the optimal feedback control algorithm has been implemented successfully in closed-loop control simulations within TRANSP through the recently developed Expert routine. (Abstract shortened by ProQuest.).

All-Union Conference on Laser Optics, 4th, Leningrad, USSR, January 13-18, 1984, Proceedings

NASA Astrophysics Data System (ADS)

Bukhenskii, M. F.

1984-08-01

The papers presented in this volume provide an overview of current theoretical and experimental research in laser optics. Topics discussed include electronically controlled tunable lasers, nonlinear phenomena in fiber-optic waveguides, holographic distributed-feedback dye lasers, and new developments in solid-state lasers. Papers are also presented on the generation of picosecond pulses through self-Q-switching in a distributed-feedback laser, temporal compression of light pulses during stimulated backscattering, and optimization of second harmonic generation in a multimode Nd:glass laser.

An optimal state estimation model of sensory integration in human postural balance

NASA Astrophysics Data System (ADS)

Kuo, Arthur D.

2005-09-01

We propose a model for human postural balance, combining state feedback control with optimal state estimation. State estimation uses an internal model of body and sensor dynamics to process sensor information and determine body orientation. Three sensory modalities are modeled: joint proprioception, vestibular organs in the inner ear, and vision. These are mated with a two degree-of-freedom model of body dynamics in the sagittal plane. Linear quadratic optimal control is used to design state feedback and estimation gains. Nine free parameters define the control objective and the signal-to-noise ratios of the sensors. The model predicts statistical properties of human sway in terms of covariance of ankle and hip motion. These predictions are compared with normal human responses to alterations in sensory conditions. With a single parameter set, the model successfully reproduces the general nature of postural motion as a function of sensory environment. Parameter variations reveal that the model is highly robust under normal sensory conditions, but not when two or more sensors are inaccurate. This behavior is similar to that of normal human subjects. We propose that age-related sensory changes may be modeled with decreased signal-to-noise ratios, and compare the model's behavior with degraded sensors against experimental measurements from older adults. We also examine removal of the model's vestibular sense, which leads to instability similar to that observed in bilateral vestibular loss subjects. The model may be useful for predicting which sensors are most critical for balance, and how much they can deteriorate before posture becomes unstable.

Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.

PubMed

Yuan, Haidong; Fung, Chi-Hang Fred

2015-09-11

Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.

Alternatives for jet engine control

NASA Technical Reports Server (NTRS)

Sain, M. K.

1984-01-01

The technical progress of researches Alternatives for Jet Engine Control is reported. A numerical study employing feedback tensors for optimal control of nonlinear systems was completed. It is believed that these studies are the first of their kind. State regulation, with a decrease in control power is demonstrated. A detailed treatment follows.

Computation of optimal output-feedback compensators for linear time-invariant systems

NASA Technical Reports Server (NTRS)

Platzman, L. K.

1972-01-01

The control of linear time-invariant systems with respect to a quadratic performance criterion was considered, subject to the constraint that the control vector be a constant linear transformation of the output vector. The optimal feedback matrix, f*, was selected to optimize the expected performance, given the covariance of the initial state. It is first shown that the expected performance criterion can be expressed as the ratio of two multinomials in the element of f. This expression provides the basis for a feasible method of determining f* in the case of single-input single-output systems. A number of iterative algorithms are then proposed for the calculation of f* for multiple input-output systems. For two of these, monotone convergence is proved, but they involve the solution of nonlinear matrix equations at each iteration. Another is proposed involving the solution of Lyapunov equations at each iteration, and the gradual increase of the magnitude of a penalty function. Experience with this algorithm will be needed to determine whether or not it does, indeed, possess desirable convergence properties, and whether it can be used to determine the globally optimal f*.

Optimal linear-quadratic control of coupled parabolic-hyperbolic PDEs

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2017-10-01

This paper focuses on the optimal control design for a system of coupled parabolic-hypebolic partial differential equations by using the infinite-dimensional state-space description and the corresponding operator Riccati equation. Some dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the linear-quadratic (LQ)-optimal control problem. A state LQ-feedback operator is computed by solving the operator Riccati equation, which is converted into a set of algebraic and differential Riccati equations, thanks to the eigenvalues and the eigenvectors of the parabolic operator. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ-optimal controller designed in the early portion of the paper is implemented for the original nonlinear model. Numerical simulations are performed to show the controller performances.

Consensus of satellite cluster flight using an energy-matching optimal control method

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Zhou, Liang; Zhang, Bo

2017-11-01

This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

Coherent feedback control of a single qubit in diamond

NASA Astrophysics Data System (ADS)

Hirose, Masashi; Cappellaro, Paola

2016-04-01

Engineering desired operations on qubits subjected to the deleterious effects of their environment is a critical task in quantum information processing, quantum simulation and sensing. The most common approach relies on open-loop quantum control techniques, including optimal-control algorithms based on analytical or numerical solutions, Lyapunov design and Hamiltonian engineering. An alternative strategy, inspired by the success of classical control, is feedback control. Because of the complications introduced by quantum measurement, closed-loop control is less pervasive in the quantum setting and, with exceptions, its experimental implementations have been mainly limited to quantum optics experiments. Here we implement a feedback-control algorithm using a solid-state spin qubit system associated with the nitrogen vacancy centre in diamond, using coherent feedback to overcome the limitations of measurement-based feedback, and show that it can protect the qubit against intrinsic dephasing noise for milliseconds. In coherent feedback, the quantum system is connected to an auxiliary quantum controller (ancilla) that acquires information about the output state of the system (by an entangling operation) and performs an appropriate feedback action (by a conditional gate). In contrast to open-loop dynamical decoupling techniques, feedback control can protect the qubit even against Markovian noise and for an arbitrary period of time (limited only by the coherence time of the ancilla), while allowing gate operations. It is thus more closely related to quantum error-correction schemes, although these require larger and increasing qubit overheads. Increasing the number of fresh ancillas enables protection beyond their coherence time. We further evaluate the robustness of the feedback protocol, which could be applied to quantum computation and sensing, by exploring a trade-off between information gain and decoherence protection, as measurement of the ancilla-qubit correlation after the feedback algorithm voids the protection, even if the rest of the dynamics is unchanged.

Optimal and Autonomous Control Using Reinforcement Learning: A Survey.

PubMed

Kiumarsi, Bahare; Vamvoudakis, Kyriakos G; Modares, Hamidreza; Lewis, Frank L

2018-06-01

This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively. Moreover, we discuss a new direction of off-policy RL for both CT and DT systems. Finally, we review several applications.

The Dolinar Receiver in an Information Theoretic Framework

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.; Birnbaum, Kevin M.; Moision, Bruce E.; Dolinar, Samuel J.

2011-01-01

Optical communication at the quantum limit requires that measurements on the optical field be maximally informative, but devising physical measurements that accomplish this objective has proven challenging. The Dolinar receiver exemplifies a rare instance of success in distinguishing between two coherent states: an adaptive local oscillator is mixed with the signal prior to photodetection, which yields an error probability that meets the Helstrom lower bound with equality. Here we apply the same local-oscillator-based architecture with aninformation-theoretic optimization criterion. We begin with analysis of this receiver in a general framework for an arbitrary coherent-state modulation alphabet, and then we concentrate on two relevant examples. First, we study a binary antipodal alphabet and show that the Dolinar receiver's feedback function not only minimizes the probability of error, but also maximizes the mutual information. Next, we study ternary modulation consistingof antipodal coherent states and the vacuum state. We derive an analytic expression for a near-optimal local oscillator feedback function, and, via simulation, we determine its photon information efficiency (PIE). We provide the PIE versus dimensional information efficiency (DIE) trade-off curve and show that this modulation and the our receiver combination performs universally better than (generalized) on-off keying plus photoncounting, although, the advantage asymptotically vanishes as the bits-per-photon diverges towards infinity.

Optimization methodology for the global 10 Hz orbit feedback in RHIC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Chuyu; Hulsart, R.; Mernick, K.

To combat beam oscillations induced by triplet vibrations at the Relativistic Heavy Ion Collider (RHIC), a global orbit feedback system was developed and applied at injection and top energy in 2011, and during beam acceleration in 2012. Singular Value Decomposition (SVD) was employed to determine the strengths and currents of the applied corrections. The feedback algorithm was optimized for different magnetic configurations (lattices) at fixed beam energies and during beam acceleration. While the orbit feedback performed well since its inception, corrector current transients and feedback-induced beam oscillations were observed during the polarized proton program in 2015. In this paper, wemore » present the feedback algorithm, the optimization of the algorithm for various lattices and the solution adopted to mitigate the observed current transients during beam acceleration.« less

Optimization methodology for the global 10 Hz orbit feedback in RHIC

DOE PAGES

Liu, Chuyu; Hulsart, R.; Mernick, K.; ...

2018-05-08

To combat beam oscillations induced by triplet vibrations at the Relativistic Heavy Ion Collider (RHIC), a global orbit feedback system was developed and applied at injection and top energy in 2011, and during beam acceleration in 2012. Singular Value Decomposition (SVD) was employed to determine the strengths and currents of the applied corrections. The feedback algorithm was optimized for different magnetic configurations (lattices) at fixed beam energies and during beam acceleration. While the orbit feedback performed well since its inception, corrector current transients and feedback-induced beam oscillations were observed during the polarized proton program in 2015. In this paper, wemore » present the feedback algorithm, the optimization of the algorithm for various lattices and the solution adopted to mitigate the observed current transients during beam acceleration.« less

Adaptive self-organization of Bali's ancient rice terraces.

PubMed

Lansing, J Stephen; Thurner, Stefan; Chung, Ning Ning; Coudurier-Curveur, Aurélie; Karakaş, Çağil; Fesenmyer, Kurt A; Chew, Lock Yue

2017-06-20

Spatial patterning often occurs in ecosystems as a result of a self-organizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers' decisions and the ecology of the paddies, which triggers a transition from local to global-scale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers' decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human-natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.

Neural dynamic programming and its application to control systems

NASA Astrophysics Data System (ADS)

Seong, Chang-Yun

There are few general practical feedback control methods for nonlinear MIMO (multi-input-multi-output) systems, although such methods exist for their linear counterparts. Neural Dynamic Programming (NDP) is proposed as a practical design method of optimal feedback controllers for nonlinear MIMO systems. NDP is an offspring of both neural networks and optimal control theory. In optimal control theory, the optimal solution to any nonlinear MIMO control problem may be obtained from the Hamilton-Jacobi-Bellman equation (HJB) or the Euler-Lagrange equations (EL). The two sets of equations provide the same solution in different forms: EL leads to a sequence of optimal control vectors, called Feedforward Optimal Control (FOC); HJB yields a nonlinear optimal feedback controller, called Dynamic Programming (DP). DP produces an optimal solution that can reject disturbances and uncertainties as a result of feedback. Unfortunately, computation and storage requirements associated with DP solutions can be problematic, especially for high-order nonlinear systems. This dissertation presents an approximate technique for solving the DP problem based on neural network techniques that provides many of the performance benefits (e.g., optimality and feedback) of DP and benefits from the numerical properties of neural networks. We formulate neural networks to approximate optimal feedback solutions whose existence DP justifies. We show the conditions under which NDP closely approximates the optimal solution. Finally, we introduce the learning operator characterizing the learning process of the neural network in searching the optimal solution. The analysis of the learning operator provides not only a fundamental understanding of the learning process in neural networks but also useful guidelines for selecting the number of weights of the neural network. As a result, NDP finds---with a reasonable amount of computation and storage---the optimal feedback solutions to nonlinear MIMO control problems that would be very difficult to solve with DP. NDP was demonstrated on several applications such as the lateral autopilot logic for a Boeing 747, the minimum fuel control of a double-integrator plant with bounded control, the backward steering of a two-trailer truck, and the set-point control of a two-link robot arm.

Cyber-Physical Attacks With Control Objectives

DOE PAGES

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2017-08-18

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based onmore » a remotely controlled helicopter under attack.« less

Cyber-Physical Attacks With Control Objectives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

This study studies attackers with control objectives against cyber-physical systems (CPSs). The goal of the attacker is to counteract the CPS's controller and move the system to a target state while evading detection. We formulate a cost function that reflects the attacker's goals, and, using dynamic programming, we show that the optimal attack strategy reduces to a linear feedback of the attacker's state estimate. By changing the parameters of the cost function, we show how an attacker can design optimal attacks to balance the control objective and the detection avoidance objective. In conclusion, we provide a numerical illustration based onmore » a remotely controlled helicopter under attack.« less

Optimal control of coupled parabolic-hyperbolic non-autonomous PDEs: infinite-dimensional state-space approach

NASA Astrophysics Data System (ADS)

Aksikas, I.; Moghadam, A. Alizadeh; Forbes, J. F.

2018-04-01

This paper deals with the design of an optimal state-feedback linear-quadratic (LQ) controller for a system of coupled parabolic-hypebolic non-autonomous partial differential equations (PDEs). The infinite-dimensional state space representation and the corresponding operator Riccati differential equation are used to solve the control problem. Dynamical properties of the coupled system of interest are analysed to guarantee the existence and uniqueness of the solution of the LQ-optimal control problem and also to guarantee the exponential stability of the closed-loop system. Thanks to the eigenvalues and eigenfunctions of the parabolic operator and also the fact that the hyperbolic-associated operator Riccati differential equation can be converted to a scalar Riccati PDE, an algorithm to solve the LQ control problem has been presented. The results are applied to a non-isothermal packed-bed catalytic reactor. The LQ optimal controller designed in the early portion of the paper is implemented for the original non-linear model. Numerical simulations are performed to show the controller performances.

Investigation, development, and application of optimal output feedback theory. Volume 3: The relationship between dynamic compensators and observers and Kalman filters

NASA Technical Reports Server (NTRS)

Broussard, John R.

1987-01-01

Relationships between observers, Kalman Filters and dynamic compensators using feedforward control theory are investigated. In particular, the relationship, if any, between the dynamic compensator state and linear functions of a discrete plane state are investigated. It is shown that, in steady state, a dynamic compensator driven by the plant output can be expressed as the sum of two terms. The first term is a linear combination of the plant state. The second term depends on plant and measurement noise, and the plant control. Thus, the state of the dynamic compensator can be expressed as an estimator of the first term with additive error given by the second term. Conditions under which a dynamic compensator is a Kalman filter are presented, and reduced-order optimal estimaters are investigated.

Optimizing the feedback control of Galvo scanners for laser manufacturing systems

NASA Astrophysics Data System (ADS)

Mirtchev, Theodore; Weeks, Robert; Minko, Sergey

2010-06-01

This paper summarizes the factors that limit the performance of moving-magnet galvo scanners driven by closed-loop digital servo amplifiers: torsional resonances, drifts, nonlinearities, feedback noise and friction. Then it describes a detailed Simulink® simulator that takes into account these factors and can be used to automatically tune the controller for best results with given galvo type and trajectory patterns. It allows for rapid testing of different control schemes, for instance combined position/velocity PID loops and displays the corresponding output in terms of torque, angular position and feedback sensor signal. The tool is configurable and can either use a dynamical state-space model of galvo's open-loop response, or can import the experimentally measured frequency domain transfer function. Next a drive signal digital pre-filtering technique is discussed. By performing a real-time Fourier analysis of the raw command signal it can be pre-warped to minimize all harmonics around the torsional resonances while boosting other non-resonant high frequencies. The optimized waveform results in much smaller overshoot and better settling time. Similar performance gain cannot be extracted from the servo controller alone.

LMI-Based Fuzzy Optimal Variance Control of Airfoil Model Subject to Input Constraints

NASA Technical Reports Server (NTRS)

Swei, Sean S.M.; Ayoubi, Mohammad A.

2017-01-01

This paper presents a study of fuzzy optimal variance control problem for dynamical systems subject to actuator amplitude and rate constraints. Using Takagi-Sugeno fuzzy modeling and dynamic Parallel Distributed Compensation technique, the stability and the constraints can be cast as a multi-objective optimization problem in the form of Linear Matrix Inequalities. By utilizing the formulations and solutions for the input and output variance constraint problems, we develop a fuzzy full-state feedback controller. The stability and performance of the proposed controller is demonstrated through its application to the airfoil flutter suppression.

An optimal controller for an electric ventricular-assist device: theory, implementation, and testing.

PubMed

Klute, G K; Tasch, U; Geselowitz, D B

1992-04-01

This paper addresses the development and testing of an optimal position feedback controller for the Penn State electric ventricular-assist device (EVAD). The control law is designed to minimize the expected value of the EVAD's power consumption for a targeted patient population. The closed-loop control law is implemented on an Intel 8096 microprocessor and in vitro test runs show that this controller improves the EVAD's efficiency by 15-21%, when compared with the performance of the currently used feedforward control scheme.

Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

PubMed

Lewis, F L; Vamvoudakis, Kyriakos G

2011-02-01

Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.

Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB's Toolbox

PubMed Central

Mahmoodabadi, M. J.; Taherkhorsandi, M.; Bagheri, A.

2014-01-01

An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot. PMID:24616619

When More Is Less: Feedback Effects in Perceptual Category Learning

ERIC Educational Resources Information Center

Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent

2008-01-01

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether…

Interference Alignment With Partial CSI Feedback in MIMO Cellular Networks

NASA Astrophysics Data System (ADS)

Rao, Xiongbin; Lau, Vincent K. N.

2014-04-01

Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. However, most existing IA designs require full channel state information (CSI) at the transmitters, which would lead to significant CSI signaling overhead. There are two techniques, namely CSI quantization and CSI feedback filtering, to reduce the CSI feedback overhead. In this paper, we consider IA processing with CSI feedback filtering in MIMO cellular networks. We introduce a novel metric, namely the feedback dimension, to quantify the first order CSI feedback cost associated with the CSI feedback filtering. The CSI feedback filtering poses several important challenges in IA processing. First, there is a hidden partial CSI knowledge constraint in IA precoder design which cannot be handled using conventional IA design methodology. Furthermore, existing results on the feasibility conditions of IA cannot be applied due to the partial CSI knowledge. Finally, it is very challenging to find out how much CSI feedback is actually needed to support IA processing. We shall address the above challenges and propose a new IA feasibility condition under partial CSIT knowledge in MIMO cellular networks. Based on this, we consider the CSI feedback profile design subject to the degrees of freedom requirements, and we derive closed-form trade-off results between the CSI feedback cost and IA performance in MIMO cellular networks.

Finite-time H∞ control for a class of discrete-time switched time-delay systems with quantized feedback

NASA Astrophysics Data System (ADS)

Song, Haiyu; Yu, Li; Zhang, Dan; Zhang, Wen-An

2012-12-01

This paper is concerned with the finite-time quantized H∞ control problem for a class of discrete-time switched time-delay systems with time-varying exogenous disturbances. By using the sector bound approach and the average dwell time method, sufficient conditions are derived for the switched system to be finite-time bounded and ensure a prescribed H∞ disturbance attenuation level, and a mode-dependent quantized state feedback controller is designed by solving an optimization problem. Two illustrative examples are provided to demonstrate the effectiveness of the proposed theoretical results.

Two neural network algorithms for designing optimal terminal controllers with open final time

NASA Technical Reports Server (NTRS)

Plumer, Edward S.

1992-01-01

Multilayer neural networks, trained by the backpropagation through time algorithm (BPTT), have been used successfully as state-feedback controllers for nonlinear terminal control problems. Current BPTT techniques, however, are not able to deal systematically with open final-time situations such as minimum-time problems. Two approaches which extend BPTT to open final-time problems are presented. In the first, a neural network learns a mapping from initial-state to time-to-go. In the second, the optimal number of steps for each trial run is found using a line-search. Both methods are derived using Lagrange multiplier techniques. This theoretical framework is used to demonstrate that the derived algorithms are direct extensions of forward/backward sweep methods used in N-stage optimal control. The two algorithms are tested on a Zermelo problem and the resulting trajectories compare favorably to optimal control results.

Decoupling feedforward and feedback structures in hybrid active noise control systems for uncorrelated narrowband disturbances

NASA Astrophysics Data System (ADS)

Wu, Lifu; Qiu, Xiaojun; Burnett, Ian S.; Guo, Yecai

2015-08-01

Hybrid feedforward and feedback structures are useful for active noise control (ANC) applications where the noise can only be partially obtained with reference sensors. The traditional method uses the secondary signals of both the feedforward and feedback structures to synthesize a reference signal for the feedback structure in the hybrid structure. However, this approach introduces coupling between the feedforward and feedback structures and parameter changes in one structure affect the other during adaptation such that the feedforward and feedback structures must be optimized simultaneously in practical ANC system design. Two methods are investigated in this paper to remove such coupling effects. One is a simplified method, which uses the error signal directly as the reference signal in the feedback structure, and the second method generates the reference signal for the feedback structure by using only the secondary signal from the feedback structure and utilizes the generated reference signal as the error signal of the feedforward structure. Because the two decoupling methods can optimize the feedforward and feedback structures separately, they provide more flexibility in the design and optimization of the adaptive filters in practical ANC applications.

Optimal run-and-tumble-based transportation of a Janus particle with active steering

NASA Astrophysics Data System (ADS)

Mano, Tomoyuki; Delfau, Jean-Baptiste; Iwasawa, Junichiro; Sano, Masaki

2017-03-01

Although making artificial micrometric swimmers has been made possible by using various propulsion mechanisms, guiding their motion in the presence of thermal fluctuations still remains a great challenge. Such a task is essential in biological systems, which present a number of intriguing solutions that are robust against noisy environmental conditions as well as variability in individual genetic makeup. Using synthetic Janus particles driven by an electric field, we present a feedback-based particle-guiding method quite analogous to the “run-and-tumbling” behavior of Escherichia coli but with a deterministic steering in the tumbling phase: the particle is set to the run state when its orientation vector aligns with the target, whereas the transition to the “steering” state is triggered when it exceeds a tolerance angle αα. The active and deterministic reorientation of the particle is achieved by a characteristic rotational motion that can be switched on and off by modulating the ac frequency of the electric field, which is reported in this work. Relying on numerical simulations and analytical results, we show that this feedback algorithm can be optimized by tuning the tolerance angle αα. The optimal resetting angle depends on signal to noise ratio in the steering state, and it is shown in the experiment. The proposed method is simple and robust for targeting, despite variability in self-propelling speeds and angular velocities of individual particles.

Trajectory optimization for the National Aerospace Plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1992-01-01

The primary objective of this research is to develop an efficient and robust trajectory optimization tool for the optimal ascent problem of the National Aerospace Plane (NASP). This report is organized in the following order to summarize the complete work: Section two states the formulation and models of the trajectory optimization problem. An inverse dynamics approach to the problem is introduced in Section three. Optimal trajectories corresponding to various conditions and performance parameters are presented in Section four. A midcourse nonlinear feedback controller is developed in Section five. Section six demonstrates the performance of the inverse dynamics approach and midcourse controller during disturbances. Section seven discusses rocket assisted ascent which may be beneficial when orbital altitude is high. Finally, Section eight recommends areas of future research.

Optimality and stability of intentional and unintentional actions: I. Origins of drifts in performance.

PubMed

Parsa, Behnoosh; Terekhov, Alexander; Zatsiorsky, Vladimir M; Latash, Mark L

2017-02-01

We address the nature of unintentional changes in performance in two papers. This first paper tested a hypothesis that unintentional changes in performance variables during continuous tasks without visual feedback are due to two processes. First, there is a drift of the referent coordinate for the salient performance variable toward the actual coordinate of the effector. Second, there is a drift toward minimum of a cost function. We tested this hypothesis in four-finger isometric pressing tasks that required the accurate production of a combination of total moment and total force with natural and modified finger involvement. Subjects performed accurate force-moment production tasks under visual feedback, and then visual feedback was removed for some or all of the salient variables. Analytical inverse optimization was used to compute a cost function. Without visual feedback, both force and moment drifted slowly toward lower absolute magnitudes. Over 15 s, the force drop could reach 20% of its initial magnitude while moment drop could reach 30% of its initial magnitude. Individual finger forces could show drifts toward both higher and lower forces. The cost function estimated using the analytical inverse optimization reduced its value as a consequence of the drift. We interpret the results within the framework of hierarchical control with referent spatial coordinates for salient variables at each level of the hierarchy combined with synergic control of salient variables. The force drift is discussed as a natural relaxation process toward states with lower potential energy in the physical (physiological) system involved in the task.

Optimality and stability of intentional and unintentional actions: I. Origins of drifts in performance

PubMed Central

Parsa, Behnoosh; Terekhov, Alexander; Zatsiorsky, Vladimir M.; Latash, Mark L.

2016-01-01

We address the nature of unintentional changes in performance in two papers. This first paper tested a hypothesis that unintentional changes in performance variables during continuous tasks without visual feedback are due to two processes. First, there is a drift of the referent coordinate for the salient performance variable toward the actual coordinate of the effector. Second, there is a drift toward minimum of a cost function. We tested this hypothesis in four-finger isometric pressing tasks that required the accurate production of a combination of total moment and total force with natural and modified finger involvement. Subjects performed accurate force/moment production tasks under visual feedback, and then visual feedback was removed for some or all of the salient variables. Analytical inverse optimization was used to compute a cost function. Without visual feedback, both force and moment drifted slowly toward lower absolute magnitudes. Over 15 s, the force drop could reach 20% of its initial magnitude while moment drop could reach 30% of its initial magnitude. Individual finger forces could show drifts toward both higher and lower forces. The cost function estimated using the analytical inverse optimization reduced its value as a consequence of the drift. We interpret the results within the framework of hierarchical control with referent spatial coordinates for salient variables at each level of the hierarchy combined with synergic control of salient variables. The force drift is discussed as a natural relaxation process toward states with lower potential energy in the physical (physiological) system involved in the task. PMID:27785549

Switching State-Feedback LPV Control with Uncertain Scheduling Parameters

NASA Technical Reports Server (NTRS)

He, Tianyi; Al-Jiboory, Ali Khudhair; Swei, Sean Shan-Min; Zhu, Guoming G.

2017-01-01

This paper presents a new method to design Robust Switching State-Feedback Gain-Scheduling (RSSFGS) controllers for Linear Parameter Varying (LPV) systems with uncertain scheduling parameters. The domain of scheduling parameters are divided into several overlapped subregions to undergo hysteresis switching among a family of simultaneously designed LPV controllers over the corresponding subregion with the guaranteed H-infinity performance. The synthesis conditions are given in terms of Parameterized Linear Matrix Inequalities that guarantee both stability and performance at each subregion and associated switching surfaces. The switching stability is ensured by descent parameter-dependent Lyapunov function on switching surfaces. By solving the optimization problem, RSSFGS controller can be obtained for each subregion. A numerical example is given to illustrate the effectiveness of the proposed approach over the non-switching controllers.

Achieving optimal growth: lessons from simple metabolic modules

NASA Astrophysics Data System (ADS)

Goyal, Sidhartha; Chen, Thomas; Wingreen, Ned

2009-03-01

Metabolism is a universal property of living organisms. While the metabolic network itself has been well characterized, the logic of its regulation remains largely mysterious. Recent work has shown that growth rates of microorganisms, including the bacterium Escherichia coli, correlate well with optimal growth rates predicted by flux-balance analysis (FBA), a constraint-based computational method. How difficult is it for cells to achieve optimal growth? Our analysis of representative metabolic modules drawn from real metabolism shows that, in all cases, simple feedback inhibition allows nearly optimal growth. Indeed, product-feedback inhibition is found in every biosynthetic pathway and constitutes about 80% of metabolic regulation. However, we find that product-feedback systems designed to approach optimal growth necessarily produce large pool sizes of metabolites, with potentially detrimental effects on cells via toxicity and osmotic imbalance. Interestingly, the sizes of metabolite pools can be strongly restricted if the feedback inhibition is ultrasensitive (i.e. with high Hill coefficient). The need for ultrasensitive mechanisms to limit pool sizes may therefore explain some of the ubiquitous, puzzling complexity found in metabolic feedback regulation at both the transcriptional and post-transcriptional levels.

Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean

DOE Office of Scientific and Technical Information (OSTI.GOV)

Razooky, Brandon S.; Cao, Youfang; Hansen, Maike M. K.

Fundamental to biological decision-making is the ability to generate bimodal expression patterns where two alternate expression states simultaneously exist. Here in this study, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV’s fate decision between active replication and viral latency. We find that the HIV Tat protein manipulates the intrinsic toggling of HIV’s promoter, the LTR, to generate bimodal ON-OFF expression, and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-lengthmore » virus. Strikingly, computational analysis indicates that the Tat circuit’s non-cooperative ‘non-latching’ feedback architecture is optimized to slow the promoter’s toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that non-latching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean-expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV’s decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.« less

Optimizing electricity consumption: A case of function learning.

PubMed

Guath, Mona; Millroth, Philip; Juslin, Peter; Elwin, Ebba

2015-12-01

A popular way to improve consumers' control over their electricity consumption is by providing outcome feedback on the cost with in-home displays. Research on function learning, however, suggests that outcome feedback may not always be ideal for learning, especially if the feedback signal is noisy. In this study, we relate research on function learning to in-home displays and use a laboratory task simulating a household to investigate the role of outcome feedback and function learning on electricity optimization. Three function training schemes (FTSs) are presented that convey specific properties of the functions that relate the electricity consumption to the utility and cost. In Experiment 1, we compared learning from outcome feedback with 3 FTSs, 1 of which allowed maximization of the utility while keeping the budget, despite no feedback about the total monthly cost. In Experiment 2, we explored the combination of this FTS and outcome feedback. The results suggested that electricity optimization may be facilitated if feedback learning is preceded by a brief period of function training. (c) 2015 APA, all rights reserved).

Adaptation, Growth, and Resilience in Biological Distribution Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.

Digital flight control systems

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Vanlandingham, H. F.

1977-01-01

The design of stable feedback control laws for sampled-data systems with variable rate sampling was investigated. These types of sampled-data systems arise naturally in digital flight control systems which use digital actuators where it is desirable to decrease the number of control computer output commands in order to save wear and tear of the associated equipment. The design of aircraft control systems which are optimally tolerant of sensor and actuator failures was also studied. Detection of the failed sensor or actuator must be resolved and if the estimate of the state is used in the control law, then it is also desirable to have an estimator which will give the optimal state estimate even under the failed conditions.

Spacecraft attitude control using neuro-fuzzy approximation of the optimal controllers

NASA Astrophysics Data System (ADS)

Kim, Sung-Woo; Park, Sang-Young; Park, Chandeok

2016-01-01

In this study, a neuro-fuzzy controller (NFC) was developed for spacecraft attitude control to mitigate large computational load of the state-dependent Riccati equation (SDRE) controller. The NFC was developed by training a neuro-fuzzy network to approximate the SDRE controller. The stability of the NFC was numerically verified using a Lyapunov-based method, and the performance of the controller was analyzed in terms of approximation ability, steady-state error, cost, and execution time. The simulations and test results indicate that the developed NFC efficiently approximates the SDRE controller, with asymptotic stability in a bounded region of angular velocity encompassing the operational range of rapid-attitude maneuvers. In addition, it was shown that an approximated optimal feedback controller can be designed successfully through neuro-fuzzy approximation of the optimal open-loop controller.

Cross-entropy optimization for neuromodulation.

PubMed

Brar, Harleen K; Yunpeng Pan; Mahmoudi, Babak; Theodorou, Evangelos A

2016-08-01

This study presents a reinforcement learning approach for the optimization of the proportional-integral gains of the feedback controller represented in a computational model of epilepsy. The chaotic oscillator model provides a feedback control systems view of the dynamics of an epileptic brain with an internal feedback controller representative of the natural seizure suppression mechanism within the brain circuitry. Normal and pathological brain activity is simulated in this model by adjusting the feedback gain values of the internal controller. With insufficient gains, the internal controller cannot provide enough feedback to the brain dynamics causing an increase in correlation between different brain sites. This increase in synchronization results in the destabilization of the brain dynamics, which is representative of an epileptic seizure. To provide compensation for an insufficient internal controller an external controller is designed using proportional-integral feedback control strategy. A cross-entropy optimization algorithm is applied to the chaotic oscillator network model to learn the optimal feedback gains for the external controller instead of hand-tuning the gains to provide sufficient control to the pathological brain and prevent seizure generation. The correlation between the dynamics of neural activity within different brain sites is calculated for experimental data to show similar dynamics of epileptic neural activity as simulated by the network of chaotic oscillators.

Feedback laws for fuel minimization for transport aircraft

NASA Technical Reports Server (NTRS)

Price, D. B.; Gracey, C.

1984-01-01

The Theoretical Mechanics Branch has as one of its long-range goals to work toward solving real-time trajectory optimization problems on board an aircraft. This is a generic problem that has application to all aspects of aviation from general aviation through commercial to military. Overall interest is in the generic problem, but specific problems to achieve concrete results are examined. The problem is to develop control laws that generate approximately optimal trajectories with respect to some criteria such as minimum time, minimum fuel, or some combination of the two. These laws must be simple enough to be implemented on a computer that is flown on board an aircraft, which implies a major simplification from the two point boundary value problem generated by a standard trajectory optimization problem. In addition, the control laws allow for changes in end conditions during the flight, and changes in weather along a planned flight path. Therefore, a feedback control law that generates commands based on the current state rather than a precomputed open-loop control law is desired. This requirement, along with the need for order reduction, argues for the application of singular perturbation techniques.

Choosing Sensor Configuration for a Flexible Structure Using Full Control Synthesis

NASA Technical Reports Server (NTRS)

Lind, Rick; Nalbantoglu, Volkan; Balas, Gary

1997-01-01

Optimal locations and types for feedback sensors which meet design constraints and control requirements are difficult to determine. This paper introduces an approach to choosing a sensor configuration based on Full Control synthesis. A globally optimal Full Control compensator is computed for each member of a set of sensor configurations which are feasible for the plant. The sensor configuration associated with the Full Control system achieving the best closed-loop performance is chosen for feedback measurements to an output feedback controller. A flexible structure is used as an example to demonstrate this procedure. Experimental results show sensor configurations chosen to optimize the Full Control performance are effective for output feedback controllers.

Physics-model-based nonlinear actuator trajectory optimization and safety factor profile feedback control for advanced scenario development in DIII-D

DOE PAGES

Barton, Justin E.; Boyer, Mark D.; Shi, Wenyu; ...

2015-07-30

DIII-D experimental results are reported to demonstrate the potential of physics-model-based safety factor profile control for robust and reproducible sustainment of advanced scenarios. In the absence of feedback control, variability in wall conditions and plasma impurities, as well as drifts due to external disturbances, can limit the reproducibility of discharges with simple pre-programmed scenario trajectories. The control architecture utilized is a feedforward + feedback scheme where the feedforward commands are computed off-line and the feedback commands are computed on-line. In this work, firstly a first-principles-driven (FPD), physics-based model of the q profile and normalized beta (β N) dynamics is embeddedmore » into a numerical optimization algorithm to design feedforward actuator trajectories that sheer the plasma through the tokamak operating space to reach a desired stationary target state that is characterized by the achieved q profile and β N. Good agreement between experimental results and simulations demonstrates the accuracy of the models employed for physics-model-based control design. Secondly, a feedback algorithm for q profile control is designed following a FPD approach, and the ability of the controller to achieve and maintain a target q profile evolution is tested in DIII-D high confinement (H-mode) experiments. The controller is shown to be able to effectively control the q profile when β N is relatively close to the target, indicating the need for integrated q profile and β N control to further enhance the ability to achieve robust scenario execution. Furthermore, the ability of an integrated q profile + β N feedback controller to track a desired target is demonstrated through simulation.« less

A Simplified Algorithm for Statistical Investigation of Damage Spreading

NASA Astrophysics Data System (ADS)

Gecow, Andrzej

2009-04-01

On the way to simulating adaptive evolution of complex system describing a living object or human developed project, a fitness should be defined on node states or network external outputs. Feedbacks lead to circular attractors of these states or outputs which make it difficult to define a fitness. The main statistical effects of adaptive condition are the result of small change tendency and to appear, they only need a statistically correct size of damage initiated by evolutionary change of system. This observation allows to cut loops of feedbacks and in effect to obtain a particular statistically correct state instead of a long circular attractor which in the quenched model is expected for chaotic network with feedback. Defining fitness on such states is simple. We calculate only damaged nodes and only once. Such an algorithm is optimal for investigation of damage spreading i.e. statistical connections of structural parameters of initial change with the size of effected damage. It is a reversed-annealed method—function and states (signals) may be randomly substituted but connections are important and are preserved. The small damages important for adaptive evolution are correctly depicted in comparison to Derrida annealed approximation which expects equilibrium levels for large networks. The algorithm indicates these levels correctly. The relevant program in Pascal, which executes the algorithm for a wide range of parameters, can be obtained from the author.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gecow, Andrzej

On the way to simulating adaptive evolution of complex system describing a living object or human developed project, a fitness should be defined on node states or network external outputs. Feedbacks lead to circular attractors of these states or outputs which make it difficult to define a fitness. The main statistical effects of adaptive condition are the result of small change tendency and to appear, they only need a statistically correct size of damage initiated by evolutionary change of system. This observation allows to cut loops of feedbacks and in effect to obtain a particular statistically correct state instead ofmore » a long circular attractor which in the quenched model is expected for chaotic network with feedback. Defining fitness on such states is simple. We calculate only damaged nodes and only once. Such an algorithm is optimal for investigation of damage spreading i.e. statistical connections of structural parameters of initial change with the size of effected damage. It is a reversed-annealed method--function and states (signals) may be randomly substituted but connections are important and are preserved. The small damages important for adaptive evolution are correctly depicted in comparison to Derrida annealed approximation which expects equilibrium levels for large networks. The algorithm indicates these levels correctly. The relevant program in Pascal, which executes the algorithm for a wide range of parameters, can be obtained from the author.« less

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarmmore » rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.« less

Optimal Attack Strategies Subject to Detection Constraints Against Cyber-Physical Systems

DOE PAGES

Chen, Yuan; Kar, Soummya; Moura, Jose M. F.

2017-03-31

This paper studies an attacker against a cyberphysical system (CPS) whose goal is to move the state of a CPS to a target state while ensuring that his or her probability of being detected does not exceed a given bound. The attacker’s probability of being detected is related to the nonnegative bias induced by his or her attack on the CPS’s detection statistic. We formulate a linear quadratic cost function that captures the attacker’s control goal and establish constraints on the induced bias that reflect the attacker’s detection-avoidance objectives. When the attacker is constrained to be detected at the false-alarmmore » rate of the detector, we show that the optimal attack strategy reduces to a linear feedback of the attacker’s state estimate. In the case that the attacker’s bias is upper bounded by a positive constant, we provide two algorithms – an optimal algorithm and a sub-optimal, less computationally intensive algorithm – to find suitable attack sequences. Lastly, we illustrate our attack strategies in numerical examples based on a remotely-controlled helicopter under attack.« less

Computational alternatives to obtain time optimal jet engine control. M.S. Thesis

NASA Technical Reports Server (NTRS)

Basso, R. J.; Leake, R. J.

1976-01-01

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

Realizable optimal control for a remotely piloted research vehicle. [stability augmentation

NASA Technical Reports Server (NTRS)

Dunn, H. J.

1980-01-01

The design of a control system using the linear-quadratic regulator (LQR) control law theory for time invariant systems in conjunction with an incremental gradient procedure is presented. The incremental gradient technique reduces the full-state feedback controller design, generated by the LQR algorithm, to a realizable design. With a realizable controller, the feedback gains are based only on the available system outputs instead of being based on the full-state outputs. The design is for a remotely piloted research vehicle (RPRV) stability augmentation system. The design includes methods for accounting for noisy measurements, discrete controls with zero-order-hold outputs, and computational delay errors. Results from simulation studies of the response of the RPRV to a step in the elevator and frequency analysis techniques are included to illustrate these abnormalities and their influence on the controller design.

Catastrophic desert formation in Daisyworld.

PubMed

Ackland, Graeme J; Clark, Michael A; Lenton, Timothy M

2003-07-07

Feedback between life and its environment is ubiquitous but the strength of coupling and its global implications remain hotly debated. Abrupt changes in the abundance of life for small changes in forcing provide one indicator of regulation, for example, when vegetation-climate feedback collapses in the formation of a desert. Here we use a two-dimensional "Daisyworld" model with curvature to show that catastrophic collapse of life under gradual forcing provides a testable indicator of environmental feedback. When solar luminosity increases to a critical value, a desert forms across a wide band of the planet. The scale of collapse depends on the strength of feedback. The efficiency of temperature regulation is limited by mutation rate in an analogous manner to the limitation of adaptive fitness in evolutionary theories. The final state of the system emerging from single-site rules can be described by two global quantities: optimization of temperature regulation and maximization of diversity, which are mathematically analogous to energy and entropy in thermodynamics.

Assessing Feedback in a Mobile Videogame.

PubMed

Brand, Leah; Beltran, Alicia; Hughes, Sheryl; O'Connor, Teresia; Baranowski, Janice; Nicklas, Theresa; Chen, Tzu-An; Dadabhoy, Hafza R; Diep, Cassandra S; Buday, Richard; Baranowski, Tom

2016-06-01

Player feedback is an important part of serious games, although there is no consensus regarding its delivery or optimal content. "Mommio" is a serious game designed to help mothers motivate their preschoolers to eat vegetables. The purpose of this study was to assess optimal format and content of player feedback for use in "Mommio." The current study posed 36 potential "Mommio" gameplay feedback statements to 20 mothers using a Web survey and interview. Mothers were asked about the meaning and helpfulness of each feedback statement. Several themes emerged upon thematic analysis, including identifying an effective alternative in the case of corrective feedback, avoiding vague wording, using succinct and correct grammar, avoiding provocation of guilt, and clearly identifying why players' game choice was correct or incorrect. Guidelines are proposed for future feedback statements.

A global bioheat model with self-tuning optimal regulation of body temperature using Hebbian feedback covariance learning.

PubMed

Ong, M L; Ng, E Y K

2005-12-01

In the lower brain, body temperature is continually being regulated almost flawlessly despite huge fluctuations in ambient and physiological conditions that constantly threaten the well-being of the body. The underlying control problem defining thermal homeostasis is one of great enormity: Many systems and sub-systems are involved in temperature regulation and physiological processes are intrinsically complex and intertwined. Thus the defining control system has to take into account the complications of nonlinearities, system uncertainties, delayed feedback loops as well as internal and external disturbances. In this paper, we propose a self-tuning adaptive thermal controller based upon Hebbian feedback covariance learning where the system is to be regulated continually to best suit its environment. This hypothesis is supported in part by postulations of the presence of adaptive optimization behavior in biological systems of certain organisms which face limited resources vital for survival. We demonstrate the use of Hebbian feedback covariance learning as a possible self-adaptive controller in body temperature regulation. The model postulates an important role of Hebbian covariance adaptation as a means of reinforcement learning in the thermal controller. The passive system is based on a simplified 2-node core and shell representation of the body, where global responses are captured. Model predictions are consistent with observed thermoregulatory responses to conditions of exercise and rest, and heat and cold stress. An important implication of the model is that optimal physiological behaviors arising from self-tuning adaptive regulation in the thermal controller may be responsible for the departure from homeostasis in abnormal states, e.g., fever. This was previously unexplained using the conventional "set-point" control theory.

Assisted closed-loop optimization of SSVEP-BCI efficiency

PubMed Central

Fernandez-Vargas, Jacobo; Pfaff, Hanns U.; Rodríguez, Francisco B.; Varona, Pablo

2012-01-01

We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a closed-loop search for the best set of SSVEP flicker frequencies and (2) feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research. PMID:23443214

Assisted closed-loop optimization of SSVEP-BCI efficiency.

PubMed

Fernandez-Vargas, Jacobo; Pfaff, Hanns U; Rodríguez, Francisco B; Varona, Pablo

2013-01-01

We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a closed-loop search for the best set of SSVEP flicker frequencies and (2) feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research.

Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories.

PubMed

Faruque, Imraan A; Muijres, Florian T; Macfarlane, Kenneth M; Kehlenbeck, Andrew; Humbert, J Sean

2018-06-01

This paper presents "optimal identification," a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate.

Feedback Implementation of Zermelo's Optimal Control by Sugeno Approximation

NASA Technical Reports Server (NTRS)

Clifton, C.; Homaifax, A.; Bikdash, M.

1997-01-01

This paper proposes an approach to implement optimal control laws of nonlinear systems in real time. Our methodology does not require solving two-point boundary value problems online and may not require it off-line either. The optimal control law is learned using the original Sugeno controller (OSC) from a family of optimal trajectories. We compare the trajectories generated by the OSC and the trajectories yielded by the optimal feedback control law when applied to Zermelo's ship steering problem.

HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler

NASA Technical Reports Server (NTRS)

Hua, Hook; Mrozinski, Joseph J.; Elfes, Alberto; Adumitroaie, Virgil; Shelton, Kacie E.; Smith, Jeffrey H.; Lincoln, William P.; Weisbin, Charles R.

2012-01-01

HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.

Coherent Amplification of Ultrafast Molecular Dynamics in an Optical Oscillator

NASA Astrophysics Data System (ADS)

Aharonovich, Igal; Pe'er, Avi

2016-02-01

Optical oscillators present a powerful optimization mechanism. The inherent competition for the gain resources between possible modes of oscillation entails the prevalence of the most efficient single mode. We harness this "ultrafast" coherent feedback to optimize an optical field in time, and show that, when an optical oscillator based on a molecular gain medium is synchronously pumped by ultrashort pulses, a temporally coherent multimode field can develop that optimally dumps a general, dynamically evolving vibrational wave packet, into a single vibrational target state. Measuring the emitted field opens a new window to visualization and control of fast molecular dynamics. The realization of such a coherent oscillator with hot alkali dimers appears within experimental reach.

Assessing Feedback in a Mobile Videogame

PubMed Central

Brand, Leah; Beltran, Alicia; Hughes, Sheryl; O'Connor, Teresia; Baranowski, Janice; Nicklas, Theresa; Chen, Tzu-An; Dadabhoy, Hafza R.; Diep, Cassandra S.; Buday, Richard

2016-01-01

Abstract Background: Player feedback is an important part of serious games, although there is no consensus regarding its delivery or optimal content. “Mommio” is a serious game designed to help mothers motivate their preschoolers to eat vegetables. The purpose of this study was to assess optimal format and content of player feedback for use in “Mommio.” Materials and Methods: The current study posed 36 potential “Mommio” gameplay feedback statements to 20 mothers using a Web survey and interview. Mothers were asked about the meaning and helpfulness of each feedback statement. Results: Several themes emerged upon thematic analysis, including identifying an effective alternative in the case of corrective feedback, avoiding vague wording, using succinct and correct grammar, avoiding provocation of guilt, and clearly identifying why players' game choice was correct or incorrect. Conclusions: Guidelines are proposed for future feedback statements. PMID:27058403

Closed-form recursive formula for an optimal tracker with terminal constraints

NASA Technical Reports Server (NTRS)

Juang, J. N.; Turner, J. D.; Chun, H. M.

1986-01-01

Feedback control laws are derived for a class of optimal finite time tracking problems with terminal constraints. Analytical solutions are obtained for the feedback gain and the closed-loop response trajectory. Such formulations are expressed in recursive forms so that a real-time computer implementation becomes feasible. An example involving the feedback slewing of a flexible spacecraft is given to illustrate the validity and usefulness of the formulations.

A stochastic optimal feedforward and feedback control methodology for superagility

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Direskeneli, Haldun; Taylor, Deborah B.

1992-01-01

A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.

Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

PubMed Central

Liu, Xiaoli; Chen, Hong-Xin; Kim, Jinxie

2014-01-01

A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline. PMID:25025089

Optimization and evaluation of a proportional derivative controller for planar arm movement.

PubMed

Jagodnik, Kathleen M; van den Bogert, Antonie J

2010-04-19

In most clinical applications of functional electrical stimulation (FES), the timing and amplitude of electrical stimuli have been controlled by open-loop pattern generators. The control of upper extremity reaching movements, however, will require feedback control to achieve the required precision. Here we present three controllers using proportional derivative (PD) feedback to stimulate six arm muscles, using two joint angle sensors. Controllers were first optimized and then evaluated on a computational arm model that includes musculoskeletal dynamics. Feedback gains were optimized by minimizing a weighted sum of position errors and muscle forces. Generalizability of the controllers was evaluated by performing movements for which the controller was not optimized, and robustness was tested via model simulations with randomly weakened muscles. Robustness was further evaluated by adding joint friction and doubling the arm mass. After optimization with a properly weighted cost function, all PD controllers performed fast, accurate, and robust reaching movements in simulation. Oscillatory behavior was seen after improper tuning. Performance improved slightly as the complexity of the feedback gain matrix increased. Copyright 2009 Elsevier Ltd. All rights reserved.

Optimization and evaluation of a proportional derivative controller for planar arm movement

PubMed Central

Jagodnik, Kathleen M.; van den Bogert, Antonie J.

2013-01-01

In most clinical applications of functional electrical stimulation (FES), the timing and amplitude of electrical stimuli have been controlled by open-loop pattern generators. The control of upper extremity reaching movements, however, will require feedback control to achieve the required precision. Here we present three controllers using proportional derivative (PD) feedback to stimulate six arm muscles, using two joint angle sensors. Controllers were first optimized and then evaluated on a computational arm model that includes musculoskeletal dynamics. Feedback gains were optimized by minimizing a weighted sum of position errors and muscle forces. Generalizability of the controllers was evaluated by performing movements for which the controller was not optimized, and robustness was tested via model simulations with randomly weakened muscles. Robustness was further evaluated by adding joint friction and doubling the arm mass. After optimization with a properly weighted cost function, all PD controllers performed fast, accurate, and robust reaching movements in simulation. Oscillatory behavior was seen after improper tuning. Performance improved slightly as the complexity of the feedback gain matrix increased. PMID:20097345

Research in Network Management Techniques for Tactical Data Communications Network.

DTIC Science & Technology

1982-09-01

the control period. Research areas include Packet Network modelling, adaptive network routing, network design algorithms, network design techniques...contro!lers are designed to perform their limited tasks optimally. For the dynamic routing problem considered here, the local controllers are node...feedback to finding in optimum stead-o-state routing (static strategies) under non - control which can be easily implemented in real time. congested

Stabilization of model-based networked control systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miranda, Francisco; Instituto Politécnico de Viana do Castelo, Viana do Castelo; Abreu, Carlos

2016-06-08

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtainmore » an optimal feedback control is also presented.« less

Tailored parameter optimization methods for ordinary differential equation models with steady-state constraints.

PubMed

Fiedler, Anna; Raeth, Sebastian; Theis, Fabian J; Hausser, Angelika; Hasenauer, Jan

2016-08-22

Ordinary differential equation (ODE) models are widely used to describe (bio-)chemical and biological processes. To enhance the predictive power of these models, their unknown parameters are estimated from experimental data. These experimental data are mostly collected in perturbation experiments, in which the processes are pushed out of steady state by applying a stimulus. The information that the initial condition is a steady state of the unperturbed process provides valuable information, as it restricts the dynamics of the process and thereby the parameters. However, implementing steady-state constraints in the optimization often results in convergence problems. In this manuscript, we propose two new methods for solving optimization problems with steady-state constraints. The first method exploits ideas from optimization algorithms on manifolds and introduces a retraction operator, essentially reducing the dimension of the optimization problem. The second method is based on the continuous analogue of the optimization problem. This continuous analogue is an ODE whose equilibrium points are the optima of the constrained optimization problem. This equivalence enables the use of adaptive numerical methods for solving optimization problems with steady-state constraints. Both methods are tailored to the problem structure and exploit the local geometry of the steady-state manifold and its stability properties. A parameterization of the steady-state manifold is not required. The efficiency and reliability of the proposed methods is evaluated using one toy example and two applications. The first application example uses published data while the second uses a novel dataset for Raf/MEK/ERK signaling. The proposed methods demonstrated better convergence properties than state-of-the-art methods employed in systems and computational biology. Furthermore, the average computation time per converged start is significantly lower. In addition to the theoretical results, the analysis of the dataset for Raf/MEK/ERK signaling provides novel biological insights regarding the existence of feedback regulation. Many optimization problems considered in systems and computational biology are subject to steady-state constraints. While most optimization methods have convergence problems if these steady-state constraints are highly nonlinear, the methods presented recover the convergence properties of optimizers which can exploit an analytical expression for the parameter-dependent steady state. This renders them an excellent alternative to methods which are currently employed in systems and computational biology.

Extensions to PIFCGT: Multirate output feedback and optimal disturbance suppression

NASA Technical Reports Server (NTRS)

Broussard, J. R.

1986-01-01

New control synthesis procedures for digital flight control systems were developed. The theoretical developments are the solution to the problem of optimal disturbance suppression in the presence of windshear. Control synthesis is accomplished using a linear quadratic cost function, the command generator tracker for trajectory following and the proportional-integral-filter control structure for practical implementation. Extensions are made to the optimal output feedback algorithm for computing feedback gains so that the multirate and optimal disturbance control designs are computed and compared for the advanced transport operating system (ATOPS). The performance of the designs is demonstrated by closed-loop poles, frequency domain multiinput sigma and eigenvalue plots and detailed nonlinear 6-DOF aircraft simulations in the terminal area in the presence of windshear.

Hybrid suboptimal control of multi-rate multi-loop sampled-data systems

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Chen, Gwangchywan; Tsai, Jason S. H.

1992-01-01

A hybrid state-space controller is developed for suboptimal digital control of multirate multiloop multivariable continuous-time systems. First, an LQR is designed for a continuous-time subsystem which has a large bandwidth and is connnected in the inner loop of the overall system. The designed LQR would optimally place the eigenvalues of a closed-loop subsystem in the common region of an open sector bounded by sector angles + or - pi/2k for k = 2 or 3 from the negative real axis and the left-hand side of a vertical line on the negative real axis in the s-plane. Then, the developed continuous-time state-feedback gain is converted into an equivalent fast-rate discrete-time state-feedback gain via a digital redesign technique (Tsai et al. 1989, Shieh et al. 1990) reviewed here. A real state reconstructor is redeveloped utilizing the fast-rate input-output data of the system of interest. The design procedure of multiloop multivariable systems using multirate samplers is shown, and a terminal homing missile system example is used to demonstrate the effectiveness of the proposed method.

Feedback-Based Projected-Gradient Method for Real-Time Optimization of Aggregations of Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize operational objectives of distribution-level distributed energy resources (DERs), while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power flows, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying convex optimization problem.« less

Feedback-Based Projected-Gradient Method For Real-Time Optimization of Aggregations of Energy Resources: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize the operational objectives of distribution-level distributed energy resources (DERs) while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying optimization problem.« less

Quantum demolition filtering and optimal control of unstable systems.

PubMed

Belavkin, V P

2012-11-28

A brief account of the quantum information dynamics and dynamical programming methods for optimal control of quantum unstable systems is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme, we exploit the separation theorem of filtering and control aspects as in the usual case of quantum stable systems with non-demolition observation. This allows us to start with the Belavkin quantum filtering equation generalized to demolition observations and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to Hamiltonian terms in the filtering equation. An unstable controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.

Neural networks for feedback feedforward nonlinear control systems.

PubMed

Parisini, T; Zoppoli, R

1994-01-01

This paper deals with the problem of designing feedback feedforward control strategies to drive the state of a dynamic system (in general, nonlinear) so as to track any desired trajectory joining the points of given compact sets, while minimizing a certain cost function (in general, nonquadratic). Due to the generality of the problem, conventional methods are difficult to apply. Thus, an approximate solution is sought by constraining control strategies to take on the structure of multilayer feedforward neural networks. After discussing the approximation properties of neural control strategies, a particular neural architecture is presented, which is based on what has been called the "linear-structure preserving principle". The original functional problem is then reduced to a nonlinear programming one, and backpropagation is applied to derive the optimal values of the synaptic weights. Recursive equations to compute the gradient components are presented, which generalize the classical adjoint system equations of N-stage optimal control theory. Simulation results related to nonlinear nonquadratic problems show the effectiveness of the proposed method.

Trajectory optimization for the National Aerospace Plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1993-01-01

The objective of this second phase research is to investigate the optimal ascent trajectory for the National Aerospace Plane (NASP) from runway take-off to orbital insertion and address the unique problems associated with the hypersonic flight trajectory optimization. The trajectory optimization problem for an aerospace plane is a highly challenging problem because of the complexity involved. Previous work has been successful in obtaining sub-optimal trajectories by using energy-state approximation and time-scale decomposition techniques. But it is known that the energy-state approximation is not valid in certain portions of the trajectory. This research aims at employing full dynamics of the aerospace plane and emphasizing direct trajectory optimization methods. The major accomplishments of this research include the first-time development of an inverse dynamics approach in trajectory optimization which enables us to generate optimal trajectories for the aerospace plane efficiently and reliably, and general analytical solutions to constrained hypersonic trajectories that has wide application in trajectory optimization as well as in guidance and flight dynamics. Optimal trajectories in abort landing and ascent augmented with rocket propulsion and thrust vectoring control were also investigated. Motivated by this study, a new global trajectory optimization tool using continuous simulated annealing and a nonlinear predictive feedback guidance law have been under investigation and some promising results have been obtained, which may well lead to more significant development and application in the near future.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements.

PubMed

Bonato, C; Blok, M S; Dinani, H T; Berry, D W; Markham, M L; Twitchen, D J; Hanson, R

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements

NASA Astrophysics Data System (ADS)

Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Asymmetric dual-loop feedback to suppress spurious tones and reduce timing jitter in self-mode-locked quantum-dash lasers emitting at 155 μm

NASA Astrophysics Data System (ADS)

Asghar, Haroon; McInerney, John G.

2017-09-01

We demonstrate an asymmetric dual-loop feedback scheme to suppress external cavity side-modes induced in self-mode-locked quantum-dash lasers with conventional single and dual-loop feedback. In this letter, we achieved optimal suppression of spurious tones by optimizing the length of second delay time. We observed that asymmetric dual-loop feedback, with large (~8x) disparity in cavity lengths, eliminates all external-cavity side-modes and produces flat RF spectra close to the main peak with low timing jitter compared to single-loop feedback. Significant reduction in RF linewidth and reduced timing jitter was also observed as a function of increased second feedback delay time. The experimental results based on this feedback configuration validate predictions of recently published numerical simulations. This interesting asymmetric dual-loop feedback scheme provides simplest, efficient and cost effective stabilization of side-band free optoelectronic oscillators based on mode-locked lasers.

When to throw the switch: The adaptiveness of modifying emotion regulation strategies based on affective and physiological feedback.

PubMed

Birk, Jeffrey L; Bonanno, George A

2016-08-01

Particular emotion regulation (ER) strategies are beneficial in certain contexts, but little is known about the adaptiveness of switching strategies after implementing an initial strategy. Research and theory on regulatory flexibility suggest that people switch strategies dynamically and that internal states provide feedback indicating when switches are appropriate. Frequent switching may predict positive outcomes among people who respond to this feedback. We investigated whether internal feedback (particularly corrugator activity, heart rate, or subjective negative intensity) guides people to switch to an optimal (i.e., distraction) but not nonoptimal (i.e., reappraisal) strategy for regulating strong emotion. We also tested whether switching frequency and responsiveness to internal feedback (RIF) together predict well-being. While attempting to regulate emotion elicited by unpleasant pictures, participants could switch to an optimal (Study 1; reappraisal-to-distraction order; N = 90) or nonoptimal (Study 2; distraction-to-reappraisal order; N = 95) strategy for high-arousal emotion. A RIF score for each emotion measure indexed the relative strength of emotion during the initial phase for trials on which participants later switched strategies. As hypothesized, negative intensity, corrugator activity, and the magnitude of heart rate deceleration during this early phase were higher on switch than maintain trials in Study 1 only. Critically, in Study 1 only, greater switching frequency predicted higher and lower life satisfaction for participants with high and low corrugator RIF, respectively, even after controlling for reappraisal success. Individual differences in RIF may contribute to subjective well-being provided that the direction of strategy switching aligns well with regulatory preferences for high emotion. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Control of linear uncertain systems utilizing mismatched state observers

NASA Technical Reports Server (NTRS)

Goldstein, B.

1972-01-01

The control of linear continuous dynamical systems is investigated as a problem of limited state feedback control. The equations which describe the structure of an observer are developed constrained to time-invarient systems. The optimal control problem is formulated, accounting for the uncertainty in the design parameters. Expressions for bounds on closed loop stability are also developed. The results indicate that very little uncertainty may be tolerated before divergence occurs in the recursive computation algorithms, and the derived stability bound yields extremely conservative estimates of regions of allowable parameter variations.

Integrated Assessment of Carbon Dioxide Removal

NASA Astrophysics Data System (ADS)

Rickels, W.; Reith, F.; Keller, D.; Oschlies, A.; Quaas, M. F.

2018-03-01

To maintain the chance of keeping the average global temperature increase below 2°C and to limit long-term climate change, removing carbon dioxide from the atmosphere (carbon dioxide removal, CDR) is becoming increasingly necessary. We analyze optimal and cost-effective climate policies in the dynamic integrated assessment model (IAM) of climate and the economy (DICE2016R) and investigate (1) the utilization of (ocean) CDR under different climate objectives, (2) the sensitivity of policies with respect to carbon cycle feedbacks, and (3) how well carbon cycle feedbacks are captured in the carbon cycle models used in state-of-the-art IAMs. Overall, the carbon cycle model in DICE2016R shows clear improvements compared to its predecessor, DICE2013R, capturing much better long-term dynamics and also oceanic carbon outgassing due to excess oceanic storage of carbon from CDR. However, this comes at the cost of a (too) tight short-term remaining emission budget, limiting the model suitability to analyze low-emission scenarios accurately. With DICE2016R, the compliance with the 2°C goal is no longer feasible without negative emissions via CDR. Overall, the optimal amount of CDR has to take into account (1) the emission substitution effect and (2) compensation for carbon cycle feedbacks.

Assessing feedback in a mobile videogame

USDA-ARS?s Scientific Manuscript database

Player feedback is an important part of serious games, although there is no consensus regarding its delivery or optimal content. "Mommio" is a serious game designed to help mothers motivate their preschoolers to eat vegetables. The purpose of this study was to assess optimal format and content of pl...

Lyapunov optimal feedback control of a nonlinear inverted pendulum

NASA Technical Reports Server (NTRS)

Grantham, W. J.; Anderson, M. J.

1989-01-01

Liapunov optimal feedback control is applied to a nonlinear inverted pendulum in which the control torque was constrained to be less than the nonlinear gravity torque in the model. This necessitates a control algorithm which 'rocks' the pendulum out of its potential wells, in order to stabilize it at a unique vertical position. Simulation results indicate that a preliminary Liapunov feedback controller can successfully overcome the nonlinearity and bring almost all trajectories to the target.

Dynamic imperfections and optimized feedback design in the Compact Linear Collider main linac

NASA Astrophysics Data System (ADS)

Eliasson, Peder

2008-05-01

The Compact Linear Collider (CLIC) main linac is sensitive to dynamic imperfections such as element jitter, injected beam jitter, and ground motion. These effects cause emittance growth that, in case of ground motion, has to be counteracted by a trajectory feedback system. The feedback system itself will, due to jitter effects and imperfect beam position monitors (BPMs), indirectly cause emittance growth. Fast and accurate simulations of both the direct and indirect effects are desirable, but due to the many elements of the CLIC main linac, simulations may become very time consuming. In this paper, an efficient way of simulating linear (or nearly linear) dynamic effects is described. The method is also shown to facilitate the analytic determination of emittance growth caused by the different dynamic imperfections while using a trajectory feedback system. Emittance growth expressions are derived for quadrupole, accelerating structure, and beam jitter, for ground motion, and for noise in the feedback BPMs. Finally, it is shown how the method can be used to design a feedback system that is optimized for the optics of the machine and the ground motion spectrum of the particular site. This feedback system gives an emittance growth rate that is approximately 10 times lower than that of traditional trajectory feedbacks. The robustness of the optimized feedback system is studied for a number of additional imperfections, e.g., dipole corrector imperfections and faulty knowledge about the machine optics, with promising results.

Optimizing Wastewater Reuse in Agricultural Fields via Merging of Embedded Network Sensor Data and Flow and Transport Models Using Data Assimilation

NASA Astrophysics Data System (ADS)

Wu, C.; Margulis, S. A.

2007-12-01

Wastewater re-use via crop irrigation has the potential to be an effective means of wastewater disposal. However, nitrate in wastewater may contaminate groundwater if it does not decay before reaching the groundwater table. In order to dispose of wastewater while preventing long-term groundwater pollution, irrigation rates need to be optimized based on the current and predicted states of the soil, such as soil moisture content and/or nitrate concentration. A real-time soil states estimation system using the Ensemble Kalman Filter (EnKF) has been developed for application to a test bed for wastewater re-use in Palmdale, CA. This test bed, covered with alfalfa, is a 30-acre irrigation plot with a 200-meter long rotating pivot arm that irrigates the area with reclaimed wastewater. A sensor network is deployed in the soil near the surface. The data assimilation system has shown the ability to characterize soil states and fluxes from sparse measurements. The real-time estimation system will then be used to explore the potential feedback for optimizing the sprinkler operation (i.e. maximizing the magnitude of wastewater release while minimizing the ultimate groundwater pollution). In optimization models, soil states and fluxes can be regarded as functions of irrigation rate. Through optimization, the irrigation rate in a finite horizon can be maximized while still satisfying all criteria in soil states and fluxes to ensure the safety of groundwater. Since the data assimilation system provides reliable estimation of soil states and fluxes, it is expected to define the optimal irrigation rate with higher confidence compared to using models or sensors only.

Resonant current in coupled inertial Brownian particles with delayed-feedback control

NASA Astrophysics Data System (ADS)

Gao, Tian-Fu; Zheng, Zhi-Gang; Chen, Jin-Can

2017-12-01

The transport of a walker in rocking feedback-controlled ratchets is investigated. The walker consists of two coupled "feet" that allow the interchange of the order of particles while the walker moves. In the underdamped case, the deterministic dynamics of the walker in a tilted asymmetric ratchet with an external periodic force is considered. It is found that delayed feedback ratchets with a switching-onand-off dependence of the states of the system can lead to absolute negative mobility. In such a novel phenomenon, the particles move against the bias. Moreover, the walker can acquire a series of resonant steps for different values of the current. It is interesting to find that the resonant currents of the walker are induced by the phase locked motion that corresponds to the synchronization of the motion with the change in the frequency of the external driving. These resonant steps can be well predicted in terms of time-space symmetry analysis, which is in good agreement with dynamics simulations. The transport performances can be optimized and controlled by suitably adjusting the parameters of the delayed-feedback ratchets.

Optimal Sensor Scheduling for Multiple Hypothesis Testing

DTIC Science & Technology

1981-09-01

Naval Research, under contract N00014-77-0532 is gratpfully acknowledged. 2 Laboratory for Information and Decision Systems , MIT Room 35-213, Cambridge...treat the more general problem [9,10]. However, two common threads connect these approaches: they obtain feedback laws mapping posterior destributions ...objective of a detection or identification algorithm is to produce correct estimates of the true state of a system . It is also bene- ficial if these

Issues in the digital implementation of control compensators. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Moroney, P.

1979-01-01

Techniques developed for the finite-precision implementation of digital filters were used, adapted, and extended for digital feedback compensators, with particular emphasis on steady state, linear-quadratic-Gaussian compensators. Topics covered include: (1) the linear-quadratic-Gaussian problem; (2) compensator structures; (3) architectural issues: serialism, parallelism, and pipelining; (4) finite wordlength effects: quantization noise, quantizing the coefficients, and limit cycles; and (5) the optimization of structures.

Tactile Sensory Supplementation of Gravitational References to Optimize Sensorimotor Recovery

NASA Technical Reports Server (NTRS)

Black, F. O.; Paloski, W. H.; Bloomberg, J. J.; Wood, S. J.

2007-01-01

Integration of multi-sensory inputs to detect tilts relative to gravity is critical for sensorimotor control of upright orientation. Displaying body orientation using electrotactile feedback to the tongue has been developed by Bach-y- Rita and colleagues as a sensory aid to maintain upright stance with impaired vestibular feedback. This investigation has explored the effects of Tongue Elecrotactile Feedback (TEF) for control of posture and movement as a sensorimotor countermeasure, specifically addressing the optimal location of movement sensors.

A generalised optimal linear quadratic tracker with universal applications. Part 2: discrete-time systems

NASA Astrophysics Data System (ADS)

Ebrahimzadeh, Faezeh; Tsai, Jason Sheng-Hong; Chung, Min-Ching; Liao, Ying Ting; Guo, Shu-Mei; Shieh, Leang-San; Wang, Li

2017-01-01

Contrastive to Part 1, Part 2 presents a generalised optimal linear quadratic digital tracker (LQDT) with universal applications for the discrete-time (DT) systems. This includes (1) a generalised optimal LQDT design for the system with the pre-specified trajectories of the output and the control input and additionally with both the input-to-output direct-feedthrough term and known/estimated system disturbances or extra input/output signals; (2) a new optimal filter-shaped proportional plus integral state-feedback LQDT design for non-square non-minimum phase DT systems to achieve a minimum-phase-like tracking performance; (3) a new approach for computing the control zeros of the given non-square DT systems; and (4) a one-learning-epoch input-constrained iterative learning LQDT design for the repetitive DT systems.

Driving many distant atoms into high-fidelity steady state entanglement via Lyapunov control.

PubMed

Li, Chuang; Song, Jie; Xia, Yan; Ding, Weiqiang

2018-01-22

Based on Lyapunov control theory in closed and open systems, we propose a scheme to generate W state of many distant atoms in the cavity-fiber-cavity system. In the closed system, the W state is generated successfully even when the coupling strength between the cavity and fiber is extremely weak. In the presence of atomic spontaneous emission or cavity and fiber decay, the photon-measurement and quantum feedback approaches are proposed to improve the fidelity, which enable efficient generation of high-fidelity W state in the case of large dissipation. Furthermore, the time-optimal Lyapunov control is investigated to shorten the evolution time and improve the fidelity in open systems.

Open-loop-feedback control of serum drug concentrations: pharmacokinetic approaches to drug therapy.

PubMed

Jelliffe, R W

1983-01-01

Recent developments to optimize open-loop-feedback control of drug dosage regimens, generally applicable to pharmacokinetically oriented therapy with many drugs, involve computation of patient-individualized strategies for obtaining desired serum drug concentrations. Analyses of past therapy are performed by least squares, extended least squares, and maximum a posteriori probability Bayesian methods of fitting pharmacokinetic models to serum level data. Future possibilities for truly optimal open-loop-feedback therapy with full Bayesian methods, and conceivably for optimal closed-loop therapy in such data-poor clinical situations, are also discussed. Implementation of these various therapeutic strategies, using automated, locally controlled infusion devices, has also been achieved in prototype form.

A Reduced Order Model of the Linearized Incompressible Navier-Strokes Equations for the Sensor/Actuator Placement Problem

NASA Technical Reports Server (NTRS)

Allan, Brian G.

2000-01-01

A reduced order modeling approach of the Navier-Stokes equations is presented for the design of a distributed optimal feedback kernel. This approach is based oil a Krylov subspace method where significant modes of the flow are captured in the model This model is then used in all optimal feedback control design where sensing and actuation is performed oil tile entire flow field. This control design approach yields all optimal feedback kernel which provides insight into the placement of sensors and actuators in the flow field. As all evaluation of this approach, a two-dimensional shear layer and driven cavity flow are investigated.

The waveguide laser - A review

NASA Technical Reports Server (NTRS)

Degnan, J. J.

1976-01-01

The present article reviews the fundamental physical principles essential to an understanding of waveguide gas and liquid lasers, and the current technological state of these devices. At the present time, waveguide laser transitions span the visible through submillimeter regions of the wavelength spectrum. The introduction discusses the many applications of waveguide lasers and the wide variety of laser configurations that are possible. Section 1 summarizes the properties of modes in hollow dielectric waveguides of circular, rectangular, and planar cross section. Section 2 considers various approaches to optical feedback including internal and external mirror Fabry-Perot type resonators, hollow waveguide distributed feedback structures, and ring-resonant configurations. Section 3 discusses those aspects of molecular kinetic and laser theory pertinent to the design and optimization of waveguide gas lasers.

Estimation of regions of attraction and ultimate boundedness for multiloop LQ regulators. [Linear Quadratic

NASA Technical Reports Server (NTRS)

Joshi, S. M.

1984-01-01

Closed-loop stability is investigated for multivariable linear time-invariant systems controlled by optimal full state feedback linear quadratic (LQ) regulators, with nonlinear gains present in the feedback channels. Estimates are obtained for the region of attraction when the nonlinearities escape the (0.5, infinity) sector in regions away from the origin and for the region of ultimate boundedness when the nonlinearities escape the sector near the origin. The expressions for these regions also provide methods for selecting the performance function parameters in order to obtain LQ designs with better tolerance for nonlinearities. The analytical results are illustrated by applying them to the problem of controlling the rigid-body pitch angle and elastic motion of a large, flexible space antenna.

An intermittent control model of flexible human gait using a stable manifold of saddle-type unstable limit cycle dynamics

PubMed Central

Fu, Chunjiang; Suzuki, Yasuyuki; Kiyono, Ken; Morasso, Pietro; Nomura, Taishin

2014-01-01

Stability of human gait is the ability to maintain upright posture during walking against external perturbations. It is a complex process determined by a number of cross-related factors, including gait trajectory, joint impedance and neural control strategies. Here, we consider a control strategy that can achieve stable steady-state periodic gait while maintaining joint flexibility with the lowest possible joint impedance. To this end, we carried out a simulation study of a heel-toe footed biped model with hip, knee and ankle joints and a heavy head-arms-trunk element, working in the sagittal plane. For simplicity, the model assumes a periodic desired joint angle trajectory and joint torques generated by a set of feed-forward and proportional-derivative feedback controllers, whereby the joint impedance is parametrized by the feedback gains. We could show that a desired steady-state gait accompanied by the desired joint angle trajectory can be established as a stable limit cycle (LC) for the feedback controller with an appropriate set of large feedback gains. Moreover, as the feedback gains are decreased for lowering the joint stiffness, stability of the LC is lost only in a few dimensions, while leaving the remaining large number of dimensions quite stable: this means that the LC becomes saddle-type, with a low-dimensional unstable manifold and a high-dimensional stable manifold. Remarkably, the unstable manifold remains of low dimensionality even when the feedback gains are decreased far below the instability point. We then developed an intermittent neural feedback controller that is activated only for short periods of time at an optimal phase of each gait stride. We characterized the robustness of this design by showing that it can better stabilize the unstable LC with small feedback gains, leading to a flexible gait, and in particular we demonstrated that such an intermittent controller performs better if it drives the state point to the stable manifold, rather than directly to the LC. The proposed intermittent control strategy might have a high affinity for the inverted pendulum analogy of biped gait, providing a dynamic view of how the step-to-step transition from one pendular stance to the next can be achieved stably in a robust manner by a well-timed neural intervention that exploits the stable modes embedded in the unstable dynamics. PMID:25339687

An intermittent control model of flexible human gait using a stable manifold of saddle-type unstable limit cycle dynamics.

PubMed

Fu, Chunjiang; Suzuki, Yasuyuki; Kiyono, Ken; Morasso, Pietro; Nomura, Taishin

2014-12-06

Stability of human gait is the ability to maintain upright posture during walking against external perturbations. It is a complex process determined by a number of cross-related factors, including gait trajectory, joint impedance and neural control strategies. Here, we consider a control strategy that can achieve stable steady-state periodic gait while maintaining joint flexibility with the lowest possible joint impedance. To this end, we carried out a simulation study of a heel-toe footed biped model with hip, knee and ankle joints and a heavy head-arms-trunk element, working in the sagittal plane. For simplicity, the model assumes a periodic desired joint angle trajectory and joint torques generated by a set of feed-forward and proportional-derivative feedback controllers, whereby the joint impedance is parametrized by the feedback gains. We could show that a desired steady-state gait accompanied by the desired joint angle trajectory can be established as a stable limit cycle (LC) for the feedback controller with an appropriate set of large feedback gains. Moreover, as the feedback gains are decreased for lowering the joint stiffness, stability of the LC is lost only in a few dimensions, while leaving the remaining large number of dimensions quite stable: this means that the LC becomes saddle-type, with a low-dimensional unstable manifold and a high-dimensional stable manifold. Remarkably, the unstable manifold remains of low dimensionality even when the feedback gains are decreased far below the instability point. We then developed an intermittent neural feedback controller that is activated only for short periods of time at an optimal phase of each gait stride. We characterized the robustness of this design by showing that it can better stabilize the unstable LC with small feedback gains, leading to a flexible gait, and in particular we demonstrated that such an intermittent controller performs better if it drives the state point to the stable manifold, rather than directly to the LC. The proposed intermittent control strategy might have a high affinity for the inverted pendulum analogy of biped gait, providing a dynamic view of how the step-to-step transition from one pendular stance to the next can be achieved stably in a robust manner by a well-timed neural intervention that exploits the stable modes embedded in the unstable dynamics.

An optimal output feedback gain variation scheme for the control of plants exhibiting gross parameter changes

NASA Technical Reports Server (NTRS)

Moerder, Daniel D.

1987-01-01

A concept for optimally designing output feedback controllers for plants whose dynamics exhibit gross changes over their operating regimes was developed. This was to formulate the design problem in such a way that the implemented feedback gains vary as the output of a dynamical system whose independent variable is a scalar parameterization of the plant operating point. The results of this effort include derivation of necessary conditions for optimality for the general problem formulation, and for several simplified cases. The question of existence of a solution to the design problem was also examined, and it was shown that the class of gain variation schemes developed are capable of achieving gain variation histories which are arbitrarily close to the unconstrained gain solution for each point in the plant operating range. The theory was implemented in a feedback design algorithm, which was exercised in a numerical example. The results are applicable to the design of practical high-performance feedback controllers for plants whose dynamics vary significanly during operation. Many aerospace systems fall into this category.

HOT Faults", Fault Organization, and the Occurrence of the Largest Earthquakes

NASA Astrophysics Data System (ADS)

Carlson, J. M.; Hillers, G.; Archuleta, R. J.

2006-12-01

We apply the concept of "Highly Optimized Tolerance" (HOT) for the investigation of spatio-temporal seismicity evolution, in particular mechanisms associated with largest earthquakes. HOT provides a framework for investigating both qualitative and quantitative features of complex feedback systems that are far from equilibrium and punctuated by rare, catastrophic events. In HOT, robustness trade-offs lead to complexity and power laws in systems that are coupled to evolving environments. HOT was originally inspired by biology and engineering, where systems are internally very highly structured, through biological evolution or deliberate design, and perform in an optimum manner despite fluctuations in their surroundings. Though faults and fault systems are not designed in ways comparable to biological and engineered structures, feedback processes are responsible in a conceptually comparable way for the development, evolution and maintenance of younger fault structures and primary slip surfaces of mature faults, respectively. Hence, in geophysical applications the "optimization" approach is perhaps more aptly replaced by "organization", reflecting the distinction between HOT and random, disorganized configurations, and highlighting the importance of structured interdependencies that evolve via feedback among and between different spatial and temporal scales. Expressed in the terminology of the HOT concept, mature faults represent a configuration optimally organized for the release of strain energy; whereas immature, more heterogeneous fault networks represent intermittent, suboptimal systems that are regularized towards structural simplicity and the ability to generate large earthquakes more easily. We discuss fault structure and associated seismic response pattern within the HOT concept, and outline fundamental differences between this novel interpretation to more orthodox viewpoints like the criticality concept. The discussion is flanked by numerical simulations of a 2D fault model, where we investigate different feedback mechanisms and their effect on seismicity evolution. We introduce an approach to estimate the state of a fault and thus its capability of generating a large (system-wide) event assuming likely heterogeneous distributions of hypocenters and stresses, respectively.

Dynamical Motor Control Learned with Deep Deterministic Policy Gradient

PubMed Central

2018-01-01

Conventional models of motor control exploit the spatial representation of the controlled system to generate control commands. Typically, the control command is gained with the feedback state of a specific instant in time, which behaves like an optimal regulator or spatial filter to the feedback state. Yet, recent neuroscience studies found that the motor network may constitute an autonomous dynamical system and the temporal patterns of the control command can be contained in the dynamics of the motor network, that is, the dynamical system hypothesis (DSH). Inspired by these findings, here we propose a computational model that incorporates this neural mechanism, in which the control command could be unfolded from a dynamical controller whose initial state is specified with the task parameters. The model is trained in a trial-and-error manner in the framework of deep deterministic policy gradient (DDPG). The experimental results show that the dynamical controller successfully learns the control policy for arm reaching movements, while the analysis of the internal activities of the dynamical controller provides the computational evidence to the DSH of the neural coding in motor cortices. PMID:29666634

Dynamical Motor Control Learned with Deep Deterministic Policy Gradient.

PubMed

Shi, Haibo; Sun, Yaoru; Li, Jie

2018-01-01

Conventional models of motor control exploit the spatial representation of the controlled system to generate control commands. Typically, the control command is gained with the feedback state of a specific instant in time, which behaves like an optimal regulator or spatial filter to the feedback state. Yet, recent neuroscience studies found that the motor network may constitute an autonomous dynamical system and the temporal patterns of the control command can be contained in the dynamics of the motor network, that is, the dynamical system hypothesis (DSH). Inspired by these findings, here we propose a computational model that incorporates this neural mechanism, in which the control command could be unfolded from a dynamical controller whose initial state is specified with the task parameters. The model is trained in a trial-and-error manner in the framework of deep deterministic policy gradient (DDPG). The experimental results show that the dynamical controller successfully learns the control policy for arm reaching movements, while the analysis of the internal activities of the dynamical controller provides the computational evidence to the DSH of the neural coding in motor cortices.

An inverse dynamics approach to trajectory optimization and guidance for an aerospace plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1992-01-01

The optimal ascent problem for an aerospace planes is formulated as an optimal inverse dynamic problem. Both minimum-fuel and minimax type of performance indices are considered. Some important features of the optimal trajectory and controls are used to construct a nonlinear feedback midcourse controller, which not only greatly simplifies the difficult constrained optimization problem and yields improved solutions, but is also suited for onboard implementation. Robust ascent guidance is obtained by using combination of feedback compensation and onboard generation of control through the inverse dynamics approach. Accurate orbital insertion can be achieved with near-optimal control of the rocket through inverse dynamics even in the presence of disturbances.

Effects of different feedback types on information integration in repeated monetary gambles

PubMed Central

Haffke, Peter; Hübner, Ronald

2015-01-01

Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback. PMID:25667576

Effects of different feedback types on information integration in repeated monetary gambles.

PubMed

Haffke, Peter; Hübner, Ronald

2014-01-01

Most models of risky decision making assume that all relevant information is taken into account (e.g., von Neumann and Morgenstern, 1944; Kahneman and Tversky, 1979). However, there are also some models supposing that only part of the information is considered (e.g., Brandstätter et al., 2006; Gigerenzer and Gaissmaier, 2011). To further investigate the amount of information that is usually used for decision making, and how the use depends on feedback, we conducted a series of three experiments in which participants choose between two lotteries and where no feedback, outcome feedback, and error feedback was provided, respectively. The results show that without feedback participants mostly chose the lottery with the higher winning probability, and largely ignored the potential gains. The same results occurred when the outcome of each decision was fed back. Only after presenting error feedback (i.e., signaling whether a choice was optimal or not), participants considered probabilities as well as gains, resulting in more optimal choices. We propose that outcome feedback was ineffective, because of its probabilistic and ambiguous nature. Participants improve information integration only if provided with a consistent and deterministic signal such as error feedback.

The optimal location of piezoelectric actuators and sensors for vibration control of plates

NASA Astrophysics Data System (ADS)

Kumar, K. Ramesh; Narayanan, S.

2007-12-01

This paper considers the optimal placement of collocated piezoelectric actuator-sensor pairs on a thin plate using a model-based linear quadratic regulator (LQR) controller. LQR performance is taken as objective for finding the optimal location of sensor-actuator pairs. The problem is formulated using the finite element method (FEM) as multi-input-multi-output (MIMO) model control. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero-one optimization problem. A genetic algorithm (GA) is used to solve the zero-one optimization problem. Different classical control strategies like direct proportional feedback, constant-gain negative velocity feedback and the LQR optimal control scheme are applied to study the control effectiveness.

Teaching Large Groups the Tennis Serve: Optimizing Practice Opportunities and Providing Individual Feedback

ERIC Educational Resources Information Center

Hume, Donald

2018-01-01

This article describes a progressive methodology for teaching the tennis serve to large groups with a focus on optimizing practice opportunities and providing individual feedback to players. Specifically, it delineates teaching the serve to 24 players on two courts. The methodology can be adapted for more players and/or more courts as appropriate,…

Feedback Functions, Optimization, and the Relation of Response Rate to Reinforcer Rate

ERIC Educational Resources Information Center

Soto, Paul L.; McDowell, Jack J.; Dallery, Jesse

2006-01-01

The present experiment arranged a series of inverted U-shaped feedback functions relating reinforcer rate to response rate to test whether responding was consistent with an optimization account or with a one-to-one relation of response rate to reinforcer rate such as linear system theory's rate equation or Herrnstein's hyperbola. Reinforcer rate…

A coherent Ising machine for 2000-node optimization problems

NASA Astrophysics Data System (ADS)

Inagaki, Takahiro; Haribara, Yoshitaka; Igarashi, Koji; Sonobe, Tomohiro; Tamate, Shuhei; Honjo, Toshimori; Marandi, Alireza; McMahon, Peter L.; Umeki, Takeshi; Enbutsu, Koji; Tadanaga, Osamu; Takenouchi, Hirokazu; Aihara, Kazuyuki; Kawarabayashi, Ken-ichi; Inoue, Kyo; Utsunomiya, Shoko; Takesue, Hiroki

2016-11-01

The analysis and optimization of complex systems can be reduced to mathematical problems collectively known as combinatorial optimization. Many such problems can be mapped onto ground-state search problems of the Ising model, and various artificial spin systems are now emerging as promising approaches. However, physical Ising machines have suffered from limited numbers of spin-spin couplings because of implementations based on localized spins, resulting in severe scalability problems. We report a 2000-spin network with all-to-all spin-spin couplings. Using a measurement and feedback scheme, we coupled time-multiplexed degenerate optical parametric oscillators to implement maximum cut problems on arbitrary graph topologies with up to 2000 nodes. Our coherent Ising machine outperformed simulated annealing in terms of accuracy and computation time for a 2000-node complete graph.

Neural network-based optimal adaptive output feedback control of a helicopter UAV.

PubMed

Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

2013-07-01

Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

A m-ary linear feedback shift register with binary logic

NASA Technical Reports Server (NTRS)

Perlman, M. (Inventor)

1973-01-01

A family of m-ary linear feedback shift registers with binary logic is disclosed. Each m-ary linear feedback shift register with binary logic generates a binary representation of a nonbinary recurring sequence, producible with a m-ary linear feedback shift register without binary logic in which m is greater than 2. The state table of a m-ary linear feedback shift register without binary logic, utilizing sum modulo m feedback, is first tubulated for a given initial state. The entries in the state table are coded in binary and the binary entries are used to set the initial states of the stages of a plurality of binary shift registers. A single feedback logic unit is employed which provides a separate feedback binary digit to each binary register as a function of the states of corresponding stages of the binary registers.

Reserve selection with land market feedbacks.

PubMed

Butsic, Van; Lewis, David J; Radeloff, Volker C

2013-01-15

How to best site reserves is a leading question for conservation biologists. Recently, reserve selection has emphasized efficient conservation: maximizing conservation goals given the reality of limited conservation budgets, and this work indicates that land market can potentially undermine the conservation benefits of reserves by increasing property values and development probabilities near reserves. Here we propose a reserve selection methodology which optimizes conservation given both a budget constraint and land market feedbacks by using a combination of econometric models along with stochastic dynamic programming. We show that amenity based feedbacks can be accounted for in optimal reserve selection by choosing property price and land development models which exogenously estimate the effects of reserve establishment. In our empirical example, we use previously estimated models of land development and property prices to select parcels to maximize coarse woody debris along 16 lakes in Vilas County, WI, USA. Using each lake as an independent experiment, we find that including land market feedbacks in the reserve selection algorithm has only small effects on conservation efficacy. Likewise, we find that in our setting heuristic (minloss and maxgain) algorithms perform nearly as well as the optimal selection strategy. We emphasize that land market feedbacks can be included in optimal reserve selection; the extent to which this improves reserve placement will likely vary across landscapes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Investigation and appreciation of optimal output feedback. Volume 1: A convergent algorithm for the stochastic infinite-time discrete optimal output feedback problem

NASA Technical Reports Server (NTRS)

Halyo, N.; Broussard, J. R.

1984-01-01

The stochastic, infinite time, discrete output feedback problem for time invariant linear systems is examined. Two sets of sufficient conditions for the existence of a stable, globally optimal solution are presented. An expression for the total change in the cost function due to a change in the feedback gain is obtained. This expression is used to show that a sequence of gains can be obtained by an algorithm, so that the corresponding cost sequence is monotonically decreasing and the corresponding sequence of the cost gradient converges to zero. The algorithm is guaranteed to obtain a critical point of the cost function. The computational steps necessary to implement the algorithm on a computer are presented. The results are applied to a digital outer loop flight control problem. The numerical results for this 13th order problem indicate a rate of convergence considerably faster than two other algorithms used for comparison.

Collective irrationality and positive feedback.

PubMed

Nicolis, Stamatios C; Zabzina, Natalia; Latty, Tanya; Sumpter, David J T

2011-04-26

Recent experiments on ants and slime moulds have assessed the degree to which they make rational decisions when presented with a number of alternative food sources or shelter. Ants and slime moulds are just two examples of a wide range of species and biological processes that use positive feedback mechanisms to reach decisions. Here we use a generic, experimentally validated model of positive feedback between group members to show that the probability of taking the best of options depends crucially on the strength of feedback. We show how the probability of choosing the best option can be maximized by applying an optimal feedback strength. Importantly, this optimal value depends on the number of options, so that when we change the number of options the preference of the group changes, producing apparent "irrationalities". We thus reinterpret the idea that collectives show "rational" or "irrational" preferences as being a necessary consequence of the use of positive feedback. We argue that positive feedback is a heuristic which often produces fast and accurate group decision-making, but is always susceptible to apparent irrationality when studied under particular experimental conditions.

Dynamical modelling of haematopoiesis: an integrated view over the system in homeostasis and under perturbation.

PubMed

Manesso, Erica; Teles, José; Bryder, David; Peterson, Carsten

2013-03-06

A very high number of different types of blood cells must be generated daily through a process called haematopoiesis in order to meet the physiological requirements of the organism. All blood cells originate from a population of relatively few haematopoietic stem cells residing in the bone marrow, which give rise to specific progenitors through different lineages. Steady-state dynamics are governed by cell division and commitment rates as well as by population sizes, while feedback components guarantee the restoration of steady-state conditions. In this study, all parameters governing these processes were estimated in a computational model to describe the haematopoietic hierarchy in adult mice. The model consisted of ordinary differential equations and included negative feedback regulation. A combination of literature data, a novel divide et impera approach for steady-state calculations and stochastic optimization allowed one to reduce possible configurations of the system. The model was able to recapitulate the fundamental steady-state features of haematopoiesis and simulate the re-establishment of steady-state conditions after haemorrhage and bone marrow transplantation. This computational approach to the haematopoietic system is novel and provides insight into the dynamics and the nature of possible solutions, with potential applications in both fundamental and clinical research.

Closed-form recursive formula for an optimal tracker with terminal constraints

NASA Technical Reports Server (NTRS)

Juang, J.-N.; Turner, J. D.; Chun, H. M.

1984-01-01

Feedback control laws are derived for a class of optimal finite time tracking problems with terminal constraints. Analytical solutions are obtained for the feedback gain and the closed-loop response trajectory. Such formulations are expressed in recursive forms so that a real-time computer implementation becomes feasible. Two examples are given to illustrate the validity and usefulness of the formulations.

Understanding the role of ecohydrological feedbacks in ecosystem state change in drylands

USGS Publications Warehouse

Turnbull, L.; Wilcox, B.P.; Belnap, J.; Ravi, S.; D'Odorico, P.; Childers, D.; Gwenzi, W.; Okin, G.; Wainwright, J.; Caylor, K.K.; Sankey, T.

2012-01-01

Ecohydrological feedbacks are likely to be critical for understanding the mechanisms by which changes in exogenous forces result in ecosystem state change. We propose that in drylands, the dynamics of ecosystem state change are determined by changes in the type (stabilizing vs amplifying) and strength of ecohydrological feedbacks following a change in exogenous forces. Using a selection of five case studies from drylands, we explore the characteristics of ecohydrological feedbacks and resulting dynamics of ecosystem state change. We surmise that stabilizing feedbacks are critical for the provision of plant-essential resources in drylands. Exogenous forces that break these stabilizing feedbacks can alter the state of the system, although such changes are potentially reversible if strong amplifying ecohydrological feedbacks do not develop. The case studies indicate that if amplifying ecohydrological feedbacks do develop, they are typically associated with abiotic processes such as runoff, erosion (by wind and water), and fire. These amplifying ecohydrological feedbacks progressively modify the system in ways that are long-lasting and possibly irreversible on human timescales.

Circuit mechanisms of sensorimotor learning

PubMed Central

Makino, Hiroshi; Hwang, Eun Jung; Hedrick, Nathan G.; Komiyama, Takaki

2016-01-01

SUMMARY The relationship between the brain and the environment is flexible, forming the foundation for our ability to learn. Here we review the current state of our understanding of the modifications in the sensorimotor pathway related to sensorimotor learning. We divide the process in three hierarchical levels with distinct goals: 1) sensory perceptual learning, 2) sensorimotor associative learning, and 3) motor skill learning. Perceptual learning optimizes the representations of important sensory stimuli. Associative learning and the initial phase of motor skill learning are ensured by feedback-based mechanisms that permit trial-and-error learning. The later phase of motor skill learning may primarily involve feedback-independent mechanisms operating under the classic Hebbian rule. With these changes under distinct constraints and mechanisms, sensorimotor learning establishes dedicated circuitry for the reproduction of stereotyped neural activity patterns and behavior. PMID:27883902

Application of IFT and SPSA to servo system control.

PubMed

Rădac, Mircea-Bogdan; Precup, Radu-Emil; Petriu, Emil M; Preitl, Stefan

2011-12-01

This paper treats the application of two data-based model-free gradient-based stochastic optimization techniques, i.e., iterative feedback tuning (IFT) and simultaneous perturbation stochastic approximation (SPSA), to servo system control. The representative case of controlled processes modeled by second-order systems with an integral component is discussed. New IFT and SPSA algorithms are suggested to tune the parameters of the state feedback controllers with an integrator in the linear-quadratic-Gaussian (LQG) problem formulation. An implementation case study concerning the LQG-based design of an angular position controller for a direct current servo system laboratory equipment is included to highlight the pros and cons of IFT and SPSA from an application's point of view. The comparison of IFT and SPSA algorithms is focused on an insight into their implementation.

MATHEMATICAL ANALYSIS OF STEADY-STATE SOLUTIONS IN COMPARTMENT AND CONTINUUM MODELS OF CELL POLARIZATION

PubMed Central

ZHENG, ZHENZHEN; CHOU, CHING-SHAN; YI, TAU-MU; NIE, QING

2013-01-01

Cell polarization, in which substances previously uniformly distributed become asymmetric due to external or/and internal stimulation, is a fundamental process underlying cell mobility, cell division, and other polarized functions. The yeast cell S. cerevisiae has been a model system to study cell polarization. During mating, yeast cells sense shallow external spatial gradients and respond by creating steeper internal gradients of protein aligned with the external cue. The complex spatial dynamics during yeast mating polarization consists of positive feedback, degradation, global negative feedback control, and cooperative effects in protein synthesis. Understanding such complex regulations and interactions is critical to studying many important characteristics in cell polarization including signal amplification, tracking dynamic signals, and potential trade-off between achieving both objectives in a robust fashion. In this paper, we study some of these questions by analyzing several models with different spatial complexity: two compartments, three compartments, and continuum in space. The step-wise approach allows detailed characterization of properties of the steady state of the system, providing more insights for biological regulations during cell polarization. For cases without membrane diffusion, our study reveals that increasing the number of spatial compartments results in an increase in the number of steady-state solutions, in particular, the number of stable steady-state solutions, with the continuum models possessing infinitely many steady-state solutions. Through both analysis and simulations, we find that stronger positive feedback, reduced diffusion, and a shallower ligand gradient all result in more steady-state solutions, although most of these are not optimally aligned with the gradient. We explore in the different settings the relationship between the number of steady-state solutions and the extent and accuracy of the polarization. Taken together these results furnish a detailed description of the factors that influence the tradeoff between a single correctly aligned but poorly polarized stable steady-state solution versus multiple more highly polarized stable steady-state solutions that may be incorrectly aligned with the external gradient. PMID:21936604

Integrator Windup Protection-Techniques and a STOVL Aircraft Engine Controller Application

NASA Technical Reports Server (NTRS)

KrishnaKumar, K.; Narayanaswamy, S.

1997-01-01

Integrators are included in the feedback loop of a control system to eliminate the steady state errors in the commanded variables. The integrator windup problem arises if the control actuators encounter operational limits before the steady state errors are driven to zero by the integrator. The typical effects of windup are large system oscillations, high steady state error, and a delayed system response following the windup. In this study, methods to prevent the integrator windup are examined to provide Integrator Windup Protection (IW) for an engine controller of a Short Take-Off and Vertical Landing (STOVL) aircraft. An unified performance index is defined to optimize the performance of the Conventional Anti-Windup (CAW) and the Modified Anti-Windup (MAW) methods. A modified Genetic Algorithm search procedure with stochastic parameter encoding is implemented to obtain the optimal parameters of the CAW scheme. The advantages and drawbacks of the CAW and MAW techniques are discussed and recommendations are made for the choice of the IWP scheme, given some characteristics of the system.

Study of dynamics of X-14B VTOL aircraft

NASA Technical Reports Server (NTRS)

Loscutoff, W. V.; Mitchiner, J. L.; Roesener, R. A.; Seevers, J. A.

1973-01-01

Research was initiated to investigate certain facets of modern control theory and their integration with a digital computer to provide a tractable flight control system for a VTOL aircraft. Since the hover mode is the most demanding phase in the operation of a VTOL aircraft, the research efforts were concentrated in this mode of aircraft operation. Research work on three different aspects of the operation of the X-14B VTOL aircraft is discussed. A general theory for optimal, prespecified, closed-loop control is developed. The ultimate goal was optimal decoupling of the modes of the VTOL aircraft to simplify the pilot's task of handling the aircraft. Modern control theory is used to design deterministic state estimators which provide state variables not measured directly, but which are needed for state variable feedback control. The effect of atmospheric turbulence on the X-14B is investigated. A maximum magnitude gust envelope within which the aircraft could operate stably with the available control power is determined.

Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Li, Xiaohui; Sun, Zhenping; Cao, Dongpu; Liu, Daxue; He, Hangen

2017-03-01

This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ILTPTC framework, an efficient state-space sampling-based trajectory planning scheme is employed to smoothly follow the reference path. A model-based predictive path generation algorithm is applied to produce a set of smooth and kinematically-feasible paths connecting the initial state with the sampling terminal states. A velocity control law is then designed to assign a speed value at each of the points along the generated paths. An objective function considering both safety and comfort performance is carefully formulated for assessing the generated trajectories and selecting the optimal one. For accurately tracking the optimal trajectory while overcoming external disturbances and model uncertainties, a combined feedforward and feedback controller is developed. Both simulation analyses and vehicle testing are performed to verify the effectiveness of the proposed ILTPTC framework, and future research is also briefly discussed.

Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form.

PubMed

Jagannathan, Sarangapani; He, Pingan

2008-12-01

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights in order to attain the near-optimal control action. Both the NN control methods present a well-defined controller design and the noncausal problem in discrete-time backstepping design is avoided via NN approximation. A comparison between the controller methodologies is highlighted. The stability analysis of the closed-loop control schemes is demonstrated. The NN controller schemes do not require an offline learning phase and the NN weights can be initialized at zero or random. Results show that the performance of the proposed controller schemes is highly satisfactory while meeting the closed-loop stability.

Time-delayed feedback technique for suppressing instabilities in time-periodic flow

NASA Astrophysics Data System (ADS)

Shaabani-Ardali, Léopold; Sipp, Denis; Lesshafft, Lutz

2017-11-01

A numerical method is presented that allows to compute time-periodic flow states, even in the presence of hydrodynamic instabilities. The method is based on filtering nonharmonic components by way of delayed feedback control, as introduced by Pyragas [Phys. Lett. A 170, 421 (1992), 10.1016/0375-9601(92)90745-8]. Its use in flow problems is demonstrated here for the case of a periodically forced laminar jet, subject to a subharmonic instability that gives rise to vortex pairing. The optimal choice of the filter gain, which is a free parameter in the stabilization procedure, is investigated in the context of a low-dimensional model problem, and it is shown that this model predicts well the filter performance in the high-dimensional flow system. Vortex pairing in the jet is efficiently suppressed, so that the unstable periodic flow state in response to harmonic forcing is accurately retrieved. The procedure is straightforward to implement inside any standard flow solver. Memory requirements for the delayed feedback control can be significantly reduced by means of time interpolation between checkpoints. Finally, the method is extended for the treatment of periodic problems where the frequency is not known a priori. This procedure is demonstrated for a three-dimensional cubic lid-driven cavity in supercritical conditions.

The role of feedback contingency in perceptual category learning.

PubMed

Ashby, F Gregory; Vucovich, Lauren E

2016-11-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from 2 or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all 4 conditions, and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects, as well as their theoretical implications, are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Role of Feedback Contingency in Perceptual Category Learning

PubMed Central

Ashby, F. Gregory; Vucovich, Lauren E.

2016-01-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from two or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all four conditions and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects are discussed, as well as their theoretical implications. PMID:27149393

A neural-network-based exponential H∞ synchronisation for chaotic secure communication via improved genetic algorithm

NASA Astrophysics Data System (ADS)

Hsiao, Feng-Hsiag

2016-10-01

In this study, a novel approach via improved genetic algorithm (IGA)-based fuzzy observer is proposed to realise exponential optimal H∞ synchronisation and secure communication in multiple time-delay chaotic (MTDC) systems. First, an original message is inserted into the MTDC system. Then, a neural-network (NN) model is employed to approximate the MTDC system. Next, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion derived in terms of Lyapunov's direct method, thus ensuring that the trajectories of the slave system approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to GA's random global optimisation search capabilities, the lower and upper bounds of the search space can be set so that the GA will seek better fuzzy observer feedback gains, accelerating feedback gain-based synchronisation via the LMI-based approach. IGA, which exhibits better performance than traditional GA, is used to synthesise a fuzzy observer to not only realise the exponential synchronisation, but also achieve optimal H∞ performance by minimizing the disturbance attenuation level and recovering the transmitted message. Finally, a numerical example with simulations is given in order to demonstrate the effectiveness of our approach.

When more is less: Feedback effects in perceptual category learning ☆

PubMed Central

Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent

2008-01-01

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed. PMID:18455155

Effect of biased feedback on motor imagery learning in BCI-teleoperation system.

PubMed

Alimardani, Maryam; Nishio, Shuichi; Ishiguro, Hiroshi

2014-01-01

Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users' BCI performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects' performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects' BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects' online performance, evaluation of brain activity patterns revealed that subjects' self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects' motor imagery skills.

Static inverter with synchronous output waveform synthesized by time-optimal-response feedback

NASA Technical Reports Server (NTRS)

Kernick, A.; Stechschulte, D. L.; Shireman, D. W.

1976-01-01

Time-optimal-response 'bang-bang' or 'bang-hang' technique, using four feedback control loops, synthesizes static-inverter sinusoidal output waveform by self-oscillatory but yet synchronous pulse-frequency-modulation (SPFM). A single modular power stage per phase of ac output entails the minimum of circuit complexity while providing by feedback synthesis individual phase voltage regulation, phase position control and inherent compensation simultaneously for line and load disturbances. Clipped sinewave performance is described under off-limit load or input voltage conditions. Also, approaches to high power levels, 3-phase arraying and parallel modular connection are given.

Optimization of the Laser Properties of Polymer Films Doped with N,N´-Bis(3-methylphenyl)-N,N´-diphenylbenzidine

PubMed Central

Calzado, Eva M.; Boj, Pedro G.; Díaz-García, María A.

2009-01-01

This review compiles the work performed in the field of organic solid-state lasers with the hole-transporting organic molecule N,N´-bis(3-methylphenyl)-N,N´-diphenyl-benzidine system (TPD), in view of improving active laser material properties. The optimization of the amplified spontaneous emission characteristics, i.e., threshold, linewidth, emission wavelength and photostability, of polystyrene films doped with TPD in waveguide configuration has been achieved by investigating the influence of several materials parameters such as film thickness and TPD concentration. In addition, the influence in the emission properties of the inclusion of a second-order distributed feedback grating in the substrate is discussed.

A robust hybrid fuzzy-simulated annealing-intelligent water drops approach for tuning a distribution static compensator nonlinear controller in a distribution system

NASA Astrophysics Data System (ADS)

Bagheri Tolabi, Hajar; Hosseini, Rahil; Shakarami, Mahmoud Reza

2016-06-01

This article presents a novel hybrid optimization approach for a nonlinear controller of a distribution static compensator (DSTATCOM). The DSTATCOM is connected to a distribution system with the distributed generation units. The nonlinear control is based on partial feedback linearization. Two proportional-integral-derivative (PID) controllers regulate the voltage and track the output in this control system. In the conventional scheme, the trial-and-error method is used to determine the PID controller coefficients. This article uses a combination of a fuzzy system, simulated annealing (SA) and intelligent water drops (IWD) algorithms to optimize the parameters of the controllers. The obtained results reveal that the response of the optimized controlled system is effectively improved by finding a high-quality solution. The results confirm that using the tuning method based on the fuzzy-SA-IWD can significantly decrease the settling and rising times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM. The proposed hybrid tuning method for the partial feedback linearizing (PFL) controller achieved better regulation of the direct current voltage for the capacitor within the DSTATCOM. Furthermore, in the event of a fault the proposed controller tuned by the fuzzy-SA-IWD method showed better performance than the conventional controller or the PFL controller without optimization by the fuzzy-SA-IWD method with regard to both fault duration and clearing times.

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

NASA Technical Reports Server (NTRS)

Blackmore, Lars

2008-01-01

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

Effects of Feedback Timing and Type on Learning ESL Grammar Rules

ERIC Educational Resources Information Center

Lavolette, Elizabeth H. P.

2014-01-01

The optimal timing of feedback on formative assessments is an open question, with the cognitive processing window theory (Doughty, 2001) underlying the interaction approach suggesting that immediate feedback may be most beneficial for language acquisition (e.g., Gass, 2010; Polio, 2012) and two educational psychology hypotheses conversely…

Active Nonlinear Feedback Control for Aerospace Systems. Processor

DTIC Science & Technology

1990-12-01

relating to the role of nonlinearities in feedback control. These area include Lyapunov function theory, chaotic controllers, statistical energy analysis , phase robustness, and optimal nonlinear control theory.

Optimal structure of metaplasticity for adaptive learning

PubMed Central

2017-01-01

Learning from reward feedback in a changing environment requires a high degree of adaptability, yet the precise estimation of reward information demands slow updates. In the framework of estimating reward probability, here we investigated how this tradeoff between adaptability and precision can be mitigated via metaplasticity, i.e. synaptic changes that do not always alter synaptic efficacy. Using the mean-field and Monte Carlo simulations we identified ‘superior’ metaplastic models that can substantially overcome the adaptability-precision tradeoff. These models can achieve both adaptability and precision by forming two separate sets of meta-states: reservoirs and buffers. Synapses in reservoir meta-states do not change their efficacy upon reward feedback, whereas those in buffer meta-states can change their efficacy. Rapid changes in efficacy are limited to synapses occupying buffers, creating a bottleneck that reduces noise without significantly decreasing adaptability. In contrast, more-populated reservoirs can generate a strong signal without manifesting any observable plasticity. By comparing the behavior of our model and a few competing models during a dynamic probability estimation task, we found that superior metaplastic models perform close to optimally for a wider range of model parameters. Finally, we found that metaplastic models are robust to changes in model parameters and that metaplastic transitions are crucial for adaptive learning since replacing them with graded plastic transitions (transitions that change synaptic efficacy) reduces the ability to overcome the adaptability-precision tradeoff. Overall, our results suggest that ubiquitous unreliability of synaptic changes evinces metaplasticity that can provide a robust mechanism for mitigating the tradeoff between adaptability and precision and thus adaptive learning. PMID:28658247

Architecture and settings optimization procedure of a TES frequency domain multiplexed readout firmware

NASA Astrophysics Data System (ADS)

Clenet, A.; Ravera, L.; Bertrand, B.; den Hartog, R.; Jackson, B.; van Leeuwen, B.-J.; van Loon, D.; Parot, Y.; Pointecouteau, E.; Sournac, A.

2014-11-01

IRAP is developing the readout electronics of the SPICA-SAFARI's TES bolometer arrays. Based on the frequency domain multiplexing technique the readout electronics provides the AC-signals to voltage-bias the detectors; it demodulates the data; and it computes a feedback to linearize the detection chain. The feedback is computed with a specific technique, so called baseband feedback (BBFB) which ensures that the loop is stable even with long propagation and processing delays (i.e. several μ s) and with fast signals (i.e. frequency carriers of the order of 5 MHz). To optimize the power consumption we took advantage of the reduced science signal bandwidth to decouple the signal sampling frequency and the data processing rate. This technique allowed a reduction of the power consumption of the circuit by a factor of 10. Beyond the firmware architecture the optimization of the instrument concerns the characterization routines and the definition of the optimal parameters. Indeed, to operate an array TES one has to properly define about 21000 parameters. We defined a set of procedures to automatically characterize these parameters and find out the optimal settings.

Neural dynamic optimization for control systems. I. Background.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Neural dynamic optimization for control systems.III. Applications.

PubMed

Seong, C Y; Widrow, B

2001-01-01

For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively.

Neural dynamic optimization for control systems.II. Theory.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

NASA Astrophysics Data System (ADS)

Tiwari, Shivendra N.; Padhi, Radhakant

2018-01-01

Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method.

PubMed

Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong

2011-12-01

In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.

Optimal feedback strategies for pursuit-evasion and interception in a plane

NASA Technical Reports Server (NTRS)

Rajan, N.; Ardema, M. D.

1983-01-01

Variable-speed pursuit-evasion and interception for two aircraft moving in a horizontal plane are analyzed in terms of a coordinate frame fixed in the plane at termination. Each participant's optimal motion can be represented by extremal trajectory maps. These maps are used to discuss sub-optimal approximations that are independent of the other participant. A method of constructing sections of the barrier, dispersal, and control-level surfaces and thus determining feedback strategies is described. Some examples are shown for pursuit-evasion and the minimum-time interception of a straight-flying target.

Strong Converse Exponents for a Quantum Channel Discrimination Problem and Quantum-Feedback-Assisted Communication

NASA Astrophysics Data System (ADS)

Cooney, Tom; Mosonyi, Milán; Wilde, Mark M.

2016-06-01

This paper studies the difficulty of discriminating between an arbitrary quantum channel and a "replacer" channel that discards its input and replaces it with a fixed state. The results obtained here generalize those known in the theory of quantum hypothesis testing for binary state discrimination. We show that, in this particular setting, the most general adaptive discrimination strategies provide no asymptotic advantage over non-adaptive tensor-power strategies. This conclusion follows by proving a quantum Stein's lemma for this channel discrimination setting, showing that a constant bound on the Type I error leads to the Type II error decreasing to zero exponentially quickly at a rate determined by the maximum relative entropy registered between the channels. The strong converse part of the lemma states that any attempt to make the Type II error decay to zero at a rate faster than the channel relative entropy implies that the Type I error necessarily converges to one. We then refine this latter result by identifying the optimal strong converse exponent for this task. As a consequence of these results, we can establish a strong converse theorem for the quantum-feedback-assisted capacity of a channel, sharpening a result due to Bowen. Furthermore, our channel discrimination result demonstrates the asymptotic optimality of a non-adaptive tensor-power strategy in the setting of quantum illumination, as was used in prior work on the topic. The sandwiched Rényi relative entropy is a key tool in our analysis. Finally, by combining our results with recent results of Hayashi and Tomamichel, we find a novel operational interpretation of the mutual information of a quantum channel {mathcal{N}} as the optimal Type II error exponent when discriminating between a large number of independent instances of {mathcal{N}} and an arbitrary "worst-case" replacer channel chosen from the set of all replacer channels.

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Optimization of Sensing and Feedback Control for Vibration/Flutter of Rotating Disk by PZT Actuators via Air Coupled Pressure

PubMed Central

Yan, Tianhong; Xu, Xinsheng; Han, Jianqiang; Lin, Rongming; Ju, Bingfeng; Li, Qing

2011-01-01

In this paper, a feedback control mechanism and its optimization for rotating disk vibration/flutter via changes of air-coupled pressure generated using piezoelectric patch actuators are studied. A thin disk rotates in an enclosure, which is equipped with a feedback control loop consisting of a micro-sensor, a signal processor, a power amplifier, and several piezoelectric (PZT) actuator patches distributed on the cover of the enclosure. The actuator patches are mounted on the inner or the outer surfaces of the enclosure to produce necessary control force required through the airflow around the disk. The control mechanism for rotating disk flutter using enclosure surfaces bonded with sensors and piezoelectric actuators is thoroughly studied through analytical simulations. The sensor output is used to determine the amount of input to the actuator for controlling the response of the disk in a closed loop configuration. The dynamic stability of the disk-enclosure system, together with the feedback control loop, is analyzed as a complex eigenvalue problem, which is solved using Galerkin’s discretization procedure. The results show that the disk flutter can be reduced effectively with proper configurations of the control gain and the phase shift through the actuations of PZT patches. The effectiveness of different feedback control methods in altering system characteristics and system response has been investigated. The control capability, in terms of control gain, phase shift, and especially the physical configuration of actuator patches, are also evaluated by calculating the complex eigenvalues and the maximum displacement produced by the actuators. To achieve a optimal control performance, sizes, positions and shapes of PZT patches used need to be optimized and such optimization has been achieved through numerical simulations. PMID:22163788

Optimization of sensing and feedback control for vibration/flutter of rotating disk by PZT actuators via air coupled pressure.

PubMed

Yan, Tianhong; Xu, Xinsheng; Han, Jianqiang; Lin, Rongming; Ju, Bingfeng; Li, Qing

2011-01-01

In this paper, a feedback control mechanism and its optimization for rotating disk vibration/flutter via changes of air-coupled pressure generated using piezoelectric patch actuators are studied. A thin disk rotates in an enclosure, which is equipped with a feedback control loop consisting of a micro-sensor, a signal processor, a power amplifier, and several piezoelectric (PZT) actuator patches distributed on the cover of the enclosure. The actuator patches are mounted on the inner or the outer surfaces of the enclosure to produce necessary control force required through the airflow around the disk. The control mechanism for rotating disk flutter using enclosure surfaces bonded with sensors and piezoelectric actuators is thoroughly studied through analytical simulations. The sensor output is used to determine the amount of input to the actuator for controlling the response of the disk in a closed loop configuration. The dynamic stability of the disk-enclosure system, together with the feedback control loop, is analyzed as a complex eigenvalue problem, which is solved using Galerkin's discretization procedure. The results show that the disk flutter can be reduced effectively with proper configurations of the control gain and the phase shift through the actuations of PZT patches. The effectiveness of different feedback control methods in altering system characteristics and system response has been investigated. The control capability, in terms of control gain, phase shift, and especially the physical configuration of actuator patches, are also evaluated by calculating the complex eigenvalues and the maximum displacement produced by the actuators. To achieve a optimal control performance, sizes, positions and shapes of PZT patches used need to be optimized and such optimization has been achieved through numerical simulations.

Final Technical Report: Distributed Controls for High Penetrations of Renewables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byrne, Raymond H.; Neely, Jason C.; Rashkin, Lee J.

2015-12-01

The goal of this effort was to apply four potential control analysis/design approaches to the design of distributed grid control systems to address the impact of latency and communications uncertainty with high penetrations of photovoltaic (PV) generation. The four techniques considered were: optimal fixed structure control; Nyquist stability criterion; vector Lyapunov analysis; and Hamiltonian design methods. A reduced order model of the Western Electricity Coordinating Council (WECC) developed for the Matlab Power Systems Toolbox (PST) was employed for the study, as well as representative smaller systems (e.g., a two-area, three-area, and four-area power system). Excellent results were obtained with themore » optimal fixed structure approach, and the methodology we developed was published in a journal article. This approach is promising because it offers a method for designing optimal control systems with the feedback signals available from Phasor Measurement Unit (PMU) data as opposed to full state feedback or the design of an observer. The Nyquist approach inherently handles time delay and incorporates performance guarantees (e.g., gain and phase margin). We developed a technique that works for moderate sized systems, but the approach does not scale well to extremely large system because of computational complexity. The vector Lyapunov approach was applied to a two area model to demonstrate the utility for modeling communications uncertainty. Application to large power systems requires a method to automatically expand/contract the state space and partition the system so that communications uncertainty can be considered. The Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) design methodology was selected to investigate grid systems for energy storage requirements to support high penetration of variable or stochastic generation (such as wind and PV) and loads. This method was applied to several small system models.« less

Just-in-Time Feedback in Diet and Physical Activity Interventions: Systematic Review and Practical Design Framework

PubMed Central

Robertson, Michael C; Dunton, Genevieve Fridlund; Kerr, Jacqueline; Haffey, Meghan E; Burnett, Taylor; Basen-Engquist, Karen; Hicklen, Rachel S

2018-01-01

Background The integration of body-worn sensors with mobile devices presents a tremendous opportunity to improve just-in-time behavioral interventions by enhancing bidirectional communication between investigators and their participants. This approach can be used to deliver supportive feedback at critical moments to optimize the attainment of health behavior goals. Objective The goals of this systematic review were to summarize data on the content characteristics of feedback messaging used in diet and physical activity (PA) interventions and to develop a practical framework for designing just-in-time feedback for behavioral interventions. Methods Interventions that included just-in-time feedback on PA, sedentary behavior, or dietary intake were eligible for inclusion. Feedback content and efficacy data were synthesized descriptively. Results The review included 31 studies (15/31, 48%, targeting PA or sedentary behavior only; 13/31, 42%, targeting diet and PA; and 3/31, 10%, targeting diet only). All studies used just-in-time feedback, 30 (97%, 30/31) used personalized feedback, and 24 (78%, 24/31) used goal-oriented feedback, but only 5 (16%, 5/31) used actionable feedback. Of the 9 studies that tested the efficacy of providing feedback to promote behavior change, 4 reported significant improvements in health behavior. In 3 of these 4 studies, feedback was continuously available, goal-oriented, or actionable. Conclusions Feedback that was continuously available, personalized, and actionable relative to a known behavioral objective was prominent in intervention studies with significant behavior change outcomes. Future research should determine whether all or some of these characteristics are needed to optimize the effect of feedback in just-in-time interventions. PMID:29567638

Feedback control of a Darrieus wind turbine and optimization of the produced energy

NASA Astrophysics Data System (ADS)

Maurin, T.; Henry, B.; Devos, F.; de Saint Louvent, B.; Gosselin, J.

1984-03-01

A microprocessor-driven control system, applied to the feedback control of a Darrieus wind turbine is presented. The use of a dc machine as a generator to recover the energy and as a motor to start the engine, allows simplified power electronics. The architecture of the control unit is built to ensure four different functions: starting, optimization of the recoverable energy, regulation of the speed, and braking. An experimental study of the system in a wind tunnel allowed optimization of the coefficients of the proportional and integral (pi) control algorithm. The electrical energy recovery was found to be much more efficient using the feedback system than without the control unit. This system allows a better characterization of the wind turbine and a regulation adapted to the wind statistics observed in one given geographical location.

Cultivating Engagement and Enjoyment in Exergames Using Feedback, Challenge, and Rewards.

PubMed

Lyons, Elizabeth J

2015-02-01

This article reviews theoretical and empirical evidence related to three mechanisms for encouraging enjoyment during exergame play: Feedback, challenge, and rewards. A literature search and narrative review were conducted. Feedback is found in nearly all exergames, and richer, more in-depth feedback is associated with increased activity. Challenge is a vital component of any videogame, and exergames include physical as well as cognitive challenges. Flow states have traditionally been conceptualized as occurring when an optimal match between player skills and game challenge occurs. However, failure and retrial are necessary for feelings of overall satisfaction and fun, despite not necessarily being ideally fun or satisfying themselves. Rewards are a more complicated issue, with significant theoretical and empirical evidence suggesting positive and negative effects of reward systems. How rewards are integrated into the mechanics and storyline of the game likely impacts how they are perceived and, thus, their effectiveness. Finally, integration of these mechanisms into exergames requires specific attention to both cognitive and physical implementations. Movements that are not themselves enjoyable or engaging may lead to cheating and lower energy expenditure. Feedback, challenge, and rewards are promising mechanisms by which exergames could become more enjoyable. How these concepts are operationalized can affect physical and psychological reactions to exergames. Attention to these concepts in future exergame development and implementation would benefit theory, research, and practice.

Cultivating Engagement and Enjoyment in Exergames Using Feedback, Challenge, and Rewards

PubMed Central

2015-01-01

Abstract Objective: This article reviews theoretical and empirical evidence related to three mechanisms for encouraging enjoyment during exergame play: Feedback, challenge, and rewards. Materials and Methods: A literature search and narrative review were conducted. Results: Feedback is found in nearly all exergames, and richer, more in-depth feedback is associated with increased activity. Challenge is a vital component of any videogame, and exergames include physical as well as cognitive challenges. Flow states have traditionally been conceptualized as occurring when an optimal match between player skills and game challenge occurs. However, failure and retrial are necessary for feelings of overall satisfaction and fun, despite not necessarily being ideally fun or satisfying themselves. Rewards are a more complicated issue, with significant theoretical and empirical evidence suggesting positive and negative effects of reward systems. How rewards are integrated into the mechanics and storyline of the game likely impacts how they are perceived and, thus, their effectiveness. Finally, integration of these mechanisms into exergames requires specific attention to both cognitive and physical implementations. Movements that are not themselves enjoyable or engaging may lead to cheating and lower energy expenditure. Conclusions: Feedback, challenge, and rewards are promising mechanisms by which exergames could become more enjoyable. How these concepts are operationalized can affect physical and psychological reactions to exergames. Attention to these concepts in future exergame development and implementation would benefit theory, research, and practice. PMID:26181675

Hybrid Solution of Stochastic Optimal Control Problems Using Gauss Pseudospectral Method and Generalized Polynomial Chaos Algorithms

DTIC Science & Technology

2012-03-01

0-486-41183-4. 15. Brown , Robert G. and Patrick Y. C. Hwang . Introduction to Random Signals and Applied Kalman Filtering. Wiley, New York, 1996. ISBN...stability and perfor- mance criteria. In the 1960’s, Kalman introduced the Linear Quadratic Regulator (LQR) method using an integral performance index...feedback of the state variables and was able to apply this method to time-varying and Multi-Input Multi-Output (MIMO) systems. Kalman further showed

New MHD feedback control schemes using the MARTe framework in RFX-mod

NASA Astrophysics Data System (ADS)

Piron, Chiara; Manduchi, Gabriele; Marrelli, Lionello; Piovesan, Paolo; Zanca, Paolo

2013-10-01

Real-time feedback control of MHD instabilities is a topic of major interest in magnetic thermonuclear fusion, since it allows to optimize a device performance even beyond its stability bounds. The stability properties of different magnetic configurations are important test benches for real-time control systems. RFX-mod, a Reversed Field Pinch experiment that can also operate as a tokamak, is a well suited device to investigate this topic. It is equipped with a sophisticated magnetic feedback system that controls MHD instabilities and error fields by means of 192 active coils and a corresponding grid of sensors. In addition, the RFX-mod control system has recently gained new potentialities thanks to the introduction of the MARTe framework and of a new CPU architecture. These capabilities allow to study new feedback algorithms relevant to both RFP and tokamak operation and to contribute to the debate on the optimal feedback strategy. This work focuses on the design of new feedback schemes. For this purpose new magnetic sensors have been explored, together with new algorithms that refine the de-aliasing computation of the radial sideband harmonics. The comparison of different sensor and feedback strategy performance is described in both RFP and tokamak experiments.

Algorithms for output feedback, multiple-model, and decentralized control problems

NASA Technical Reports Server (NTRS)

Halyo, N.; Broussard, J. R.

1984-01-01

The optimal stochastic output feedback, multiple-model, and decentralized control problems with dynamic compensation are formulated and discussed. Algorithms for each problem are presented, and their relationship to a basic output feedback algorithm is discussed. An aircraft control design problem is posed as a combined decentralized, multiple-model, output feedback problem. A control design is obtained using the combined algorithm. An analysis of the design is presented.

Optimal feedback control infinite dimensional parabolic evolution systems: Approximation techniques

NASA Technical Reports Server (NTRS)

Banks, H. T.; Wang, C.

1989-01-01

A general approximation framework is discussed for computation of optimal feedback controls in linear quadratic regular problems for nonautonomous parabolic distributed parameter systems. This is done in the context of a theoretical framework using general evolution systems in infinite dimensional Hilbert spaces. Conditions are discussed for preservation under approximation of stabilizability and detectability hypotheses on the infinite dimensional system. The special case of periodic systems is also treated.

Proper Use of Feedback Leads to an Optimal Motivational Climate

ERIC Educational Resources Information Center

Staley, Addison; Moore, E. Whitney G.

2016-01-01

Feedback given by coaches can have a profound effect on athletes' performance, as well as on their perception of the motivational climate. The Coaching Behaviors Assessment System classifies the feedback that coaches give during practices or games into 12 behavioral categories, which will be described in this article. Real-life scenarios will be…

Controllers, observers, and applications thereof

NASA Technical Reports Server (NTRS)

Gao, Zhiqiang (Inventor); Zhou, Wankun (Inventor); Miklosovic, Robert (Inventor); Radke, Aaron (Inventor); Zheng, Qing (Inventor)

2011-01-01

Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also apply to state feedback and state observer based controllers, as well as linear active disturbance rejection (ADRC) controllers. Parameterization simplifies the use of ADRC. A discrete extended state observer (DESO) and a generalized extended state observer (GESO) are described. They improve the performance of the ESO and therefore ADRC. A tracking control algorithm is also described that improves the performance of the ADRC controller. A general algorithm is described for applying ADRC to multi-input multi-output systems. Several specific applications of the control systems and processes are disclosed.

Target Uncertainty Mediates Sensorimotor Error Correction

PubMed Central

Vijayakumar, Sethu; Wolpert, Daniel M.

2017-01-01

Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects’ scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one’s response. By suggesting that subjects’ decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated. PMID:28129323

Target Uncertainty Mediates Sensorimotor Error Correction.

PubMed

Acerbi, Luigi; Vijayakumar, Sethu; Wolpert, Daniel M

2017-01-01

Human movements are prone to errors that arise from inaccuracies in both our perceptual processing and execution of motor commands. We can reduce such errors by both improving our estimates of the state of the world and through online error correction of the ongoing action. Two prominent frameworks that explain how humans solve these problems are Bayesian estimation and stochastic optimal feedback control. Here we examine the interaction between estimation and control by asking if uncertainty in estimates affects how subjects correct for errors that may arise during the movement. Unbeknownst to participants, we randomly shifted the visual feedback of their finger position as they reached to indicate the center of mass of an object. Even though participants were given ample time to compensate for this perturbation, they only fully corrected for the induced error on trials with low uncertainty about center of mass, with correction only partial in trials involving more uncertainty. The analysis of subjects' scores revealed that participants corrected for errors just enough to avoid significant decrease in their overall scores, in agreement with the minimal intervention principle of optimal feedback control. We explain this behavior with a term in the loss function that accounts for the additional effort of adjusting one's response. By suggesting that subjects' decision uncertainty, as reflected in their posterior distribution, is a major factor in determining how their sensorimotor system responds to error, our findings support theoretical models in which the decision making and control processes are fully integrated.

Combinatorics of feedback in cellular uptake and metabolism of small molecules.

PubMed

Krishna, Sandeep; Semsey, Szabolcs; Sneppen, Kim

2007-12-26

We analyze the connection between structure and function for regulatory motifs associated with cellular uptake and usage of small molecules. Based on the boolean logic of the feedback we suggest four classes: the socialist, consumer, fashion, and collector motifs. We find that the socialist motif is good for homeostasis of a useful but potentially poisonous molecule, whereas the consumer motif is optimal for nutrition molecules. Accordingly, examples of these motifs are found in, respectively, the iron homeostasis system in various organisms and in the uptake of sugar molecules in bacteria. The remaining two motifs have no obvious analogs in small molecule regulation, but we illustrate their behavior using analogies to fashion and obesity. These extreme motifs could inspire construction of synthetic systems that exhibit bistable, history-dependent states, and homeostasis of flux (rather than concentration).

Elastic robot control - Nonlinear inversion and linear stabilization

NASA Technical Reports Server (NTRS)

Singh, S. N.; Schy, A. A.

1986-01-01

An approach to the control of elastic robot systems for space applications using inversion, servocompensation, and feedback stabilization is presented. For simplicity, a robot arm (PUMA type) with three rotational joints is considered. The third link is assumed to be elastic. Using an inversion algorithm, a nonlinear decoupling control law u(d) is derived such that in the closed-loop system independent control of joint angles by the three joint torquers is accomplished. For the stabilization of elastic oscillations, a linear feedback torquer control law u(s) is obtained applying linear quadratic optimization to the linearized arm model augmented with a servocompensator about the terminal state. Simulation results show that in spite of uncertainties in the payload and vehicle angular velocity, good joint angle control and damping of elastic oscillations are obtained with the torquer control law u = u(d) + u(s).

Generation of “gigantic” ultra-short microwave pulses based on passive mode-locking effect in electron oscillators with saturable absorber in the feedback loop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ginzburg, N. S., E-mail: ginzburg@appl.sci-nnov.ru; Denisov, G. G.; Vilkov, M. N.

2016-05-15

A periodic train of powerful ultrashort microwave pulses can be generated in electron oscillators with a non-linear saturable absorber installed in the feedback loop. This method of pulse formation resembles the passive mode-locking widely used in laser physics. Nevertheless, there is a specific feature in the mechanism of pulse amplification when consecutive energy extraction from different fractions of a stationary electron beam takes place due to pulse slippage over the beam caused by the difference between the wave group velocity and the electron axial velocity. As a result, the peak power of generated “gigantic” pulses can exceed not only themore » level of steady-state generation but also, in the optimal case, the power of the driving electron beam.« less

Control of Vibratory Energy Harvesters in the Presence of Nonlinearities and Power-Flow Constraints

NASA Astrophysics Data System (ADS)

Cassidy, Ian L.

Over the past decade, a significant amount of research activity has been devoted to developing electromechanical systems that can convert ambient mechanical vibrations into usable electric power. Such systems, referred to as vibratory energy harvesters, have a number of useful of applications, ranging in scale from self-powered wireless sensors for structural health monitoring in bridges and buildings to energy harvesting from ocean waves. One of the most challenging aspects of this technology concerns the efficient extraction and transmission of power from transducer to storage. Maximizing the rate of power extraction from vibratory energy harvesters is further complicated by the stochastic nature of the disturbance. The primary purpose of this dissertation is to develop feedback control algorithms which optimize the average power generated from stochastically-excited vibratory energy harvesters. This dissertation will illustrate the performance of various controllers using two vibratory energy harvesting systems: an electromagnetic transducer embedded within a flexible structure, and a piezoelectric bimorph cantilever beam. Compared with piezoelectric systems, large-scale electromagnetic systems have received much less attention in the literature despite their ability to generate power at the watt--kilowatt scale. Motivated by this observation, the first part of this dissertation focuses on developing an experimentally validated predictive model of an actively controlled electromagnetic transducer. Following this experimental analysis, linear-quadratic-Gaussian control theory is used to compute unconstrained state feedback controllers for two ideal vibratory energy harvesting systems. This theory is then augmented to account for competing objectives, nonlinearities in the harvester dynamics, and non-quadratic transmission loss models in the electronics. In many vibratory energy harvesting applications, employing a bi-directional power electronic drive to actively control the harvester is infeasible due to the high levels of parasitic power required to operate the drive. For the case where a single-directional drive is used, a constraint on the directionality of power-flow is imposed on the system, which necessitates the use of nonlinear feedback. As such, a sub-optimal controller for power-flow-constrained vibratory energy harvesters is presented, which is analytically guaranteed to outperform the optimal static admittance controller. Finally, the last section of this dissertation explores a numerical approach to compute optimal discretized control manifolds for systems with power-flow constraints. Unlike the sub-optimal nonlinear controller, the numerical controller satisfies the necessary conditions for optimality by solving the stochastic Hamilton-Jacobi equation.

A guidance law for hypersonic descent to a point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisler, G.R.; Hull, D.G.

1992-05-01

A neighboring external control problem is formulated for a hypersonic glider to execute a maximum-terminal-velocity descent to a stationary target. The resulting two-part, feedback control scheme initially solves a nonlinear algebraic problem to generate a nominal trajectory to the target altitude. Secondly, a neighboring optimal path computation about the nominal provides a lift and side-force perturbations necessary to achieve the target downrange and crossrange. On-line feedback simulations of the proposed scheme and a form of proportional navigation are compared with an off-line parameter optimization method. The neighboring optimal terminal velocity compares very well with the parameter optimization solution and ismore » far superior to proportional navigation. 8 refs.« less

A guidance law for hypersonic descent to a point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisler, G.R.; Hull, D.G.

1992-01-01

A neighboring external control problem is formulated for a hypersonic glider to execute a maximum-terminal-velocity descent to a stationary target. The resulting two-part, feedback control scheme initially solves a nonlinear algebraic problem to generate a nominal trajectory to the target altitude. Secondly, a neighboring optimal path computation about the nominal provides a lift and side-force perturbations necessary to achieve the target downrange and crossrange. On-line feedback simulations of the proposed scheme and a form of proportional navigation are compared with an off-line parameter optimization method. The neighboring optimal terminal velocity compares very well with the parameter optimization solution and ismore » far superior to proportional navigation. 8 refs.« less

Control of cardiac alternans by mechanical and electrical feedback.

PubMed

Yapari, Felicia; Deshpande, Dipen; Belhamadia, Youssef; Dubljevic, Stevan

2014-07-01

A persistent alternation in the cardiac action potential duration has been linked to the onset of ventricular arrhythmia, which may lead to sudden cardiac death. A coupling between these cardiac alternans and the intracellular calcium dynamics has also been identified in previous studies. In this paper, the system of PDEs describing the small amplitude of alternans and the alternation of peak intracellular Ca(2+) are stabilized by optimal boundary and spatially distributed actuation. A simulation study demonstrating the successful annihilation of both alternans on a one-dimensional cable of cardiac cells by utilizing the full-state feedback controller is presented. Complimentary to these studies, a three variable Nash-Panfilov model is used to investigate alternans annihilation via mechanical (or stretch) perturbations. The coupled model includes the active stress which defines the mechanical properties of the tissue and is utilized in the feedback algorithm as an independent input from the pacing based controller realization in alternans annihilation. Simulation studies of both control methods demonstrate that the proposed methods can successfully annihilate alternans in cables that are significantly longer than 1 cm, thus overcoming the limitations of earlier control efforts.

Surgeon Training in Telerobotic Surgery via a Hardware-in-the-Loop Simulator

PubMed Central

Alemzadeh, Homa; Chen, Daniel; Kalbarczyk, Zbigniew; Iyer, Ravishankar K.; Kesavadas, Thenkurussi

2017-01-01

This work presents a software and hardware framework for a telerobotic surgery safety and motor skill training simulator. The aims are at providing trainees a comprehensive simulator for acquiring essential skills to perform telerobotic surgery. Existing commercial robotic surgery simulators lack features for safety training and optimal motion planning, which are critical factors in ensuring patient safety and efficiency in operation. In this work, we propose a hardware-in-the-loop simulator directly introducing these two features. The proposed simulator is built upon the Raven-II™ open source surgical robot, integrated with a physics engine and a safety hazard injection engine. Also, a Fast Marching Tree-based motion planning algorithm is used to help trainee learn the optimal instrument motion patterns. The main contributions of this work are (1) reproducing safety hazards events, related to da Vinci™ system, reported to the FDA MAUDE database, with a novel haptic feedback strategy to provide feedback to the operator when the underlying dynamics differ from the real robot's states so that the operator will be aware and can mitigate the negative impact of the safety-critical events, and (2) using motion planner to generate semioptimal path in an interactive robotic surgery training environment. PMID:29065635

A Bayesian Account of Vocal Adaptation to Pitch-Shifted Auditory Feedback

PubMed Central

Hahnloser, Richard H. R.

2017-01-01

Motor systems are highly adaptive. Both birds and humans compensate for synthetically induced shifts in the pitch (fundamental frequency) of auditory feedback stemming from their vocalizations. Pitch-shift compensation is partial in the sense that large shifts lead to smaller relative compensatory adjustments of vocal pitch than small shifts. Also, compensation is larger in subjects with high motor variability. To formulate a mechanistic description of these findings, we adapt a Bayesian model of error relevance. We assume that vocal-auditory feedback loops in the brain cope optimally with known sensory and motor variability. Based on measurements of motor variability, optimal compensatory responses in our model provide accurate fits to published experimental data. Optimal compensation correctly predicts sensory acuity, which has been estimated in psychophysical experiments as just-noticeable pitch differences. Our model extends the utility of Bayesian approaches to adaptive vocal behaviors. PMID:28135267

Output-Feedback Control of Unknown Linear Discrete-Time Systems With Stochastic Measurement and Process Noise via Approximate Dynamic Programming.

PubMed

Wang, Jun-Sheng; Yang, Guang-Hong

2017-07-25

This paper studies the optimal output-feedback control problem for unknown linear discrete-time systems with stochastic measurement and process noise. A dithered Bellman equation with the innovation covariance matrix is constructed via the expectation operator given in the form of a finite summation. On this basis, an output-feedback-based approximate dynamic programming method is developed, where the terms depending on the innovation covariance matrix are available with the aid of the innovation covariance matrix identified beforehand. Therefore, by iterating the Bellman equation, the resulting value function can converge to the optimal one in the presence of the aforementioned noise, and the nearly optimal control laws are delivered. To show the effectiveness and the advantages of the proposed approach, a simulation example and a velocity control experiment on a dc machine are employed.

Coherent control of plasma dynamics by feedback-optimized wavefront manipulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Z.-H.; Hou, B.; Gao, G.

2015-05-15

Plasmas generated by an intense laser pulse can support coherent structures such as large amplitude wakefield that can affect the outcome of an experiment. We investigate the coherent control of plasma dynamics by feedback-optimized wavefront manipulation using a deformable mirror. The experimental outcome is directly used as feedback in an evolutionary algorithm for optimization of the phase front of the driving laser pulse. In this paper, we applied this method to two different experiments: (i) acceleration of electrons in laser driven plasma waves and (ii) self-compression of optical pulses induced by ionization nonlinearity. The manipulation of the laser wavefront leadsmore » to orders of magnitude improvement to electron beam properties such as the peak charge, beam divergence, and transverse emittance. The demonstration of coherent control for plasmas opens new possibilities for future laser-based accelerators and their applications.« less

Optimal control theory investigation of proprotor/wing response to vertical gust

NASA Technical Reports Server (NTRS)

Frick, J. K. D.; Johnson, W.

1974-01-01

Optimal control theory is used to design linear state variable feedback to improve the dynamic characteristics of a rotor and cantilever wing representing the tilting proprotor aircraft in cruise flight. The response to a vertical gust and system damping are used as criteria for the open and closed loop performance. The improvement in the dynamic characteristics achievable is examined for a gimballed rotor and for a hingeless rotor design. Several features of the design process are examined, including: (1) using only the wing or only the rotor dynamics in the control system design; (2) the use of a wing flap as well as the rotor controls for inputs; (3) and the performance of the system designed for one velocity at other forward speeds.

Animal personality and state-behaviour feedbacks: a review and guide for empiricists.

PubMed

Sih, Andrew; Mathot, Kimberley J; Moirón, María; Montiglio, Pierre-Olivier; Wolf, Max; Dingemanse, Niels J

2015-01-01

An exciting area in behavioural ecology focuses on understanding why animals exhibit consistent among-individual differences in behaviour (animal personalities). Animal personality has been proposed to emerge as an adaptation to individual differences in state variables, leading to the question of why individuals differ consistently in state. Recent theory emphasizes the role that positive feedbacks between state and behaviour can play in producing consistent among-individual covariance between state and behaviour, hence state-dependent personality. We review the role of feedbacks in recent models of adaptive personalities, and provide guidelines for empirical testing of model assumptions and predictions. We discuss the importance of the mediating effects of ecology on these feedbacks, and provide a roadmap for including state-behaviour feedbacks in behavioural ecology research. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bifurcation and Control in a Singular Phytoplankton-Zooplankton-Fish Model with Nonlinear Fish Harvesting and Taxation

NASA Astrophysics Data System (ADS)

Meng, Xin-You; Wu, Yu-Qian

In this paper, a delayed differential algebraic phytoplankton-zooplankton-fish model with taxation and nonlinear fish harvesting is proposed. In the absence of time delay, the existence of singularity induced bifurcation is discussed by regarding economic interest as bifurcation parameter. A state feedback controller is designed to eliminate singularity induced bifurcation. Based on Liu’s criterion, Hopf bifurcation occurs at the interior equilibrium when taxation is taken as bifurcation parameter and is more than its corresponding critical value. In the presence of time delay, by analyzing the associated characteristic transcendental equation, the interior equilibrium loses local stability when time delay crosses its critical value. What’s more, the direction of Hopf bifurcation and stability of the bifurcating periodic solutions are investigated based on normal form theory and center manifold theorem, and nonlinear state feedback controller is designed to eliminate Hopf bifurcation. Furthermore, Pontryagin’s maximum principle has been used to obtain optimal tax policy to maximize the benefit as well as the conservation of the ecosystem. Finally, some numerical simulations are given to demonstrate our theoretical analysis.

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

Comparison of an enhanced versus a written feedback model on the management of Medicare inpatients with venous thrombosis.

PubMed

Hayes, R; Bratzler, D; Armour, B; Moore, L; Murray, C; Stevens, B R; Radford, M; Fitzgerald, D; Elward, K; Ballard, D J

2001-03-01

A multistate randomized study conducted under the Health Care Financing Administration's (HCFA's) Health Care Quality Improvement Program (HCQIP) offered the opportunity to compare the effect of a written feedback intervention (WFI) with that of an enhanced feedback intervention (EFI) on improving the anticoagulant management of Medicare beneficiaries who present to the hospital with venous thromboembolic disease. Twenty-nine hospitals in five states were randomly assigned to receive written hospital-specific feedback (WFI) of feedback enhanced by the participation of a trained physician, quality improvement tools, and an Anticoagulant Management of Venous Thrombosis (AMVT) project liaison (EFI). Differences in the performance of five quality indicators between baseline and remeasurement were assessed. Quality managers were interviewed to determine perceptions of project implementation. No significant differences in the change from baseline to remeasurement were found between the two intervention groups. Significant improvement in one indicator and significant decline in two indicators were found for one or both groups. Yet 59% of all quality managers perceived the AMVT project as being successful to very successful, and more EFI quality managers perceived success than did WFI managers (71% versus 40%). In the majority of EFI hospitals, physician liaisons played an important role in project implementation. Study results indicated that the addition of a physician liaison, quality improvement tools, and a project liaison did not provide incremental value to hospital-specific feedback for improving quality of care. Future studies with larger sample sizes, lengthier follow-up periods, and interventions that include more of the elements shown to affect practice behavior change are needed to identify an optimal feedback model for use by external quality management organizations.

Electron beam energy stabilization using a neural network hybrid controller at the Australian Synchrotron Linac.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meier, E.; Morgan, M. J.; Biedron, S. G.

2009-01-01

This paper describes the implementation of a neural network hybrid controller for energy stabilization at the Australian Synchrotron Linac. The structure of the controller consists of a neural network (NNET) feed forward control, augmented by a conventional Proportional-Integral (PI) feedback controller to ensure stability of the system. The system is provided with past states of the machine in order to predict its future state, and therefore apply appropriate feed forward control. The NNET is able to cancel multiple frequency jitter in real-time. When it is not performing optimally due to jitter changes, the system can successfully be augmented by themore » PI controller to attenuate the remaining perturbations. With a view to control the energy and bunch length at the FERMI{at}Elettra Free Electron Laser (FEL), the present study considers a neural network hybrid feed forward-feedback type of control to rectify limitations related to feedback systems, such as poor response for high jitter frequencies or limited bandwidth, while ensuring robustness of control. The Australian Synchrotron Linac is equipped with a beam position monitor (BPM), that was provided by Sincrotrone Trieste from a former transport line thus allowing energy measurements and energy control experiments. The present study will consequently focus on correcting energy jitter induced by variations in klystron phase and voltage.« less

Optimal reorientation of asymmetric underactuated spacecraft using differential flatness and receding horizon control

NASA Astrophysics Data System (ADS)

Cai, Wei-wei; Yang, Le-ping; Zhu, Yan-wei

2015-01-01

This paper presents a novel method integrating nominal trajectory optimization and tracking for the reorientation control of an underactuated spacecraft with only two available control torque inputs. By employing a pseudo input along the uncontrolled axis, the flatness property of a general underactuated spacecraft is extended explicitly, by which the reorientation trajectory optimization problem is formulated into the flat output space with all the differential constraints eliminated. Ultimately, the flat output optimization problem is transformed into a nonlinear programming problem via the Chebyshev pseudospectral method, which is improved by the conformal map and barycentric rational interpolation techniques to overcome the side effects of the differential matrix's ill-conditions on numerical accuracy. Treating the trajectory tracking control as a state regulation problem, we develop a robust closed-loop tracking control law using the receding-horizon control method, and compute the feedback control at each control cycle rapidly via the differential transformation method. Numerical simulation results show that the proposed control scheme is feasible and effective for the reorientation maneuver.

Regulation control and energy management scheme for wireless power transfer

DOEpatents

Miller, John M.

2015-12-29

Power transfer rate at a charging facility can be maximized by employing a feedback scheme. The state of charge (SOC) and temperature of the regenerative energy storage system (RESS) pack of a vehicle is monitored to determine the load due to the RESS pack. An optimal frequency that cancels the imaginary component of the input impedance for the output signal from a grid converter is calculated from the load of the RESS pack, and a frequency offset f* is made to the nominal frequency f.sub.0 of the grid converter output based on the resonance frequency of a magnetically coupled circuit. The optimal frequency can maximize the efficiency of the power transfer. Further, an optimal grid converter duty ratio d* can be derived from the charge rate of the RESS pack. The grid converter duty ratio d* regulates wireless power transfer (WPT) power level.

Active control of transient rotordynamic vibration by optimal control methods

NASA Technical Reports Server (NTRS)

Palazzolo, A. B.; Lin, R. R.; Alexander, R. M.; Kascak, A. F.

1988-01-01

Although considerable effort has been put into the study of steady state vibration control, there are few methods applicable to transient vibration control of rotorbearing systems. In this paper optimal control theory has been adopted to minimize rotor vibration due to sudden imbalance, e.g., blade loss. The system gain matrix is obtained by choosing the weighting matrices and solving the Riccati equation. Control forces are applied to the system via a feedback loop. A seven mass rotor system is simulated for illustration. A relationship between the number of sensors and the number of modes used in the optimal control model is investigated. Comparisons of responses are made for various configurations of modes, sensors, and actuators. Furthermore, spillover effect is examined by comparing results from collocated and noncollocated sensor configurations. Results show that shaft vibration is significantly attenuated in the closed loop system.

Active flutter suppression using optical output feedback digital controllers

NASA Technical Reports Server (NTRS)

1982-01-01

A method for synthesizing digital active flutter suppression controllers using the concept of optimal output feedback is presented. A convergent algorithm is employed to determine constrained control law parameters that minimize an infinite time discrete quadratic performance index. Low order compensator dynamics are included in the control law and the compensator parameters are computed along with the output feedback gain as part of the optimization process. An input noise adjustment procedure is used to improve the stability margins of the digital active flutter controller. Sample rate variation, prefilter pole variation, control structure variation and gain scheduling are discussed. A digital control law which accommodates computation delay can stabilize the wing with reasonable rms performance and adequate stability margins.

Linear feedback stabilization of a dispersively monitored qubit

NASA Astrophysics Data System (ADS)

Patti, Taylor Lee; Chantasri, Areeya; García-Pintos, Luis Pedro; Jordan, Andrew N.; Dressel, Justin

2017-08-01

The state of a continuously monitored qubit evolves stochastically, exhibiting competition between coherent Hamiltonian dynamics and diffusive partial collapse dynamics that follow the measurement record. We couple these distinct types of dynamics together by linearly feeding the collected record for dispersive energy measurements directly back into a coherent Rabi drive amplitude. Such feedback turns the competition cooperative and effectively stabilizes the qubit state near a target state. We derive the conditions for obtaining such dispersive state stabilization and verify the stabilization conditions numerically. We include common experimental nonidealities, such as energy decay, environmental dephasing, detector efficiency, and feedback delay, and show that the feedback delay has the most significant negative effect on the feedback protocol. Setting the measurement collapse time scale to be long compared to the feedback delay yields the best stabilization.

Autopilot for frequency-modulation atomic force microscopy.

PubMed

Kuchuk, Kfir; Schlesinger, Itai; Sivan, Uri

2015-10-01

One of the most challenging aspects of operating an atomic force microscope (AFM) is finding optimal feedback parameters. This statement applies particularly to frequency-modulation AFM (FM-AFM), which utilizes three feedback loops to control the cantilever excitation amplitude, cantilever excitation frequency, and z-piezo extension. These loops are regulated by a set of feedback parameters, tuned by the user to optimize stability, sensitivity, and noise in the imaging process. Optimization of these parameters is difficult due to the coupling between the frequency and z-piezo feedback loops by the non-linear tip-sample interaction. Four proportional-integral (PI) parameters and two lock-in parameters regulating these loops require simultaneous optimization in the presence of a varying unknown tip-sample coupling. Presently, this optimization is done manually in a tedious process of trial and error. Here, we report on the development and implementation of an algorithm that computes the control parameters automatically. The algorithm reads the unperturbed cantilever resonance frequency, its quality factor, and the z-piezo driving signal power spectral density. It analyzes the poles and zeros of the total closed loop transfer function, extracts the unknown tip-sample transfer function, and finds four PI parameters and two lock-in parameters for the frequency and z-piezo control loops that optimize the bandwidth and step response of the total system. Implementation of the algorithm in a home-built AFM shows that the calculated parameters are consistently excellent and rarely require further tweaking by the user. The new algorithm saves the precious time of experienced users, facilitates utilization of FM-AFM by casual users, and removes the main hurdle on the way to fully automated FM-AFM.

Autopilot for frequency-modulation atomic force microscopy

NASA Astrophysics Data System (ADS)

Kuchuk, Kfir; Schlesinger, Itai; Sivan, Uri

2015-10-01

One of the most challenging aspects of operating an atomic force microscope (AFM) is finding optimal feedback parameters. This statement applies particularly to frequency-modulation AFM (FM-AFM), which utilizes three feedback loops to control the cantilever excitation amplitude, cantilever excitation frequency, and z-piezo extension. These loops are regulated by a set of feedback parameters, tuned by the user to optimize stability, sensitivity, and noise in the imaging process. Optimization of these parameters is difficult due to the coupling between the frequency and z-piezo feedback loops by the non-linear tip-sample interaction. Four proportional-integral (PI) parameters and two lock-in parameters regulating these loops require simultaneous optimization in the presence of a varying unknown tip-sample coupling. Presently, this optimization is done manually in a tedious process of trial and error. Here, we report on the development and implementation of an algorithm that computes the control parameters automatically. The algorithm reads the unperturbed cantilever resonance frequency, its quality factor, and the z-piezo driving signal power spectral density. It analyzes the poles and zeros of the total closed loop transfer function, extracts the unknown tip-sample transfer function, and finds four PI parameters and two lock-in parameters for the frequency and z-piezo control loops that optimize the bandwidth and step response of the total system. Implementation of the algorithm in a home-built AFM shows that the calculated parameters are consistently excellent and rarely require further tweaking by the user. The new algorithm saves the precious time of experienced users, facilitates utilization of FM-AFM by casual users, and removes the main hurdle on the way to fully automated FM-AFM.

Autopilot for frequency-modulation atomic force microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuchuk, Kfir; Schlesinger, Itai; Sivan, Uri, E-mail: phsivan@tx.technion.ac.il

2015-10-15

One of the most challenging aspects of operating an atomic force microscope (AFM) is finding optimal feedback parameters. This statement applies particularly to frequency-modulation AFM (FM-AFM), which utilizes three feedback loops to control the cantilever excitation amplitude, cantilever excitation frequency, and z-piezo extension. These loops are regulated by a set of feedback parameters, tuned by the user to optimize stability, sensitivity, and noise in the imaging process. Optimization of these parameters is difficult due to the coupling between the frequency and z-piezo feedback loops by the non-linear tip-sample interaction. Four proportional-integral (PI) parameters and two lock-in parameters regulating these loopsmore » require simultaneous optimization in the presence of a varying unknown tip-sample coupling. Presently, this optimization is done manually in a tedious process of trial and error. Here, we report on the development and implementation of an algorithm that computes the control parameters automatically. The algorithm reads the unperturbed cantilever resonance frequency, its quality factor, and the z-piezo driving signal power spectral density. It analyzes the poles and zeros of the total closed loop transfer function, extracts the unknown tip-sample transfer function, and finds four PI parameters and two lock-in parameters for the frequency and z-piezo control loops that optimize the bandwidth and step response of the total system. Implementation of the algorithm in a home-built AFM shows that the calculated parameters are consistently excellent and rarely require further tweaking by the user. The new algorithm saves the precious time of experienced users, facilitates utilization of FM-AFM by casual users, and removes the main hurdle on the way to fully automated FM-AFM.« less

Efficacy of chest compressions directed by end-tidal CO2 feedback in a pediatric resuscitation model of basic life support.

PubMed

Hamrick, Jennifer L; Hamrick, Justin T; Lee, Jennifer K; Lee, Benjamin H; Koehler, Raymond C; Shaffner, Donald H

2014-04-14

End-tidal carbon dioxide (ETCO2) correlates with systemic blood flow and resuscitation rate during cardiopulmonary resuscitation (CPR) and may potentially direct chest compression performance. We compared ETCO2-directed chest compressions with chest compressions optimized to pediatric basic life support guidelines in an infant swine model to determine the effect on rate of return of spontaneous circulation (ROSC). Forty 2-kg piglets underwent general anesthesia, tracheostomy, placement of vascular catheters, ventricular fibrillation, and 90 seconds of no-flow before receiving 10 or 12 minutes of pediatric basic life support. In the optimized group, chest compressions were optimized by marker, video, and verbal feedback to obtain American Heart Association-recommended depth and rate. In the ETCO2-directed group, compression depth, rate, and hand position were modified to obtain a maximal ETCO2 without video or verbal feedback. After the interval of pediatric basic life support, external defibrillation and intravenous epinephrine were administered for another 10 minutes of CPR or until ROSC. Mean ETCO2 at 10 minutes of CPR was 22.7±7.8 mm Hg in the optimized group (n=20) and 28.5±7.0 mm Hg in the ETCO2-directed group (n=20; P=0.02). Despite higher ETCO2 and mean arterial pressure in the latter group, ROSC rates were similar: 13 of 20 (65%; optimized) and 14 of 20 (70%; ETCO2 directed). The best predictor of ROSC was systemic perfusion pressure. Defibrillation attempts, epinephrine doses required, and CPR-related injuries were similar between groups. The use of ETCO2-directed chest compressions is a novel guided approach to resuscitation that can be as effective as standard CPR optimized with marker, video, and verbal feedback.

Object discrimination using optimized multi-frequency auditory cross-modal haptic feedback.

PubMed

Gibson, Alison; Artemiadis, Panagiotis

2014-01-01

As the field of brain-machine interfaces and neuro-prosthetics continues to grow, there is a high need for sensor and actuation mechanisms that can provide haptic feedback to the user. Current technologies employ expensive, invasive and often inefficient force feedback methods, resulting in an unrealistic solution for individuals who rely on these devices. This paper responds through the development, integration and analysis of a novel feedback architecture where haptic information during the neural control of a prosthetic hand is perceived through multi-frequency auditory signals. Through representing force magnitude with volume and force location with frequency, the feedback architecture can translate the haptic experiences of a robotic end effector into the alternative sensory modality of sound. Previous research with the proposed cross-modal feedback method confirmed its learnability, so the current work aimed to investigate which frequency map (i.e. frequency-specific locations on the hand) is optimal in helping users distinguish between hand-held objects and tasks associated with them. After short use with the cross-modal feedback during the electromyographic (EMG) control of a prosthetic hand, testing results show that users are able to use audial feedback alone to discriminate between everyday objects. While users showed adaptation to three different frequency maps, the simplest map containing only two frequencies was found to be the most useful in discriminating between objects. This outcome provides support for the feasibility and practicality of the cross-modal feedback method during the neural control of prosthetics.

Comparison of MERRA-2 and ECCO-v4 ocean surface heat fluxes: Consequences of different forcing feedbacks on ocean circulation and implications for climate data assimilation.

NASA Astrophysics Data System (ADS)

Strobach, E.; Molod, A.; Menemenlis, D.; Forget, G.; Hill, C. N.; Campin, J. M.; Heimbach, P.

2017-12-01

Forcing ocean models with reanalysis data is a common practice in ocean modeling. As part of this practice, prescribed atmospheric state variables and interactive ocean SST are used to calculate fluxes between the ocean and the atmosphere. When forcing an ocean model with reanalysis fields, errors in the reanalysis data, errors in the ocean model and errors in the forcing formulation will generate a different solution compared to other ocean reanalysis solutions (which also have their own errors). As a first step towards a consistent coupled ocean-atmosphere reanalysis, we compare surface heat fluxes from a state-of-the-art atmospheric reanalysis, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), to heat fluxes from a state-of-the-art oceanic reanalysis, the Estimating the Circulation and Climate of the Ocean Version 4, Release 2 (ECCO-v4). Then, we investigate the errors associated with the MITgcm ocean model in its ECCO-v4 ocean reanalysis configuration (1992-2011) when it is forced with MERRA-2 atmospheric reanalysis fields instead of with the ECCO-v4 adjoint optimized ERA-interim state variables. This is done by forcing ECCO-v4 ocean with and without feedbacks from MERRA-2 related to turbulent fluxes of heat and moisture and the outgoing long wave radiation. In addition, we introduce an intermediate forcing method that includes only the feedback from the interactive outgoing long wave radiation. The resulting ocean circulation is compared with ECCO-v4 reanalysis and in-situ observations. We show that, without feedbacks, imbalances in the energy and the hydrological cycles of MERRA-2 (which are directly related to the fact it was created without interactive ocean) result in considerable SST drifts and a large reduction in sea level. The bulk formulae and interactive outgoing long wave radiation, although providing air-sea feedbacks and reducing model-data misfit, strongly relax the ocean to observed SST and may result in unwanted features such as large change in the water budget. These features have implications in on desired forcing recipe to be used. The results strongly and unambiguously argue for next generation data assimilation climate studies to involve fully coupled systems.

Legendre-tau approximation for functional differential equations. Part 2: The linear quadratic optimal control problem

NASA Technical Reports Server (NTRS)

Ito, K.; Teglas, R.

1984-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

Legendre-tau approximation for functional differential equations. II - The linear quadratic optimal control problem

NASA Technical Reports Server (NTRS)

Ito, Kazufumi; Teglas, Russell

1987-01-01

The numerical scheme based on the Legendre-tau approximation is proposed to approximate the feedback solution to the linear quadratic optimal control problem for hereditary differential systems. The convergence property is established using Trotter ideas. The method yields very good approximations at low orders and provides an approximation technique for computing closed-loop eigenvalues of the feedback system. A comparison with existing methods (based on averaging and spline approximations) is made.

A variable-gain output feedback control design methodology

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Moerder, Daniel D.; Broussard, John R.; Taylor, Deborah B.

1989-01-01

A digital control system design technique is developed in which the control system gain matrix varies with the plant operating point parameters. The design technique is obtained by formulating the problem as an optimal stochastic output feedback control law with variable gains. This approach provides a control theory framework within which the operating range of a control law can be significantly extended. Furthermore, the approach avoids the major shortcomings of the conventional gain-scheduling techniques. The optimal variable gain output feedback control problem is solved by embedding the Multi-Configuration Control (MCC) problem, previously solved at ICS. An algorithm to compute the optimal variable gain output feedback control gain matrices is developed. The algorithm is a modified version of the MCC algorithm improved so as to handle the large dimensionality which arises particularly in variable-gain control problems. The design methodology developed is applied to a reconfigurable aircraft control problem. A variable-gain output feedback control problem was formulated to design a flight control law for an AFTI F-16 aircraft which can automatically reconfigure its control strategy to accommodate failures in the horizontal tail control surface. Simulations of the closed-loop reconfigurable system show that the approach produces a control design which can accommodate such failures with relative ease. The technique can be applied to many other problems including sensor failure accommodation, mode switching control laws and super agility.

Ride comfort control in large flexible aircraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Warren, M. E.

1971-01-01

The problem of ameliorating the discomfort of passengers on a large air transport subject to flight disturbances is examined. The longitudinal dynamics of the aircraft, including effects of body flexing, are developed in terms of linear, constant coefficient differential equations in state variables. A cost functional, penalizing the rigid body displacements and flexure accelerations over the surface of the aircraft is formulated as a quadratic form. The resulting control problem, to minimize the cost subject to the state equation constraints, is of a class whose solutions are well known. The feedback gains for the optimal controller are calculated digitally, and the resulting autopilot is simulated on an analog computer and its performance evaluated.

Guidance and Control strategies for aerospace vehicles

NASA Technical Reports Server (NTRS)

Hibey, J. L.; Naidu, D. S.; Charalambous, C. D.

1989-01-01

A neighboring optimal guidance scheme was devised for a nonlinear dynamic system with stochastic inputs and perfect measurements as applicable to fuel optimal control of an aeroassisted orbital transfer vehicle. For the deterministic nonlinear dynamic system describing the atmospheric maneuver, a nominal trajectory was determined. Then, a neighboring, optimal guidance scheme was obtained for open loop and closed loop control configurations. Taking modelling uncertainties into account, a linear, stochastic, neighboring optimal guidance scheme was devised. Finally, the optimal trajectory was approximated as the sum of the deterministic nominal trajectory and the stochastic neighboring optimal solution. Numerical results are presented for a typical vehicle. A fuel-optimal control problem in aeroassisted noncoplanar orbital transfer is also addressed. The equations of motion for the atmospheric maneuver are nonlinear and the optimal (nominal) trajectory and control are obtained. In order to follow the nominal trajectory under actual conditions, a neighboring optimum guidance scheme is designed using linear quadratic regulator theory for onboard real-time implementation. One of the state variables is used as the independent variable in reference to the time. The weighting matrices in the performance index are chosen by a combination of a heuristic method and an optimal modal approach. The necessary feedback control law is obtained in order to minimize the deviations from the nominal conditions.

Just-in-Time Feedback in Diet and Physical Activity Interventions: Systematic Review and Practical Design Framework.

PubMed

Schembre, Susan M; Liao, Yue; Robertson, Michael C; Dunton, Genevieve Fridlund; Kerr, Jacqueline; Haffey, Meghan E; Burnett, Taylor; Basen-Engquist, Karen; Hicklen, Rachel S

2018-03-22

The integration of body-worn sensors with mobile devices presents a tremendous opportunity to improve just-in-time behavioral interventions by enhancing bidirectional communication between investigators and their participants. This approach can be used to deliver supportive feedback at critical moments to optimize the attainment of health behavior goals. The goals of this systematic review were to summarize data on the content characteristics of feedback messaging used in diet and physical activity (PA) interventions and to develop a practical framework for designing just-in-time feedback for behavioral interventions. Interventions that included just-in-time feedback on PA, sedentary behavior, or dietary intake were eligible for inclusion. Feedback content and efficacy data were synthesized descriptively. The review included 31 studies (15/31, 48%, targeting PA or sedentary behavior only; 13/31, 42%, targeting diet and PA; and 3/31, 10%, targeting diet only). All studies used just-in-time feedback, 30 (97%, 30/31) used personalized feedback, and 24 (78%, 24/31) used goal-oriented feedback, but only 5 (16%, 5/31) used actionable feedback. Of the 9 studies that tested the efficacy of providing feedback to promote behavior change, 4 reported significant improvements in health behavior. In 3 of these 4 studies, feedback was continuously available, goal-oriented, or actionable. Feedback that was continuously available, personalized, and actionable relative to a known behavioral objective was prominent in intervention studies with significant behavior change outcomes. Future research should determine whether all or some of these characteristics are needed to optimize the effect of feedback in just-in-time interventions. ©Susan M Schembre, Yue Liao, Michael C Robertson, Genevieve Fridlund Dunton, Jacqueline Kerr, Meghan E Haffey, Taylor Burnett, Karen Basen-Engquist, Rachel S Hicklen. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.03.2018.

Microelectromechanical accelerometer with resonance-cancelling control circuit including an idle state

DOEpatents

Chu, Dahlon D.; Thelen, Jr., Donald C.; Campbell, David V.

2001-01-01

A digital feedback control circuit is disclosed for use in an accelerometer (e.g. a microelectromechanical accelerometer). The digital feedback control circuit, which periodically re-centers a proof mass in response to a sensed acceleration, is based on a sigma-delta (.SIGMA..DELTA.) configuration that includes a notch filter (e.g. a digital switched-capacitor filter) for rejecting signals due to mechanical resonances of the proof mass and further includes a comparator (e.g. a three-level comparator). The comparator generates one of three possible feedback states, with two of the feedback states acting to re-center the proof mass when that is needed, and with a third feedback state being an "idle" state which does not act to move the proof mass when no re-centering is needed. Additionally, the digital feedback control system includes an auto-zero trim capability for calibration of the accelerometer for accurate sensing of acceleration. The digital feedback control circuit can be fabricated using complementary metal-oxide semiconductor (CMOS) technology, bi-CMOS technology or bipolar technology and used in single- and dual-proof-mass accelerometers.

Development of a bunch-by-bunch longitudinal feedback system with a wide dynamic range for the HIGS facility

NASA Astrophysics Data System (ADS)

Wu, W. Z.; Kim, Y.; Li, J. Y.; Teytelman, D.; Busch, M.; Wang, P.; Swift, G.; Park, I. S.; Ko, I. S.; Wu, Y. K.

2011-03-01

Electron beam coupled-bunch instabilities can limit and degrade the performance of storage ring based light sources. A longitudinal feedback system has been developed for the Duke storage ring to suppress multi-bunch beam instabilities which prevent stable, high-current operation of the storage ring based free-electron lasers (FELs) and an FEL driven Compton gamma source, the high intensity gamma-ray source (HIGS) at Duke University. In this work, we report the development of a state-of-the-art second generation longitudinal feedback system which employs a field programmable gate array (FPGA) based processor, and a broadband, high shunt-impedance kicker cavity. With two inputs and two outputs, the kicker cavity was designed with a resonant frequency of 937 MHz, a bandwidth of 97 MHz, and a shunt impedance of 1530 Ω. We also developed an S-matrix based technique to fully characterize the performance of the kicker cavity in the cold test. This longitudinal feedback system has been commissioned and optimized to stabilize high-current electron beams with a wide range of electron beam energies (250 MeV to 1.15 GeV) and a number of electron beam bunch modes, including the single-bunch mode and all possible symmetric bunch modes. This feedback system has become a critical instrument to ensure stable, high-flux operation of HIGS to produce nearly monochromatic, highly polarized Compton gamma-ray beams.

Nonlinear dynamics of autonomous vehicles with limits on acceleration

NASA Astrophysics Data System (ADS)

Davis, L. C.

2014-07-01

The stability of autonomous vehicle platoons with limits on acceleration and deceleration is determined. If the leading-vehicle acceleration remains within the limits, all vehicles in the platoon remain within the limits when the relative-velocity feedback coefficient is equal to the headway time constant [k=1/h]. Furthermore, if the sensitivity α>1/h, no collisions occur. String stability for small perturbations is assumed and the initial condition is taken as the equilibrium state. Other values of k and α that give stability with no collisions are found from simulations. For vehicles with non-negligible mechanical response, simulations indicate that the acceleration-feedback-control gain might have to be dynamically adjusted to obtain optimal performance as the response time changes with engine speed. Stability is demonstrated for some perturbations that cause initial acceleration or deceleration greater than the limits, yet do not cause collisions.

Influence of measurement error on Maxwell's demon

NASA Astrophysics Data System (ADS)

Sørdal, Vegard; Bergli, Joakim; Galperin, Y. M.

2017-06-01

In any general cycle of measurement, feedback, and erasure, the measurement will reduce the entropy of the system when information about the state is obtained, while erasure, according to Landauer's principle, is accompanied by a corresponding increase in entropy due to the compression of logical and physical phase space. The total process can in principle be fully reversible. A measurement error reduces the information obtained and the entropy decrease in the system. The erasure still gives the same increase in entropy, and the total process is irreversible. Another consequence of measurement error is that a bad feedback is applied, which further increases the entropy production if the proper protocol adapted to the expected error rate is not applied. We consider the effect of measurement error on a realistic single-electron box Szilard engine, and we find the optimal protocol for the cycle as a function of the desired power P and error ɛ .

Feedback control for unsteady flow and its application to the stochastic Burgers equation

NASA Technical Reports Server (NTRS)

Choi, Haecheon; Temam, Roger; Moin, Parviz; Kim, John

1993-01-01

The study applies mathematical methods of control theory to the problem of control of fluid flow with the long-range objective of developing effective methods for the control of turbulent flows. Model problems are employed through the formalism and language of control theory to present the procedure of how to cast the problem of controlling turbulence into a problem in optimal control theory. Methods of calculus of variations through the adjoint state and gradient algorithms are used to present a suboptimal control and feedback procedure for stationary and time-dependent problems. Two types of controls are investigated: distributed and boundary controls. Several cases of both controls are numerically simulated to investigate the performances of the control algorithm. Most cases considered show significant reductions of the costs to be minimized. The dependence of the control algorithm on the time-descretization method is discussed.

Computational methods for optimal linear-quadratic compensators for infinite dimensional discrete-time systems

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Rosen, I. G.

1986-01-01

An abstract approximation theory and computational methods are developed for the determination of optimal linear-quadratic feedback control, observers and compensators for infinite dimensional discrete-time systems. Particular attention is paid to systems whose open-loop dynamics are described by semigroups of operators on Hilbert spaces. The approach taken is based on the finite dimensional approximation of the infinite dimensional operator Riccati equations which characterize the optimal feedback control and observer gains. Theoretical convergence results are presented and discussed. Numerical results for an example involving a heat equation with boundary control are presented and used to demonstrate the feasibility of the method.

Investigating the Effects of Multimodal Feedback through Tracking State in Pen-Based Interfaces

ERIC Educational Resources Information Center

Sun, Minghui; Ren, Xiangshi

2011-01-01

A tracking state increases the bandwidth of pen-based interfaces. However, this state is difficult to detect with default visual feedback. This paper reports on two experiments that are designed to evaluate multimodal feedback for pointing tasks (both 1D and 2D) in tracking state. In 1D pointing experiments, results show that there is a…

Qualitative and quantitative feedback in the context of competency-based education.

PubMed

Tekian, Ara; Watling, Christopher J; Roberts, Trudie E; Steinert, Yvonne; Norcini, John

2017-12-01

Research indicates the importance and usefulness of feedback, yet with the shift of medical curricula toward competencies, feedback is not well understood in this context. This paper attempts to identify how feedback fits within a competency-based curriculum. After careful consideration of the literature, the following conclusions are drawn: (1) Because feedback is predicated on assessment, the assessment should be designed to optimize and prevent inaccuracies in feedback; (2) Giving qualitative feedback in the form of a conversation would lend credibility to the feedback, address emotional obstacles and create a context in which feedback is comfortable; (3) Quantitative feedback in the form of individualized data could fulfill the demand for more feedback, help students devise strategies on how to improve, allow students to compare themselves to their peers, recognizing that big data have limitations; and (4) Faculty development needs to incorporate and promote cultural and systems changes with regard to feedback. A better understanding of the role of feedback in competency-based education could result in more efficient learning for students.

Design Criteria for the Future of Flight Controls. Proceedings of the Flight Dynamics Laboratory Flying Qualities and Flight Control Symposium 2-5 March 1982.

DTIC Science & Technology

1982-07-01

robustness of the closed-loop system as compared to state feedback. The observer theory of Luenberger specifies the conditions that must be satisfied for...No. ID-17SI-F-l, October 1963. 8. Rynaski, E. G. and Whitbeck, R. F.: "The Theory and Application of Linear Optimal Control," Calspan Report No. IH...pilots tend to control them open-loop. Frequencies much beyond 10 rad/sec are generally beyond pilots’ control capability. Control theory indicates a need

State feedback controller design for the synchronization of Boolean networks with time delays

NASA Astrophysics Data System (ADS)

Li, Fangfei; Li, Jianning; Shen, Lijuan

2018-01-01

State feedback control design to make the response Boolean network synchronize with the drive Boolean network is far from being solved in the literature. Motivated by this, this paper studies the feedback control design for the complete synchronization of two coupled Boolean networks with time delays. A necessary condition for the existence of a state feedback controller is derived first. Then the feedback control design procedure for the complete synchronization of two coupled Boolean networks is provided based on the necessary condition. Finally, an example is given to illustrate the proposed design procedure.

Wind turbine power tracking using an improved multimodel quadratic approach.

PubMed

Khezami, Nadhira; Benhadj Braiek, Naceur; Guillaud, Xavier

2010-07-01

In this paper, an improved multimodel optimal quadratic control structure for variable speed, pitch regulated wind turbines (operating at high wind speeds) is proposed in order to integrate high levels of wind power to actively provide a primary reserve for frequency control. On the basis of the nonlinear model of the studied plant, and taking into account the wind speed fluctuations, and the electrical power variation, a multimodel linear description is derived for the wind turbine, and is used for the synthesis of an optimal control law involving a state feedback, an integral action and an output reference model. This new control structure allows a rapid transition of the wind turbine generated power between different desired set values. This electrical power tracking is ensured with a high-performance behavior for all other state variables: turbine and generator rotational speeds and mechanical shaft torque; and smooth and adequate evolution of the control variables. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Regulation of Dynamical Systems to Optimal Solutions of Semidefinite Programs: Algorithms and Applications to AC Optimal Power Flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

2015-07-01

This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the controlmore » of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.« less

Concurrently examining unrealistic absolute and comparative optimism: Temporal shifts, individual-difference and event-specific correlates, and behavioural outcomes.

PubMed

Ruthig, Joelle C; Gamblin, Bradlee W; Jones, Kelly; Vanderzanden, Karen; Kehn, Andre

2017-02-01

Researchers have spent considerable effort examining unrealistic absolute optimism and unrealistic comparative optimism, yet there is a lack of research exploring them concurrently. This longitudinal study repeatedly assessed unrealistic absolute and comparative optimism within a performance context over several months to identify the degree to which they shift as a function of proximity to performance and performance feedback, their associations with global individual difference and event-specific factors, and their link to subsequent behavioural outcomes. Results showed similar shifts in unrealistic absolute and comparative optimism based on proximity to performance and performance feedback. Moreover, increases in both types of unrealistic optimism were associated with better subsequent performance beyond the effect of prior performance. However, several differences were found between the two forms of unrealistic optimism in their associations with global individual difference factors and event-specific factors, highlighting the distinctiveness of the two constructs. © 2016 The British Psychological Society.

Factorization and the synthesis of optimal feedback kernels for differential-delay systems

NASA Technical Reports Server (NTRS)

Milman, Mark M.; Scheid, Robert E.

1987-01-01

A combination of ideas from the theories of operator Riccati equations and Volterra factorizations leads to the derivation of a novel, relatively simple set of hyperbolic equations which characterize the optimal feedback kernel for the finite-time regulator problem for autonomous differential-delay systems. Analysis of these equations elucidates the underlying structure of the feedback kernel and leads to the development of fast and accurate numerical methods for its computation. Unlike traditional formulations based on the operator Riccati equation, the gain is characterized by means of classical solutions of the derived set of equations. This leads to the development of approximation schemes which are analogous to what has been accomplished for systems of ordinary differential equations with given initial conditions.

Peer Feedback on College Students' Writing: Exploring the Relation between Students' Ability Match, Feedback Quality and Essay Performance

ERIC Educational Resources Information Center

Huisman, Bart; Saab, Nadira; van Driel, Jan; van den Broek, Paul

2017-01-01

There does not appear to be consensus on how to optimally match students during the peer feedback process: with same-ability peers (homogeneously) or different-ability peers (heterogeneously). In fact, there appears to be no empirical evidence that either homogeneous or heterogeneous student matching has any direct effect on writing performance.…

Structuring the Peer Assessment Process: A Multilevel Approach for the Impact on Product Improvement and Peer Feedback Quality

ERIC Educational Resources Information Center

Gielen, M.; De Wever, B.

2015-01-01

In order to optimize students' peer feedback processes, this study investigates how an instructional intervention in the peer assessment process can have a beneficial effect on students' performance in a wiki environment in first-year higher education. The main aim was to study the effect of integrating a peer feedback template with a varying…

The Effect of Combination of Video Feedback and Audience Feedback on Social Anxiety: Preliminary Findings.

PubMed

Chen, Junwen; Mak, Rebecca; Fujita, Satoko

2015-09-01

Although video feedback (VF) is shown to improve appraisals of social performance in socially anxious individuals, its impact on state anxiety during a social situation is mixed. The current study investigated the effect of combined video feedback and audience feedback (AF) on self-perceptions of performance and bodily sensations as well as state anxiety pertaining to a speech task. Forty-one socially anxious students were randomly allocated to combined video feedback with audience feedback (VF + AF), video feedback only (VF), audience feedback only (AF), or a control condition. Following a 3-min speech, participants in the VF + AF, VF, and AF conditions watched the videotape of their speech with cognitive preparation in the presence of three confederates who served as audience, and/or received feedback from the confederates, while the control group watched their videotaped speech without cognitive preparation. Both VF + AF and AF conditions improved distorted appraisal of performance and bodily sensations as well as state anxiety. The clinical implications of these findings are discussed. © The Author(s) 2015.

A complexity basis for phenomenology: How information states at criticality offer a new approach to understanding experience of self, being and time.

PubMed

Hankey, Alex

2015-12-01

In the late 19th century Husserl studied our internal sense of time passing, maintaining that its deep connections into experience represent prima facie evidence for it as the basis for all investigations in the sciences: Phenomenology was born. Merleau-Ponty focused on perception pointing out that any theory of experience must accord with established aspects of biology i.e. be embodied. Recent analyses suggest that theories of experience require non-reductive, integrative information, together with a specific property connecting them to experience. Here we elucidate a new class of information states with just such properties found at the loci of control of complex biological systems, including nervous systems. Complexity biology concerns states satisfying self-organized criticality. Such states are located at critical instabilities, commonly observed in biological systems, and thought to maximize information diversity and processing, and hence to optimize regulation. Major results for biology follow: why organisms have unusually low entropies; and why they are not merely mechanical. Criticality states form singular self-observing systems, which reduce wave packets by processes of perfect self-observation associated with feedback gain g = 1. Analysis of their information properties leads to identification of a new kind of information state with high levels of internal coherence, and feedback loops integrated into their structure. The major idea presented here is that the integrated feedback loops are responsible for our 'sense of self', and also the feeling of continuity in our sense of time passing. Long-range internal correlations guarantee a unique kind of non-reductive, integrative information structure enabling such states to naturally support phenomenal experience. Being founded in complexity biology, they are 'embodied'; they also fulfill the statement that 'The self is a process', a singular process. High internal correlations and René Thom-style catastrophes support non-digital forms of information, gestalt cognition, and information transfer via quantum teleportation. Criticality in complexity biology can 'embody' cognitive states supporting gestalts, and phenomenology's senses of 'self,' time passing, existence and being. Copyright © 2015. Published by Elsevier Ltd.

Strategy for pH control and pH feedback-controlled substrate feeding for high-level production of L-tryptophan by Escherichia coli.

PubMed

Cheng, Li-Kun; Wang, Jian; Xu, Qing-Yang; Zhao, Chun-Guang; Shen, Zhi-Qiang; Xie, Xi-Xian; Chen, Ning

2013-05-01

Optimum production of L-tryptophan by Escherichia coli depends on pH. Here, we established conditions for optimizing the production of L-tryptophan. The optimum pH range was 6.5-7.2, and pH was controlled using a three-stage strategy [pH 6.5 (0-12 h), pH 6.8 (12-24 h), and pH 7.2 (24-38 h)]. Specifically, ammonium hydroxide was used to adjust pH during the initial 24 h, and potassium hydroxide and ammonium hydroxide (1:2, v/v) were used to adjust pH during 24-38 h. Under these conditions, NH4 (+) and K(+) concentrations were kept below the threshold for inhibiting L-tryptophan production. Optimization was also accomplished using ratios (v/v) of glucose to alkali solutions equal to 4:1 (5-24 h) and 6:1 (24-38 h). The concentration of glucose and the pH were controlled by adjusting the pH automatically. Applying a pH-feedback feeding method, the steady-state concentration of glucose was maintained at approximately 0.2 ± 0.02 g/l, and acetic acid accumulated to a concentration of 1.15 ± 0.03 g/l, and the plasmid stability was 98 ± 0.5 %. The final, optimized concentration of L-tryptophan was 43.65 ± 0.29 g/l from 52.43 ± 0.38 g/l dry cell weight.

Piecewise linear approximation for hereditary control problems

NASA Technical Reports Server (NTRS)

Propst, Georg

1987-01-01

Finite dimensional approximations are presented for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems when a quadratic cost integral has to be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in case the cost integral ranges over a finite time interval as well as in the case it ranges over an infinite time interval. The arguments in the latter case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense. This feature is established using a vector-component stability criterion in the state space R(n) x L(2) and the favorable eigenvalue behavior of the piecewise linear approximations.

A computational algorithm for spacecraft control and momentum management

NASA Technical Reports Server (NTRS)

Dzielski, John; Bergmann, Edward; Paradiso, Joseph

1990-01-01

Developments in the area of nonlinear control theory have shown how coordinate changes in the state and input spaces of a dynamical system can be used to transform certain nonlinear differential equations into equivalent linear equations. These techniques are applied to the control of a spacecraft equipped with momentum exchange devices. An optimal control problem is formulated that incorporates a nonlinear spacecraft model. An algorithm is developed for solving the optimization problem using feedback linearization to transform to an equivalent problem involving a linear dynamical constraint and a functional approximation technique to solve for the linear dynamics in terms of the control. The original problem is transformed into an unconstrained nonlinear quadratic program that yields an approximate solution to the original problem. Two examples are presented to illustrate the results.

Reinforcement Learning Multi-Agent Modeling of Decision-Making Agents for the Study of Transboundary Surface Water Conflicts with Application to the Syr Darya River Basin

NASA Astrophysics Data System (ADS)

Riegels, N.; Siegfried, T.; Pereira Cardenal, S. J.; Jensen, R. A.; Bauer-Gottwein, P.

2008-12-01

In most economics--driven approaches to optimizing water use at the river basin scale, the system is modelled deterministically with the goal of maximizing overall benefits. However, actual operation and allocation decisions must be made under hydrologic and economic uncertainty. In addition, river basins often cross political boundaries, and different states may not be motivated to cooperate so as to maximize basin- scale benefits. Even within states, competing agents such as irrigation districts, municipal water agencies, and large industrial users may not have incentives to cooperate to realize efficiency gains identified in basin- level studies. More traditional simulation--optimization approaches assume pre-commitment by individual agents and stakeholders and unconditional compliance on each side. While this can help determine attainable gains and tradeoffs from efficient management, such hardwired policies do not account for dynamic feedback between agents themselves or between agents and their environments (e.g. due to climate change etc.). In reality however, we are dealing with an out-of-equilibrium multi-agent system, where there is neither global knowledge nor global control, but rather continuous strategic interaction between decision making agents. Based on the theory of stochastic games, we present a computational framework that allows for studying the dynamic feedback between decision--making agents themselves and an inherently uncertain environment in a spatially and temporally distributed manner. Agents with decision-making control over water allocation such as countries, irrigation districts, and municipalities are represented by reinforcement learning agents and coupled to a detailed hydrologic--economic model. This approach emphasizes learning by agents from their continuous interaction with other agents and the environment. It provides a convenient framework for the solution of the problem of dynamic decision-making in a mixed cooperative / non-cooperative environment with which different institutional setups and incentive systems can be studied so to identify reasonable ways to reach desirable, Pareto--optimal allocation outcomes. Preliminary results from an application to the Syr Darya river basin in Central Asia will be presented and discussed. The Syr Darya River is a classic example of a transboundary river basin in which basin-wide efficiency gains identified in optimization studies have not been sufficient to induce cooperative management of the river by the riparian states.

A feedback control for the advanced launch system

NASA Technical Reports Server (NTRS)

Seywald, Hans; Cliff, Eugene M.

1991-01-01

A robust feedback algorithm is presented for a near-minimum-fuel ascent of a two-stage launch vehicle operating in the equatorial plane. The development of the algorithm is based on the ideas of neighboring optimal control and can be derived into three phases. In phase 1, the formalism of optimal control is employed to calculate fuel-optimal ascent trajectories for a simple point-mass model. In phase 2, these trajectories are used to numerically calculate gain functions of time for the control(s), the total flight time, and possibly, for other variables of interest. In phase 3, these gains are used to determine feedback expressions for the controls associated with a more realistic model of a launch vehicle. With the Advanced Launch System in mind, all calculations are performed on a two-stage vehicle with fixed thrust history, but this restriction is by no means important for the approach taken. Performance and robustness of the algorithm is found to be excellent.

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

PubMed

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

The Unresponsive Partner: Roles of Social Status, Auditory Feedback, and Animacy in Coordination of Joint Music Performance

PubMed Central

Demos, Alexander P.; Carter, Daniel J.; Wanderley, Marcelo M.; Palmer, Caroline

2017-01-01

We examined temporal synchronization in joint music performance to determine how social status, auditory feedback, and animacy influence interpersonal coordination. A partner’s coordination can be bidirectional (partners adapt to the actions of one another) or unidirectional (one partner adapts). According to the dynamical systems framework, bidirectional coordination should be the optimal (preferred) state during live performance. To test this, 24 skilled pianists each performed with a confederate while their coordination was measured by the asynchrony in their tone onsets. To promote social balance, half of the participants were told the confederate was a fellow participant – an equal social status. To promote social imbalance, the other half was told the confederate was an experimenter – an unequal social status. In all conditions, the confederate’s arm and finger movements were occluded from the participant’s view to allow manipulation of animacy of the confederate’s performances (live or recorded). Unbeknownst to the participants, half of the confederate’s performances were replaced with pre-recordings, forcing the participant into unidirectional coordination during performance. The other half of the confederate’s performances were live, which permitted bidirectional coordination between performers. In a final manipulation, both performers heard the auditory feedback from one or both of the performers’ parts removed at unpredictable times to disrupt their performance. Consistently larger asynchronies were observed in performances of unidirectional (recorded) than bidirectional (live) performances across all conditions. Participants who were told the confederate was an experimenter reported their synchrony as more successful than when the partner was introduced as a fellow participant. Finally, asynchronies increased as auditory feedback was removed; removal of the confederate’s part hurt coordination more than removal of the participant’s part in live performances. Consistent with the assumption that bidirectional coupling yields optimal coordination, an unresponsive partner requires the other member to do all the adapting for the pair to stay together. PMID:28261123

Can You Hear That Peak? Utilization of Auditory and Visual Feedback at Peak Limb Velocity.

PubMed

Loria, Tristan; de Grosbois, John; Tremblay, Luc

2016-09-01

At rest, the central nervous system combines and integrates multisensory cues to yield an optimal percept. When engaging in action, the relative weighing of sensory modalities has been shown to be altered. Because the timing of peak velocity is the critical moment in some goal-directed movements (e.g., overarm throwing), the current study sought to test whether visual and auditory cues are optimally integrated at that specific kinematic marker when it is the critical part of the trajectory. Participants performed an upper-limb movement in which they were required to reach their peak limb velocity when the right index finger intersected a virtual target (i.e., a flinging movement). Brief auditory, visual, or audiovisual feedback (i.e., 20 ms in duration) was provided to participants at peak limb velocity. Performance was assessed primarily through the resultant position of peak limb velocity and the variability of that position. Relative to when no feedback was provided, auditory feedback significantly reduced the resultant endpoint variability of the finger position at peak limb velocity. However, no such reductions were found for the visual or audiovisual feedback conditions. Further, providing both auditory and visual cues concurrently also failed to yield the theoretically predicted improvements in endpoint variability. Overall, the central nervous system can make significant use of an auditory cue but may not optimally integrate a visual and auditory cue at peak limb velocity, when peak velocity is the critical part of the trajectory.

People efficiently explore the solution space of the computationally intractable traveling salesman problem to find near-optimal tours.

PubMed

Acuña, Daniel E; Parada, Víctor

2010-07-29

Humans need to solve computationally intractable problems such as visual search, categorization, and simultaneous learning and acting, yet an increasing body of evidence suggests that their solutions to instantiations of these problems are near optimal. Computational complexity advances an explanation to this apparent paradox: (1) only a small portion of instances of such problems are actually hard, and (2) successful heuristics exploit structural properties of the typical instance to selectively improve parts that are likely to be sub-optimal. We hypothesize that these two ideas largely account for the good performance of humans on computationally hard problems. We tested part of this hypothesis by studying the solutions of 28 participants to 28 instances of the Euclidean Traveling Salesman Problem (TSP). Participants were provided feedback on the cost of their solutions and were allowed unlimited solution attempts (trials). We found a significant improvement between the first and last trials and that solutions are significantly different from random tours that follow the convex hull and do not have self-crossings. More importantly, we found that participants modified their current better solutions in such a way that edges belonging to the optimal solution ("good" edges) were significantly more likely to stay than other edges ("bad" edges), a hallmark of structural exploitation. We found, however, that more trials harmed the participants' ability to tell good from bad edges, suggesting that after too many trials the participants "ran out of ideas." In sum, we provide the first demonstration of significant performance improvement on the TSP under repetition and feedback and evidence that human problem-solving may exploit the structure of hard problems paralleling behavior of state-of-the-art heuristics.

People Efficiently Explore the Solution Space of the Computationally Intractable Traveling Salesman Problem to Find Near-Optimal Tours

PubMed Central

Acuña, Daniel E.; Parada, Víctor

2010-01-01

Humans need to solve computationally intractable problems such as visual search, categorization, and simultaneous learning and acting, yet an increasing body of evidence suggests that their solutions to instantiations of these problems are near optimal. Computational complexity advances an explanation to this apparent paradox: (1) only a small portion of instances of such problems are actually hard, and (2) successful heuristics exploit structural properties of the typical instance to selectively improve parts that are likely to be sub-optimal. We hypothesize that these two ideas largely account for the good performance of humans on computationally hard problems. We tested part of this hypothesis by studying the solutions of 28 participants to 28 instances of the Euclidean Traveling Salesman Problem (TSP). Participants were provided feedback on the cost of their solutions and were allowed unlimited solution attempts (trials). We found a significant improvement between the first and last trials and that solutions are significantly different from random tours that follow the convex hull and do not have self-crossings. More importantly, we found that participants modified their current better solutions in such a way that edges belonging to the optimal solution (“good” edges) were significantly more likely to stay than other edges (“bad” edges), a hallmark of structural exploitation. We found, however, that more trials harmed the participants' ability to tell good from bad edges, suggesting that after too many trials the participants “ran out of ideas.” In sum, we provide the first demonstration of significant performance improvement on the TSP under repetition and feedback and evidence that human problem-solving may exploit the structure of hard problems paralleling behavior of state-of-the-art heuristics. PMID:20686597

A Comparative Analysis of CMUT Receiving Architectures for the Design Optimization of Integrated Transceiver Front Ends.

PubMed

Sautto, Marco; Savoia, Alessandro Stuart; Quaglia, Fabio; Caliano, Giosue; Mazzanti, Andrea

2017-05-01

A formal comparison between fundamental RX amplifier configurations for capacitive micromachined ultrasonic transducers (CMUTs) is proposed in this paper. The impact on both RX and the pulse-echo frequency response and on the output SNR is thoroughly analyzed and discussed. It is shown that the resistive-feedback amplifier yields a bandpass RX frequency response, while both open-loop voltage and capacitive-feedback amplifiers exhibit a low-pass frequency response. For a given power dissipation, it is formally proved that a capacitive-feedback amplifier provides a remarkable SNR improvement against the commonly adopted resistive feedback stage, achieved at the expense of a reduced pulse-echo center frequency, making its use convenient in low-frequency and midfrequency ultrasound imaging applications. The advantage mostly comes from a much lower noise contributed by the active devices, especially with low- Q , broadband transducers. The results of the analysis are applied to the design of a CMUT front end in BIPOLAR-CMOS-DMOS Silicon-on-Insulator technology operating at 10-MHz center frequency. It comprises a low-power RX amplifier, a high-voltage Transmission/Reception switch, and a 100-V TX driver. Extensive electrical characterization, pulse-echo measurements, and imaging results are shown. Compared with previously reported CMUT front ends, this transceiver demonstrates the highest dynamic range and state-of-the-art noise performance with an RX amplifier power dissipation of 1 mW.

A real-time laser feedback control method for the three-wave laser source used in the polarimeter-interferometer diagnostic on Joint-TEXT tokamak

NASA Astrophysics Data System (ADS)

Xiong, C. Y.; Chen, J.; Li, Q.; Liu, Y.; Gao, L.

2014-12-01

A three-wave laser polarimeter-interferometer, equipped with three independent far-infrared laser sources, has been developed on Joint-TEXT (J-TEXT) tokamak. The diagnostic system is capable of high-resolution temporal and phase measurement of the Faraday angle and line-integrated density. However, for long-term operation (>10 min), the free-running lasers can lead to large drifts of the intermediate frequencies (˜100-˜500 kHz/10 min) and decay of laser power (˜10%-˜20%/10 min), which act to degrade diagnostic performance. In addition, these effects lead to increased maintenance cost and limit measurement applicability to long pulse/steady state experiments. To solve this problem, a real-time feedback control method of the laser source is proposed. By accurately controlling the length of each laser cavity, both the intermediate frequencies and laser power can be simultaneously controlled: the intermediate frequencies are controlled according to the pre-set values, while the laser powers are maintained at an optimal level. Based on this approach, a real-time feedback control system has been developed and applied on J-TEXT polarimeter-interferometer. Long-term (theoretically no time limit) feedback of intermediate frequencies (maximum change less than ±12 kHz) and laser powers (maximum relative power change less than ±7%) has been successfully achieved.

A real-time laser feedback control method for the three-wave laser source used in the polarimeter-interferometer diagnostic on Joint-TEXT tokamak.

PubMed

Xiong, C Y; Chen, J; Li, Q; Liu, Y; Gao, L

2014-12-01

A three-wave laser polarimeter-interferometer, equipped with three independent far-infrared laser sources, has been developed on Joint-TEXT (J-TEXT) tokamak. The diagnostic system is capable of high-resolution temporal and phase measurement of the Faraday angle and line-integrated density. However, for long-term operation (>10 min), the free-running lasers can lead to large drifts of the intermediate frequencies (∼100-∼500 kHz/10 min) and decay of laser power (∼10%-∼20%/10 min), which act to degrade diagnostic performance. In addition, these effects lead to increased maintenance cost and limit measurement applicability to long pulse/steady state experiments. To solve this problem, a real-time feedback control method of the laser source is proposed. By accurately controlling the length of each laser cavity, both the intermediate frequencies and laser power can be simultaneously controlled: the intermediate frequencies are controlled according to the pre-set values, while the laser powers are maintained at an optimal level. Based on this approach, a real-time feedback control system has been developed and applied on J-TEXT polarimeter-interferometer. Long-term (theoretically no time limit) feedback of intermediate frequencies (maximum change less than ±12 kHz) and laser powers (maximum relative power change less than ±7%) has been successfully achieved.

TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.

PubMed

Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald

2018-01-01

Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.

Stabilization of business cycles of finance agents using nonlinear optimal control

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Ghosh, T.; Sarno, D.

2017-11-01

Stabilization of the business cycles of interconnected finance agents is performed with the use of a new nonlinear optimal control method. First, the dynamics of the interacting finance agents and of the associated business cycles is described by a modeled of coupled nonlinear oscillators. Next, this dynamic model undergoes approximate linearization round a temporary operating point which is defined by the present value of the system's state vector and the last value of the control inputs vector that was exerted on it. The linearization procedure is based on Taylor series expansion of the dynamic model and on the computation of Jacobian matrices. The modelling error, which is due to the truncation of higher-order terms in the Taylor series expansion is considered as a disturbance which is compensated by the robustness of the control loop. Next, for the linearized model of the interacting finance agents, an H-infinity feedback controller is designed. The computation of the feedback control gain requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. Through Lyapunov stability analysis it is proven that the control scheme satisfies an H-infinity tracking performance criterion, which signifies elevated robustness against modelling uncertainty and external perturbations. Moreover, under moderate conditions the global asymptotic stability features of the control loop are proven.

Combined Audience and Video Feedback With Cognitive Review Improves State Anxiety and Self-Perceptions During Speech Tasks in Socially Anxious Individuals.

PubMed

Chen, Junwen; McLean, Jordan E; Kemps, Eva

2018-03-01

This study investigated the effects of combined audience feedback with video feedback plus cognitive preparation, and cognitive review (enabling deeper processing of feedback) on state anxiety and self-perceptions including perception of performance and perceived probability of negative evaluation in socially anxious individuals during a speech performance. One hundred and forty socially anxious students were randomly assigned to four conditions: Cognitive Preparation + Video Feedback + Audience Feedback + Cognitive Review (CP+VF+AF+CR), Cognitive Preparation + Video Feedback + Cognitive Review (CP+VF+CR), Cognitive Preparation + Video Feedback only (CP+VF), and Control. They were asked to deliver two impromptu speeches that were evaluated by confederates. Participants' levels of anxiety and self-perceptions pertaining to the speech task were assessed before and after feedback, and after the second speech. Compared to participants in the other conditions, participants in the CP+VF+AF+CR condition reported a significant decrease in their state anxiety and perceived probability of negative evaluation scores, and a significant increase in their positive perception of speech performance from before to after the feedback. These effects generalized to the second speech. Our results suggest that adding audience feedback to video feedback plus cognitive preparation and cognitive review may improve the effects of existing video feedback procedures in reducing anxiety symptoms and distorted self-representations in socially anxious individuals. Copyright © 2017. Published by Elsevier Ltd.

A dynamic feedback-control toll pricing methodology : a case study on Interstate 95 managed lanes.

DOT National Transportation Integrated Search

2013-06-01

Recently, congestion pricing emerged as a cost-effective and efficient strategy to mitigate the congestion problem on freeways. This study develops a feedback-control based dynamic toll approach to formulate and solve for optimal tolls. The study com...

Vibration suppression for large scale adaptive truss structures using direct output feedback control

NASA Technical Reports Server (NTRS)

Lu, Lyan-Ywan; Utku, Senol; Wada, Ben K.

1993-01-01

In this article, the vibration control of adaptive truss structures, where the control actuation is provided by length adjustable active members, is formulated as a direct output feedback control problem. A control method named Model Truncated Output Feedback (MTOF) is presented. The method allows the control feedback gain to be determined in a decoupled and truncated modal space in which only the critical vibration modes are retained. The on-board computation required by MTOF is minimal; thus, the method is favorable for the applications of vibration control of large scale structures. The truncation of the modal space inevitably introduces spillover effect during the control process. In this article, the effect is quantified in terms of active member locations, and it is shown that the optimal placement of active members, which minimizes the spillover effect (and thus, maximizes the control performance) can be sought. The problem of optimally selecting the locations of active members is also treated.

The effect of haptic guidance and visual feedback on learning a complex tennis task.

PubMed

Marchal-Crespo, Laura; van Raai, Mark; Rauter, Georg; Wolf, Peter; Riener, Robert

2013-11-01

While haptic guidance can improve ongoing performance of a motor task, several studies have found that it ultimately impairs motor learning. However, some recent studies suggest that the haptic demonstration of optimal timing, rather than movement magnitude, enhances learning in subjects trained with haptic guidance. Timing of an action plays a crucial role in the proper accomplishment of many motor skills, such as hitting a moving object (discrete timing task) or learning a velocity profile (time-critical tracking task). The aim of the present study is to evaluate which feedback conditions-visual or haptic guidance-optimize learning of the discrete and continuous elements of a timing task. The experiment consisted in performing a fast tennis forehand stroke in a virtual environment. A tendon-based parallel robot connected to the end of a racket was used to apply haptic guidance during training. In two different experiments, we evaluated which feedback condition was more adequate for learning: (1) a time-dependent discrete task-learning to start a tennis stroke and (2) a tracking task-learning to follow a velocity profile. The effect that the task difficulty and subject's initial skill level have on the selection of the optimal training condition was further evaluated. Results showed that the training condition that maximizes learning of the discrete time-dependent motor task depends on the subjects' initial skill level. Haptic guidance was especially suitable for less-skilled subjects and in especially difficult discrete tasks, while visual feedback seems to benefit more skilled subjects. Additionally, haptic guidance seemed to promote learning in a time-critical tracking task, while visual feedback tended to deteriorate the performance independently of the task difficulty and subjects' initial skill level. Haptic guidance outperformed visual feedback, although additional studies are needed to further analyze the effect of other types of feedback visualization on motor learning of time-critical tasks.

Robust control of flexible space vehicles with minimum structural excitation: On-off pulse control of flexible space vehicles

NASA Technical Reports Server (NTRS)

Wie, Bong; Liu, Qiang

1992-01-01

Both feedback and feedforward control approaches for uncertain dynamical systems (in particular, with uncertainty in structural mode frequency) are investigated. The control objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant uncertainty. Preshaping of an ideal, time optimal control input using a tapped-delay filter is shown to provide a fast settling time with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. It is shown that a properly designed, feedback controller performs well, as compared with a time optimal open loop controller with special preshaping for performance robustness. Also included are two separate papers by the same authors on this subject.

Singular perturbation analysis of AOTV-related trajectory optimization problems

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Bae, Gyoung H.

1990-01-01

The problem of real time guidance and optimal control of Aeroassisted Orbit Transfer Vehicles (AOTV's) was addressed using singular perturbation theory as an underlying method of analysis. Trajectories were optimized with the objective of minimum energy expenditure in the atmospheric phase of the maneuver. Two major problem areas were addressed: optimal reentry, and synergetic plane change with aeroglide. For the reentry problem, several reduced order models were analyzed with the objective of optimal changes in heading with minimum energy loss. It was demonstrated that a further model order reduction to a single state model is possible through the application of singular perturbation theory. The optimal solution for the reduced problem defines an optimal altitude profile dependent on the current energy level of the vehicle. A separate boundary layer analysis is used to account for altitude and flight path angle dynamics, and to obtain lift and bank angle control solutions. By considering alternative approximations to solve the boundary layer problem, three guidance laws were derived, each having an analytic feedback form. The guidance laws were evaluated using a Maneuvering Reentry Research Vehicle model and all three laws were found to be near optimal. For the problem of synergetic plane change with aeroglide, a difficult terminal boundary layer control problem arises which to date is found to be analytically intractable. Thus a predictive/corrective solution was developed to satisfy the terminal constraints on altitude and flight path angle. A composite guidance solution was obtained by combining the optimal reentry solution with the predictive/corrective guidance method. Numerical comparisons with the corresponding optimal trajectory solutions show that the resulting performance is very close to optimal. An attempt was made to obtain numerically optimized trajectories for the case where heating rate is constrained. A first order state variable inequality constraint was imposed on the full order AOTV point mass equations of motion, using a simple aerodynamic heating rate model.

Stochastic Optimization For Water Resources Allocation

NASA Astrophysics Data System (ADS)

Yamout, G.; Hatfield, K.

2003-12-01

For more than 40 years, water resources allocation problems have been addressed using deterministic mathematical optimization. When data uncertainties exist, these methods could lead to solutions that are sub-optimal or even infeasible. While optimization models have been proposed for water resources decision-making under uncertainty, no attempts have been made to address the uncertainties in water allocation problems in an integrated approach. This paper presents an Integrated Dynamic, Multi-stage, Feedback-controlled, Linear, Stochastic, and Distributed parameter optimization approach to solve a problem of water resources allocation. It attempts to capture (1) the conflict caused by competing objectives, (2) environmental degradation produced by resource consumption, and finally (3) the uncertainty and risk generated by the inherently random nature of state and decision parameters involved in such a problem. A theoretical system is defined throughout its different elements. These elements consisting mainly of water resource components and end-users are described in terms of quantity, quality, and present and future associated risks and uncertainties. Models are identified, modified, and interfaced together to constitute an integrated water allocation optimization framework. This effort is a novel approach to confront the water allocation optimization problem while accounting for uncertainties associated with all its elements; thus resulting in a solution that correctly reflects the physical problem in hand.

Reinforcement learning controller design for affine nonlinear discrete-time systems using online approximators.

PubMed

Yang, Qinmin; Jagannathan, Sarangapani

2012-04-01

In this paper, reinforcement learning state- and output-feedback-based adaptive critic controller designs are proposed by using the online approximators (OLAs) for a general multi-input and multioutput affine unknown nonlinear discretetime systems in the presence of bounded disturbances. The proposed controller design has two entities, an action network that is designed to produce optimal signal and a critic network that evaluates the performance of the action network. The critic estimates the cost-to-go function which is tuned online using recursive equations derived from heuristic dynamic programming. Here, neural networks (NNs) are used both for the action and critic whereas any OLAs, such as radial basis functions, splines, fuzzy logic, etc., can be utilized. For the output-feedback counterpart, an additional NN is designated as the observer to estimate the unavailable system states, and thus, separation principle is not required. The NN weight tuning laws for the controller schemes are also derived while ensuring uniform ultimate boundedness of the closed-loop system using Lyapunov theory. Finally, the effectiveness of the two controllers is tested in simulation on a pendulum balancing system and a two-link robotic arm system.

Analytical investigations in aircraft and spacecraft trajectory optimization and optimal guidance

NASA Technical Reports Server (NTRS)

Markopoulos, Nikos; Calise, Anthony J.

1995-01-01

A collection of analytical studies is presented related to unconstrained and constrained aircraft (a/c) energy-state modeling and to spacecraft (s/c) motion under continuous thrust. With regard to a/c unconstrained energy-state modeling, the physical origin of the singular perturbation parameter that accounts for the observed 2-time-scale behavior of a/c during energy climbs is identified and explained. With regard to the constrained energy-state modeling, optimal control problems are studied involving active state-variable inequality constraints. Departing from the practical deficiencies of the control programs for such problems that result from the traditional formulations, a complete reformulation is proposed for these problems which, in contrast to the old formulation, will presumably lead to practically useful controllers that can track an inequality constraint boundary asymptotically, and even in the presence of 2-sided perturbations about it. Finally, with regard to s/c motion under continuous thrust, a thrust program is proposed for which the equations of 2-dimensional motion of a space vehicle in orbit, viewed as a point mass, afford an exact analytic solution. The thrust program arises under the assumption of tangential thrust from the costate system corresponding to minimum-fuel, power-limited, coplanar transfers between two arbitrary conics. The thrust program can be used not only with power-limited propulsion systems, but also with any propulsion system capable of generating continuous thrust of controllable magnitude, and, for propulsion types and classes of transfers for which it is sufficiently optimal the results of this report suggest a method of maneuvering during planetocentric or heliocentric orbital operations, requiring a minimum amount of computation; thus uniquely suitable for real-time feedback guidance implementations.

Flight investigation of rotor/vehicle state feedback

NASA Technical Reports Server (NTRS)

Briczinski, S. J.; Cooper, D. E.

1975-01-01

The feasibility of using control feedback or rotor tip-path-plane motion or body state as a means of altering rotor and fuselage response in a prescribed manner was investigated to determine the practical limitations of in-flight utilization of a digital computer which conditions and shapes rotor flapping and fuselage state information as feedback signals, before routing these signals to the differential servo actuators. The analysis and test of various feedback schemes are discussed. Test results show that a Kalman estimator routine which is based on only the first harmonic contributions of blade flapping yields tip-path-plane coefficients which are adequate for use in feedback systems, at speeds up to 150 kts.

Optimal exploitation strategies for an animal population in a Markovian environment: A theory and an example

USGS Publications Warehouse

Anderson, D.R.

1975-01-01

Optimal exploitation strategies were studied for an animal population in a Markovian (stochastic, serially correlated) environment. This is a general case and encompasses a number of important special cases as simplifications. Extensive empirical data on the Mallard (Anas platyrhynchos) were used as an example of general theory. The number of small ponds on the central breeding grounds was used as an index to the state of the environment. A general mathematical model was formulated to provide a synthesis of the existing literature, estimates of parameters developed from an analysis of data, and hypotheses regarding the specific effect of exploitation on total survival. The literature and analysis of data were inconclusive concerning the effect of exploitation on survival. Therefore, two hypotheses were explored: (1) exploitation mortality represents a largely additive form of mortality, and (2) exploitation mortality is compensatory with other forms of mortality, at least to some threshold level. Models incorporating these two hypotheses were formulated as stochastic dynamic programming models and optimal exploitation strategies were derived numerically on a digital computer. Optimal exploitation strategies were found to exist under the rather general conditions. Direct feedback control was an integral component in the optimal decision-making process. Optimal exploitation was found to be substantially different depending upon the hypothesis regarding the effect of exploitation on the population. If we assume that exploitation is largely an additive force of mortality in Mallards, then optimal exploitation decisions are a convex function of the size of the breeding population and a linear or slight concave function of the environmental conditions. Under the hypothesis of compensatory mortality forces, optimal exploitation decisions are approximately linearly related to the size of the Mallard breeding population. Dynamic programming is suggested as a very general formulation for realistic solutions to the general optimal exploitation problem. The concepts of state vectors and stage transformations are completely general. Populations can be modeled stochastically and the objective function can include extra-biological factors. The optimal level of exploitation in year t must be based on the observed size of the population and the state of the environment in year t unless the dynamics of the population, the state of the environment, and the result of the exploitation decisions are completely deterministic. Exploitation based on an average harvest, or harvest rate, or designed to maintain a constant breeding population size is inefficient.

Optimal Power Flow Pursuit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Simonetto, Andrea

This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow (OPF) problems. Particularly, the controllers update the power setpoints based on voltage measurements as well as given (time-varying) OPF targets, and entail elementary operations implementable onto low-cost microcontrollers that accompany power-electronics interfaces of gateways and inverters. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. Convergence and OPF-target tracking capabilities of the controllers are analytically established. Overall,more » the proposed method allows to bypass traditional hierarchical setups where feedback control and optimization operate at distinct time scales, and to enable real-time optimization of distribution systems.« less

Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics.

PubMed

Cheng, Sen; Sabes, Philip N

2007-04-01

The sensorimotor calibration of visually guided reaching changes on a trial-to-trial basis in response to random shifts in the visual feedback of the hand. We show that a simple linear dynamical system is sufficient to model the dynamics of this adaptive process. In this model, an internal variable represents the current state of sensorimotor calibration. Changes in this state are driven by error feedback signals, which consist of the visually perceived reach error, the artificial shift in visual feedback, or both. Subjects correct for > or =20% of the error observed on each movement, despite being unaware of the visual shift. The state of adaptation is also driven by internal dynamics, consisting of a decay back to a baseline state and a "state noise" process. State noise includes any source of variability that directly affects the state of adaptation, such as variability in sensory feedback processing, the computations that drive learning, or the maintenance of the state. This noise is accumulated in the state across trials, creating temporal correlations in the sequence of reach errors. These correlations allow us to distinguish state noise from sensorimotor performance noise, which arises independently on each trial from random fluctuations in the sensorimotor pathway. We show that these two noise sources contribute comparably to the overall magnitude of movement variability. Finally, the dynamics of adaptation measured with random feedback shifts generalizes to the case of constant feedback shifts, allowing for a direct comparison of our results with more traditional blocked-exposure experiments.

Topology optimization of embedded piezoelectric actuators considering control spillover effects

NASA Astrophysics Data System (ADS)

Gonçalves, Juliano F.; De Leon, Daniel M.; Perondi, Eduardo A.

2017-02-01

This article addresses the problem of active structural vibration control by means of embedded piezoelectric actuators. The topology optimization method using the solid isotropic material with penalization (SIMP) approach is employed in this work to find the optimum design of actuators taken into account the control spillover effects. A coupled finite element model of the structure is derived assuming a two-phase material and this structural model is written into the state-space representation. The proposed optimization formulation aims to determine the distribution of piezoelectric material which maximizes the controllability for a given vibration mode. The undesirable effects of the feedback control on the residual modes are limited by including a spillover constraint term containing the residual controllability Gramian eigenvalues. The optimization of the shape and placement of the conventionally embedded piezoelectric actuators are performed using a Sequential Linear Programming (SLP) algorithm. Numerical examples are presented considering the control of the bending vibration modes for a cantilever and a fixed beam. A Linear-Quadratic Regulator (LQR) is synthesized for each case of controlled structure in order to compare the influence of the additional constraint.

A method for obtaining reduced-order control laws for high-order systems using optimization techniques

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Newsom, J. R.; Abel, I.

1981-01-01

A method of synthesizing reduced-order optimal feedback control laws for a high-order system is developed. A nonlinear programming algorithm is employed to search for the control law design variables that minimize a performance index defined by a weighted sum of mean-square steady-state responses and control inputs. An analogy with the linear quadractic Gaussian solution is utilized to select a set of design variables and their initial values. To improve the stability margins of the system, an input-noise adjustment procedure is used in the design algorithm. The method is applied to the synthesis of an active flutter-suppression control law for a wind tunnel model of an aeroelastic wing. The reduced-order controller is compared with the corresponding full-order controller and found to provide nearly optimal performance. The performance of the present method appeared to be superior to that of two other control law order-reduction methods. It is concluded that by using the present algorithm, nearly optimal low-order control laws with good stability margins can be synthesized.

On Approaching the Ultimate Limits of Communication Using a Photon-Counting Detector

NASA Technical Reports Server (NTRS)

Erkmen, Baris I.; Moision, Bruce E.; Dolinar, Samuel J.; Birnbaum, Kevin M.; Divsalar, Dariush

2012-01-01

Coherent states achieve the Holevo capacity of a pure-loss channel when paired with an optimal measurement, but a physical realization of this measurement scheme is as of yet unknown, and it is also likely to be of high complexity. In this paper, we focus on the photon-counting measurement and study the photon and dimensional efficiencies attainable with modulations over classical- and nonclassical-state alphabets. We analyze two binary modulation architectures that improve upon the dimensional versus photon efficiency tradeoff achievable with the state-of-the-art coherent-state on-off keying modulation. We show that at high photon efficiency these architectures achieve an efficiency tradeoff that differs from the best possible tradeoff--determined by the Holevo capacity--by only a constant factor. The first architecture we analyze is a coherent-state transmitter that relies on feedback from the receiver to control the transmitted energy. The second architecture uses a single-photon number-state source.

A Test of Genetic Algorithms in Relevance Feedback.

ERIC Educational Resources Information Center

Lopez-Pujalte, Cristina; Guerrero Bote, Vicente P.; Moya Anegon, Felix de

2002-01-01

Discussion of information retrieval, query optimization techniques, and relevance feedback focuses on genetic algorithms, which are derived from artificial intelligence techniques. Describes an evaluation of different genetic algorithms using a residual collection method and compares results with the Ide dec-hi method (Salton and Buckley, 1990…

Analytically exploiting noise correlations inside the feedback loop to improve locked-oscillator performance.

PubMed

Sastrawan, J; Jones, C; Akhalwaya, I; Uys, H; Biercuk, M J

2016-08-01

We introduce concepts from optimal estimation to the stabilization of precision frequency standards limited by noisy local oscillators. We develop a theoretical framework casting various measures for frequency standard variance in terms of frequency-domain transfer functions, capturing the effects of feedback stabilization via a time series of Ramsey measurements. Using this framework, we introduce an optimized hybrid predictive feedforward measurement protocol that employs results from multiple past measurements and transfer-function-based calculations of measurement covariance to improve the accuracy of corrections within the feedback loop. In the presence of common non-Markovian noise processes these measurements will be correlated in a calculable manner, providing a means to capture the stochastic evolution of the local oscillator frequency during the measurement cycle. We present analytic calculations and numerical simulations of oscillator performance under competing feedback schemes and demonstrate benefits in both correction accuracy and long-term oscillator stability using hybrid feedforward. Simulations verify that in the presence of uncompensated dead time and noise with significant spectral weight near the inverse cycle time predictive feedforward outperforms traditional feedback, providing a path towards developing a class of stabilization software routines for frequency standards limited by noisy local oscillators.

Integrated Control Using the SOFFT Control Structure

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1996-01-01

The need for integrated/constrained control systems has become clearer as advanced aircraft introduced new coupled subsystems such as new propulsion subsystems with thrust vectoring and new aerodynamic designs. In this study, we develop an integrated control design methodology which accomodates constraints among subsystem variables while using the Stochastic Optimal Feedforward/Feedback Control Technique (SOFFT) thus maintaining all the advantages of the SOFFT approach. The Integrated SOFFT Control methodology uses a centralized feedforward control and a constrained feedback control law. The control thus takes advantage of the known coupling among the subsystems while maintaining the identity of subsystems for validation purposes and the simplicity of the feedback law to understand the system response in complicated nonlinear scenarios. The Variable-Gain Output Feedback Control methodology (including constant gain output feedback) is extended to accommodate equality constraints. A gain computation algorithm is developed. The designer can set the cross-gains between two variables or subsystems to zero or another value and optimize the remaining gains subject to the constraint. An integrated control law is designed for a modified F-15 SMTD aircraft model with coupled airframe and propulsion subsystems using the Integrated SOFFT Control methodology to produce a set of desired flying qualities.

Design and evaluation of a Stochastic Optimal Feed-forward and Feedback Technology (SOFFT) flight control architecture

NASA Technical Reports Server (NTRS)

Ostroff, Aaron J.; Proffitt, Melissa S.

1994-01-01

This paper describes the design and evaluation of a stochastic optimal feed-forward and feedback technology (SOFFT) control architecture with emphasis on the feed-forward controller design. The SOFFT approach allows the designer to independently design the feed-forward and feedback controllers to meet separate objectives and then integrate the two controllers. The feed-forward controller has been integrated with an existing high-angle-of-attack (high-alpha) feedback controller. The feed-forward controller includes a variable command model with parameters selected to satisfy level 1 flying qualities with a high-alpha adjustment to achieve desired agility guidelines, a nonlinear interpolation approach that scales entire matrices for approximation of the plant model, and equations for calculating feed-forward gains developed for perfect plant-model tracking. The SOFFT design was applied to a nonlinear batch simulation model of an F/A-18 aircraft modified for thrust vectoring. Simulation results show that agility guidelines are met and that the SOFFT controller filters undesired pilot-induced frequencies more effectively during a tracking task than a flight controller that has the same feedback control law but does not have the SOFFT feed-forward control.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems.

PubMed

Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N

2006-12-01

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Closed-Loop Optimal Control Implementations for Space Applications

DTIC Science & Technology

2016-12-01

analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to feedback on the...through the analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to...information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering

CONDUIT: A New Multidisciplinary Integration Environment for Flight Control Development

NASA Technical Reports Server (NTRS)

Tischler, Mark B.; Colbourne, Jason D.; Morel, Mark R.; Biezad, Daniel J.; Levine, William S.; Moldoveanu, Veronica

1997-01-01

A state-of-the-art computational facility for aircraft flight control design, evaluation, and integration called CONDUIT (Control Designer's Unified Interface) has been developed. This paper describes the CONDUIT tool and case study applications to complex rotary- and fixed-wing fly-by-wire flight control problems. Control system analysis and design optimization methods are presented, including definition of design specifications and system models within CONDUIT, and the multi-objective function optimization (CONSOL-OPTCAD) used to tune the selected design parameters. Design examples are based on flight test programs for which extensive data are available for validation. CONDUIT is used to analyze baseline control laws against pertinent military handling qualities and control system specifications. In both case studies, CONDUIT successfully exploits trade-offs between forward loop and feedback dynamics to significantly improve the expected handling, qualities and minimize the required actuator authority. The CONDUIT system provides a new environment for integrated control system analysis and design, and has potential for significantly reducing the time and cost of control system flight test optimization.

Optimizing Experimental Design for Comparing Models of Brain Function

PubMed Central

Daunizeau, Jean; Preuschoff, Kerstin; Friston, Karl; Stephan, Klaas

2011-01-01

This article presents the first attempt to formalize the optimization of experimental design with the aim of comparing models of brain function based on neuroimaging data. We demonstrate our approach in the context of Dynamic Causal Modelling (DCM), which relates experimental manipulations to observed network dynamics (via hidden neuronal states) and provides an inference framework for selecting among candidate models. Here, we show how to optimize the sensitivity of model selection by choosing among experimental designs according to their respective model selection accuracy. Using Bayesian decision theory, we (i) derive the Laplace-Chernoff risk for model selection, (ii) disclose its relationship with classical design optimality criteria and (iii) assess its sensitivity to basic modelling assumptions. We then evaluate the approach when identifying brain networks using DCM. Monte-Carlo simulations and empirical analyses of fMRI data from a simple bimanual motor task in humans serve to demonstrate the relationship between network identification and the optimal experimental design. For example, we show that deciding whether there is a feedback connection requires shorter epoch durations, relative to asking whether there is experimentally induced change in a connection that is known to be present. Finally, we discuss limitations and potential extensions of this work. PMID:22125485

Feedback: Implications for Further Research and Study.

ERIC Educational Resources Information Center

Nishikawa, Sue S.

This report reviews current literature on feedback and suggests practical implications of feedback research for educators. A definition of feedback is offered, and past definitions in prior research are noted. An analysis of the current state of knowledge of feedback discusses the historical development of feedback theory and suggests that…

Multivariable control of the Space Shuttle Remote Manipulator System using linearization by state feedback. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gettman, Chang-Ching LO

1993-01-01

This thesis develops and demonstrates an approach to nonlinear control system design using linearization by state feedback. The design provides improved transient response behavior allowing faster maneuvering of payloads by the SRMS. Modeling uncertainty is accounted for by using a second feedback loop designed around the feedback linearized dynamics. A classical feedback loop is developed to provide the easy implementation required for the relatively small on board computers. Feedback linearization also allows the use of higher bandwidth model based compensation in the outer loop, since it helps maintain stability in the presence of the nonlinearities typically neglected in model based designs.

Realizing actual feedback control of complex network

NASA Astrophysics Data System (ADS)

Tu, Chengyi; Cheng, Yuhua

2014-06-01

In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems.

Feedback control for fuel-optimal descents using singular perturbation techniques

NASA Technical Reports Server (NTRS)

Price, D. B.

1984-01-01

In response to rising fuel costs and reduced profit margins for the airline companies, the optimization of the paths flown by transport aircraft has been considered. It was found that application of optimal control theory to the considered problem can result in savings in fuel, time, and direct operating costs. The best solution to the aircraft trajectory problem is an onboard real-time feedback control law. The present paper presents a technique which shows promise of becoming a part of a complete solution. The application of singular perturbation techniques to the problem is discussed, taking into account the benefits and some problems associated with them. A different technique for handling the descent part of a trajectory is also discussed.

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression

NASA Technical Reports Server (NTRS)

Miller, Christopher

2017-01-01

These slide sets describe the OCLA formulation and associated algorithms as a set of new technologies in the first practical application of load limiting flight control utilizing load feedback as a primary control measurement. Slide set one describes Experiment Development and slide set two describes Flight-Test Performance.

Advances in adaptive control theory: Gradient- and derivative-free approaches

NASA Astrophysics Data System (ADS)

Yucelen, Tansel

In this dissertation, we present new approaches to improve standard designs in adaptive control theory, and novel adaptive control architectures. We first present a novel Kalman filter based approach for approximately enforcing a linear constraint in standard adaptive control design. One application is that this leads to alternative forms for well known modification terms such as e-modification. In addition, it leads to smaller tracking errors without incurring significant oscillations in the system response and without requiring high modification gain. We derive alternative forms of e- and adaptive loop recovery (ALR-) modifications. Next, we show how to use Kalman filter optimization to derive a novel adaptation law. This results in an optimization-based time-varying adaptation gain that reduces the need for adaptation gain tuning. A second major contribution of this dissertation is the development of a novel derivative-free, delayed weight update law for adaptive control. The assumption of constant unknown ideal weights is relaxed to the existence of time-varying weights, such that fast and possibly discontinuous variation in weights are allowed. This approach is particulary advantageous for applications to systems that can undergo a sudden change in dynamics, such as might be due to reconfiguration, deployment of a payload, docking, or structural damage, and for rejection of external disturbance processes. As a third and final contribution, we develop a novel approach for extending all the methods developed in this dissertation to the case of output feedback. The approach is developed only for the case of derivative-free adaptive control, and the extension of the other approaches developed previously for the state feedback case to output feedback is left as a future research topic. The proposed approaches of this dissertation are illustrated in both simulation and flight test.

Coexisting synchronous and asynchronous states in locally coupled array of oscillators by partial self-feedback control

NASA Astrophysics Data System (ADS)

Bera, Bidesh K.; Ghosh, Dibakar; Parmananda, Punit; Osipov, G. V.; Dana, Syamal K.

2017-07-01

We report the emergence of coexisting synchronous and asynchronous subpopulations of oscillators in one dimensional arrays of identical oscillators by applying a self-feedback control. When a self-feedback is applied to a subpopulation of the array, similar to chimera states, it splits into two/more sub-subpopulations coexisting in coherent and incoherent states for a range of self-feedback strength. By tuning the coupling between the nearest neighbors and the amount of self-feedback in the perturbed subpopulation, the size of the coherent and the incoherent sub-subpopulations in the array can be controlled, although the exact size of them is unpredictable. We present numerical evidence using the Landau-Stuart system and the Kuramoto-Sakaguchi phase model.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease

NASA Astrophysics Data System (ADS)

Gorzelic, P.; Schiff, S. J.; Sinha, A.

2013-04-01

Objective. To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). Approach. A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. Main Results. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Significance. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease.

PubMed

Gorzelic, P; Schiff, S J; Sinha, A

2013-04-01

To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning

PubMed Central

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach. PMID:24616695

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning.

PubMed

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach.

Wing box transonic-flutter suppression using piezoelectric self-sensing actuators attached to skin

NASA Astrophysics Data System (ADS)

Otiefy, R. A. H.; Negm, H. M.

2010-12-01

The main objective of this research is to study the capability of piezoelectric (PZT) self-sensing actuators to suppress the transonic wing box flutter, which is a flow-structure interaction phenomenon. The unsteady general frequency modified transonic small disturbance (TSD) equation is used to model the transonic flow about the wing. The wing box structure and piezoelectric actuators are modeled using the equivalent plate method, which is based on the first order shear deformation plate theory (FSDPT). The piezoelectric actuators are bonded to the skin. The optimal electromechanical coupling conditions between the piezoelectric actuators and the wing are collected from previous work. Three main different control strategies, a linear quadratic Gaussian (LQG) which combines the linear quadratic regulator (LQR) with the Kalman filter estimator (KFE), an optimal static output feedback (SOF), and a classic feedback controller (CFC), are studied and compared. The optimum actuator and sensor locations are determined using the norm of feedback control gains (NFCG) and norm of Kalman filter estimator gains (NKFEG) respectively. A genetic algorithm (GA) optimization technique is used to calculate the controller and estimator parameters to achieve a target response.

ERD-based online brain-machine interfaces (BMI) in the context of neurorehabilitation: optimizing BMI learning and performance.

PubMed

Soekadar, Surjo R; Witkowski, Matthias; Mellinger, Jürgen; Ramos, Ander; Birbaumer, Niels; Cohen, Leonardo G

2011-10-01

Event-related desynchronization (ERD) of sensori-motor rhythms (SMR) can be used for online brain-machine interface (BMI) control, but yields challenges related to the stability of ERD and feedback strategy to optimize BMI learning.Here, we compared two approaches to this challenge in 20 right-handed healthy subjects (HS, five sessions each, S1-S5) and four stroke patients (SP, 15 sessions each, S1-S15). ERD was recorded from a 275-sensor MEG system. During daily training,motor imagery-induced ERD led to visual and proprioceptive feedback delivered through an orthotic device attached to the subjects' hand and fingers. Group A trained with a heterogeneous reference value (RV) for ERD detection with binary feedback and Group B with a homogenous RV and graded feedback (10 HS and 2 SP in each group). HS in Group B showed better BMI performance than Group A (p < 0.001) and improved BMI control from S1 to S5 (p = 0.012) while Group A did not. In spite of the small n, SP in Group B showed a trend for a higher BMI performance (p = 0.06) and learning was significantly better (p < 0.05). Using a homogeneous RV and graded feedback led to improved modulation of ipsilesional activity resulting in superior BMI learning relative to use of a heterogeneous RV and binary feedback.

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

People adopt optimal policies in simple decision-making, after practice and guidance.

PubMed

Evans, Nathan J; Brown, Scott D

2017-04-01

Organisms making repeated simple decisions are faced with a tradeoff between urgent and cautious strategies. While animals can adopt a statistically optimal policy for this tradeoff, findings about human decision-makers have been mixed. Some studies have shown that people can optimize this "speed-accuracy tradeoff", while others have identified a systematic bias towards excessive caution. These issues have driven theoretical development and spurred debate about the nature of human decision-making. We investigated a potential resolution to the debate, based on two factors that routinely differ between human and animal studies of decision-making: the effects of practice, and of longer-term feedback. Our study replicated the finding that most people, by default, are overly cautious. When given both practice and detailed feedback, people moved rapidly towards the optimal policy, with many participants reaching optimality with less than 1 h of practice. Our findings have theoretical implications for cognitive and neural models of simple decision-making, as well as methodological implications.

Focusing of light through turbid media by curve fitting optimization

NASA Astrophysics Data System (ADS)

Gong, Changmei; Wu, Tengfei; Liu, Jietao; Li, Huijuan; Shao, Xiaopeng; Zhang, Jianqi

2016-12-01

The construction of wavefront phase plays a critical role in focusing light through turbid media. We introduce the curve fitting algorithm (CFA) into the feedback control procedure for wavefront optimization. Unlike the existing continuous sequential algorithm (CSA), the CFA locates the optimal phase by fitting a curve to the measured signals. Simulation results show that, similar to the genetic algorithm (GA), the proposed CFA technique is far less susceptible to the experimental noise than the CSA. Furthermore, only three measurements of feedback signals are enough for CFA to fit the optimal phase while obtaining a higher focal intensity than the CSA and the GA, dramatically shortening the optimization time by a factor of 3 compared with the CSA and the GA. The proposed CFA approach can be applied to enhance the focus intensity and boost the focusing speed in the fields of biological imaging, particle trapping, laser therapy, and so on, and might help to focus light through dynamic turbid media.

Adaptive critic designs for optimal control of uncertain nonlinear systems with unmatched interconnections.

PubMed

Yang, Xiong; He, Haibo

2018-05-26

In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiple burn fuel-optimal orbit transfers: Numerical trajectory computation and neighboring optimal feedback guidance

NASA Technical Reports Server (NTRS)

Chuang, C.-H.; Goodson, Troy D.; Ledsinger, Laura A.

1995-01-01

This report describes current work in the numerical computation of multiple burn, fuel-optimal orbit transfers and presents an analysis of the second variation for extremal multiple burn orbital transfers as well as a discussion of a guidance scheme which may be implemented for such transfers. The discussion of numerical computation focuses on the use of multivariate interpolation to aid the computation in the numerical optimization. The second variation analysis includes the development of the conditions for the examination of both fixed and free final time transfers. Evaluations for fixed final time are presented for extremal one, two, and three burn solutions of the first variation. The free final time problem is considered for an extremal two burn solution. In addition, corresponding changes of the second variation formulation over thrust arcs and coast arcs are included. The guidance scheme discussed is an implicit scheme which implements a neighboring optimal feedback guidance strategy to calculate both thrust direction and thrust on-off times.

An Optimization Framework for Driver Feedback Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malikopoulos, Andreas; Aguilar, Juan P.

2013-01-01

Modern vehicles have sophisticated electronic control units that can control engine operation with discretion to balance fuel economy, emissions, and power. These control units are designed for specific driving conditions (e.g., different speed profiles for highway and city driving). However, individual driving styles are different and rarely match the specific driving conditions for which the units were designed. In the research reported here, we investigate driving-style factors that have a major impact on fuel economy and construct an optimization framework to optimize individual driving styles with respect to these driving factors. In this context, we construct a set of polynomialmore » metamodels to reflect the responses produced in fuel economy by changing the driving factors. Then, we compare the optimized driving styles to the original driving styles and evaluate the effectiveness of the optimization framework. Finally, we use this proposed framework to develop a real-time feedback system, including visual instructions, to enable drivers to alter their driving styles in response to actual driving conditions to improve fuel efficiency.« less

Analysis of the faster-than-Nyquist optimal linear multicarrier system

NASA Astrophysics Data System (ADS)

Marquet, Alexandre; Siclet, Cyrille; Roque, Damien

2017-02-01

Faster-than-Nyquist signalization enables a better spectral efficiency at the expense of an increased computational complexity. Regarding multicarrier communications, previous work mainly relied on the study of non-linear systems exploiting coding and/or equalization techniques, with no particular optimization of the linear part of the system. In this article, we analyze the performance of the optimal linear multicarrier system when used together with non-linear receiving structures (iterative decoding and direct feedback equalization), or in a standalone fashion. We also investigate the limits of the normality assumption of the interference, used for implementing such non-linear systems. The use of this optimal linear system leads to a closed-form expression of the bit-error probability that can be used to predict the performance and help the design of coded systems. Our work also highlights the great performance/complexity trade-off offered by decision feedback equalization in a faster-than-Nyquist context. xml:lang="fr"

Optimal Control-Based Adaptive NN Design for a Class of Nonlinear Discrete-Time Block-Triangular Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2016-11-01

In this paper, we propose an optimal control scheme-based adaptive neural network design for a class of unknown nonlinear discrete-time systems. The controlled systems are in a block-triangular multi-input-multi-output pure-feedback structure, i.e., there are both state and input couplings and nonaffine functions to be included in every equation of each subsystem. The design objective is to provide a control scheme, which not only guarantees the stability of the systems, but also achieves optimal control performance. The main contribution of this paper is that it is for the first time to achieve the optimal performance for such a class of systems. Owing to the interactions among subsystems, making an optimal control signal is a difficult task. The design ideas are that: 1) the systems are transformed into an output predictor form; 2) for the output predictor, the ideal control signal and the strategic utility function can be approximated by using an action network and a critic network, respectively; and 3) an optimal control signal is constructed with the weight update rules to be designed based on a gradient descent method. The stability of the systems can be proved based on the difference Lyapunov method. Finally, a numerical simulation is given to illustrate the performance of the proposed scheme.

Smart building temperature control using occupant feedback

NASA Astrophysics Data System (ADS)

Gupta, Santosh K.

This work was motivated by the problem of computing optimal commonly-agreeable thermal settings in spaces with multiple occupants. In this work we propose algorithms that take into account each occupant's preferences along with the thermal correlations between different zones in a building, to arrive at optimal thermal settings for all zones of the building in a coordinated manner. In the first part of this work we incorporate active occupant feedback to minimize aggregate user discomfort and total energy cost. User feedback is used to estimate the users comfort range, taking into account possible inaccuracies in the feedback. The control algorithm takes the energy cost into account, trading it off optimally with the aggregate user discomfort. A lumped heat transfer model based on thermal resistance and capacitance is used to model a multi-zone building. We provide a stability analysis and establish convergence of the proposed solution to a desired temperature that minimizes the sum of energy cost and aggregate user discomfort. However, for convergence to the optimal, sufficient separation between the user feedback frequency and the dynamics of the system is necessary; otherwise, the user feedback provided do not correctly reflect the effect of current control input value on user discomfort. The algorithm is further extended using singular perturbation theory to determine the minimum time between successive user feedback solicitations. Under sufficient time scale separation, we establish convergence of the proposed solution. Simulation study and experimental runs on the Watervliet based test facility demonstrates performance of the algorithm. In the second part we develop a consensus algorithm for attaining a common temperature set-point that is agreeable to all occupants of a zone in a typical multi-occupant space. The information on the comfort range functions is indeed held privately by each occupant. Using occupant differentiated dynamically adjusted prices as feedback signals, we propose a distributed solution, which ensures that a consensus is attained among all occupants upon convergence, irrespective of their temperature preferences being in coherence or conflicting. Occupants are only assumed to be rational, in that they choose their own temperature set-points so as to minimize their individual energy cost plus discomfort. We use Alternating Direction Method of Multipliers ( ADMM) to solve our consensus problem. We further establish the convergence of the proposed algorithm to the optimal thermal set point values that minimize the sum of the energy cost and the aggregate discomfort of all occupants in a multi-zone building. For simulating our consensus algorithm we use realistic building parameters based on the Watervliet test facility. The simulation study based on real world building parameters establish the validity of our theoretical model and provide insights on the dynamics of the system with a mobile user population. In the third part we present a game-theoretic (auction) mechanism, that requires occupants to "purchase" their individualized comfort levels beyond what is provided by default by the building operator. The comfort pricing policy, derived as an extension of Vickrey-Clarke-Groves (VCG) pricing, ensures incentive-compatibility of the mechanism, i.e., an occupant acting in self-interest cannot benefit from declaring their comfort function untruthfully, irrespective of the choices made by other occupants. The declared (or estimated) occupant comfort ranges (functions) are then utilized by the building operator---along with the energy cost information---to set the environment controls to optimally balance the aggregate discomfort of the occupants and the energy cost of the building operator. We use realistic building model and parameters based on our test facility to demonstrate the convergence of the actual temperatures in different zones to the desired temperatures, and provide insight to the pricing structure necessary for truthful comfort feedback from the occupants. Finally, we present an end-to-end framework designed for enabling occupant feedback collection and incorporating the feedback data towards energy efficient operation of a building. We have designed a mobile application that occupants can use on their smart phones to provide their thermal preference feedback. When relaying the occupant feedback to the central server the mobile application also uses indoor localization techniques to tie the occupant preference to their current thermal zone. Texas Instruments sensortags are used for real time zonal temperature readings. The mobile application relays the occupant preference along with the location to a central server that also hosts our learning algorithm to learn the environment and using occupant feedback calculates the optimal temperature set point. The entire process is triggered upon change of occupancy, environmental conditions, and or occupant preference. The learning algorithm is scheduled to run at regular intervals to respond dynamically to environmental and occupancy changes. We describe results from experimental studies in two different settings: a single family residential home setting and in a university based laboratory space setting. (Abstract shortened by UMI.).

Nonlinear time-series-based adaptive control applications

NASA Technical Reports Server (NTRS)

Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.

1991-01-01

A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.

Feedback-Driven Dynamic Invariant Discovery

NASA Technical Reports Server (NTRS)

Zhang, Lingming; Yang, Guowei; Rungta, Neha S.; Person, Suzette; Khurshid, Sarfraz

2014-01-01

Program invariants can help software developers identify program properties that must be preserved as the software evolves, however, formulating correct invariants can be challenging. In this work, we introduce iDiscovery, a technique which leverages symbolic execution to improve the quality of dynamically discovered invariants computed by Daikon. Candidate invariants generated by Daikon are synthesized into assertions and instrumented onto the program. The instrumented code is executed symbolically to generate new test cases that are fed back to Daikon to help further re ne the set of candidate invariants. This feedback loop is executed until a x-point is reached. To mitigate the cost of symbolic execution, we present optimizations to prune the symbolic state space and to reduce the complexity of the generated path conditions. We also leverage recent advances in constraint solution reuse techniques to avoid computing results for the same constraints across iterations. Experimental results show that iDiscovery converges to a set of higher quality invariants compared to the initial set of candidate invariants in a small number of iterations.

Canonical formalism for modelling and control of rigid body dynamics.

PubMed

Gurfil, P

2005-12-01

This paper develops a new paradigm for stabilization of rigid-body dynamics. The state-space model is formulated using canonical elements, known as the Serret-Andoyer (SA) variables, thus far scarcely used for engineering applications. The main feature of the SA formalism is the reduction of the dynamics via the underlying symmetry stemming from conservation of angular momentum and rotational kinetic energy. The controllability of the system model is examined using the notion of accessibility, and is shown to be accessible from all points. Based on the accessibility proof, two nonlinear asymptotic feedback stabilizers are developed: a damping feedback is designed based on the Jurdjevic-Quinn method, and a Hamiltonian controller is derived by using the Hamiltonian as a natural Lyapunov function for the closed-loop dynamics. It is shown that the Hamiltonian control is both passive and inverse optimal with respect to a meaningful performance index. The performance of the new controllers is examined and compared using simulations of realistic scenarios from the satellite attitude dynamics field.

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

NASA Astrophysics Data System (ADS)

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-10-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

On the interaction structure of linear multi-input feedback control systems. M.S. Thesis; [problem solving, lattices (mathematics)

NASA Technical Reports Server (NTRS)

Wong, P. K.

1975-01-01

The closely-related problems of designing reliable feedback stabilization strategy and coordinating decentralized feedbacks are considered. Two approaches are taken. A geometric characterization of the structure of control interaction (and its dual) was first attempted and a concept of structural homomorphism developed based on the idea of 'similarity' of interaction pattern. The idea of finding classes of individual feedback maps that do not 'interfere' with the stabilizing action of each other was developed by identifying the structural properties of nondestabilizing and LQ-optimal feedback maps. Some known stability properties of LQ-feedback were generalized and some partial solutions were provided to the reliable stabilization and decentralized feedback coordination problems. A concept of coordination parametrization was introduced, and a scheme for classifying different modes of decentralization (information, control law computation, on-line control implementation) in control systems was developed.

Marginally perceptible outcome feedback, motor learning and implicit processes.

PubMed

Masters, Rich S W; Maxwell, Jon P; Eves, Frank F

2009-09-01

Participants struck 500 golf balls to a concealed target. Outcome feedback was presented at the subjective or objective threshold of awareness of each participant or at a supraliminal threshold. Participants who received fully perceptible (supraliminal) feedback learned to strike the ball onto the target, as did participants who received feedback that was only marginally perceptible (subjective threshold). Participants who received feedback that was not perceptible (objective threshold) showed no learning. Upon transfer to a condition in which the target was unconcealed, performance increased in both the subjective and the objective threshold condition, but decreased in the supraliminal condition. In all three conditions, participants reported minimal declarative knowledge of their movements, suggesting that deliberate hypothesis testing about how best to move in order to perform the motor task successfully was disrupted by the impoverished disposition of the visual outcome feedback. It was concluded that sub-optimally perceptible visual feedback evokes implicit processes.

Finite-time state feedback stabilisation of stochastic high-order nonlinear feedforward systems

NASA Astrophysics Data System (ADS)

Xie, Xue-Jun; Zhang, Xing-Hui; Zhang, Kemei

2016-07-01

This paper studies the finite-time state feedback stabilisation of stochastic high-order nonlinear feedforward systems. Based on the stochastic Lyapunov theorem on finite-time stability, by using the homogeneous domination method, the adding one power integrator and sign function method, constructing a ? Lyapunov function and verifying the existence and uniqueness of solution, a continuous state feedback controller is designed to guarantee the closed-loop system finite-time stable in probability.

Analytical guidance law development for aerocapture at Mars

NASA Technical Reports Server (NTRS)

Calise, A. J.

1992-01-01

During the first part of this reporting period research has concentrated on performing a detailed evaluation, to zero order, of the guidance algorithm developed in the first period taking the numerical approach developed in the third period. A zero order matched asymptotic expansion (MAE) solution that closely satisfies a set of 6 implicit equations in 6 unknowns to an accuracy of 10(exp -10), was evaluated. Guidance law implementation entails treating the current state as a new initial state and repetitively solving the MAE problem to obtain the feedback controls. A zero order guided solution was evaluated and compared with optimal solution that was obtained by numerical methods. Numerical experience shows that the zero order guided solution is close to optimal solution, and that the zero order MAE outer solution plays a critical role in accounting for the variations in Loh's term near the exit phase of the maneuver. However, the deficiency that remains in several of the critical variables indicates the need for a first order correction. During the second part of this period, methods for computing a first order correction were explored.

Facilitating Real-Time Observation of, and Peer Discussion and Feedback about, Practice in Writing Classrooms

ERIC Educational Resources Information Center

Parr, Judy M.; Hawe, Eleanor

2017-01-01

This study investigates conditions designed to optimize learning where professionals utilize the expertise and support of one another. It describes a research--practice collaboration to enhance teacher knowledge and practice through peer observation of, and feedback about, classroom practice in writing. A collaboratively designed observation…

78 FR 37783 - Proposed Information Collection; Comment Request; Generic Clearance for Internet Nonprobability...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-24

... design of a survey or a release of a Census Bureau data dissemination product with a feedback mechanism... encompass both methodological and subject matter research questions that can be tested on a medium-scale... comments to determine optimal interface designs and to obtain feedback from respondents. For the initial...

Attentive Facework during Instructional Feedback: Key to Perceiving Mentorship and an Optimal Learning Environment

ERIC Educational Resources Information Center

Kerssen-Griep, Jeff; Trees, April R.; Hess, Jon A.

2008-01-01

This study investigated how the face threat mitigation students received from their teachers during feedback influenced their judgments about mentored relationships with their teachers and the supportiveness of the classroom learning environment. Public speaking students (N=345) at three universities completed an online survey about the speech…

Quadcopter Path Following Control Design Using Output Feedback with Command Generator Tracker LOS Based At Square Path

NASA Astrophysics Data System (ADS)

Nugraha, A. T.; Agustinah, T.

2018-01-01

Quadcopter an unstable system, underactuated and nonlinear in quadcopter control research developments become an important focus of attention. In this study, following the path control method for position on the X and Y axis, used structure-Generator Tracker Command (CGT) is tested. Attitude control and position feedback quadcopter is compared using the optimal output. The addition of the H∞ performance optimal output feedback control is used to maintain the stability and robustness of quadcopter. Iterative numerical techniques Linear Matrix Inequality (LMI) is used to find the gain controller. The following path control problems is solved using the method of LQ regulators with output feedback. Simulations show that the control system can follow the paths that have been defined in the form of a reference signal square shape. The result of the simulation suggest that the method which used can bring the yaw angle at the expected value algorithm. Quadcopter can do automatically following path with cross track error mean X=0.5 m and Y=0.2 m.

On fully three-dimensional resistive wall mode and feedback stabilization computationsa)

NASA Astrophysics Data System (ADS)

Strumberger, E.; Merkel, P.; Sempf, M.; Günter, S.

2008-05-01

Resistive walls, located close to the plasma boundary, reduce the growth rates of external kink modes to resistive time scales. For such slowly growing resistive wall modes, the stabilization by an active feedback system becomes feasible. The fully three-dimensional stability code STARWALL, and the feedback optimization code OPTIM have been developed [P. Merkel and M. Sempf, 21st IAEA Fusion Energy Conference 2006, Chengdu, China (International Atomic Energy Agency, Vienna, 2006, paper TH/P3-8] to compute the growth rates of resistive wall modes in the presence of nonaxisymmetric, multiply connected wall structures and to model the active feedback stabilization of these modes. In order to demonstrate the capabilities of the codes and to study the effect of the toroidal mode coupling caused by multiply connected wall structures, the codes are applied to test equilibria using the resistive wall structures currently under debate for ITER [M. Shimada et al., Nucl. Fusion 47, S1 (2007)] and ASDEX Upgrade [W. Köppendörfer et al., Proceedings of the 16th Symposium on Fusion Technology, London, 1990 (Elsevier, Amsterdam, 1991), Vol. 1, p. 208].

On fully three-dimensional resistive wall mode and feedback stabilization computations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strumberger, E.; Merkel, P.; Sempf, M.

2008-05-15

Resistive walls, located close to the plasma boundary, reduce the growth rates of external kink modes to resistive time scales. For such slowly growing resistive wall modes, the stabilization by an active feedback system becomes feasible. The fully three-dimensional stability code STARWALL, and the feedback optimization code OPTIM have been developed [P. Merkel and M. Sempf, 21st IAEA Fusion Energy Conference 2006, Chengdu, China (International Atomic Energy Agency, Vienna, 2006, paper TH/P3-8] to compute the growth rates of resistive wall modes in the presence of nonaxisymmetric, multiply connected wall structures and to model the active feedback stabilization of these modes.more » In order to demonstrate the capabilities of the codes and to study the effect of the toroidal mode coupling caused by multiply connected wall structures, the codes are applied to test equilibria using the resistive wall structures currently under debate for ITER [M. Shimada et al., Nucl. Fusion 47, S1 (2007)] and ASDEX Upgrade [W. Koeppendoerfer et al., Proceedings of the 16th Symposium on Fusion Technology, London, 1990 (Elsevier, Amsterdam, 1991), Vol. 1, p. 208].« less

mTORC1 Is a Local, Postsynaptic Voltage Sensor Regulated by Positive and Negative Feedback Pathways

PubMed Central

Niere, Farr; Raab-Graham, Kimberly F.

2017-01-01

The mammalian/mechanistic target of rapamycin complex 1 (mTORC1) serves as a regulator of mRNA translation. Recent studies suggest that mTORC1 may also serve as a local, voltage sensor in the postsynaptic region of neurons. Considering biochemical, bioinformatics and imaging data, we hypothesize that the activity state of mTORC1 dynamically regulates local membrane potential by promoting and repressing protein synthesis of select mRNAs. Our hypothesis suggests that mTORC1 uses positive and negative feedback pathways, in a branch-specific manner, to maintain neuronal excitability within an optimal range. In some dendritic branches, mTORC1 activity oscillates between the “On” and “Off” states. We define this as negative feedback. In contrast, positive feedback is defined as the pathway that leads to a prolonged depolarized or hyperpolarized resting membrane potential, whereby mTORC1 activity is constitutively on or off, respectively. We propose that inactivation of mTORC1 increases the expression of voltage-gated potassium alpha (Kv1.1 and 1.2) and beta (Kvβ2) subunits, ensuring that the membrane resets to its resting membrane potential after experiencing increased synaptic activity. In turn, reduced mTORC1 activity increases the protein expression of syntaxin-1A and promotes the surface expression of the ionotropic glutamate receptor N-methyl-D-aspartate (NMDA)-type subunit 1 (GluN1) that facilitates increased calcium entry to turn mTORC1 back on. Under conditions such as learning and memory, mTORC1 activity is required to be high for longer periods of time. Thus, the arm of the pathway that promotes syntaxin-1A and Kv1 protein synthesis will be repressed. Moreover, dendritic branches that have low mTORC1 activity with increased Kv expression would balance dendrites with constitutively high mTORC1 activity, allowing for the neuron to maintain its overall activity level within an ideal operating range. Finally, such a model suggests that recruitment of more positive feedback dendritic branches within a neuron is likely to lead to neurodegenerative disorders. PMID:28611595

Heralded ions via ionization coincidence

NASA Astrophysics Data System (ADS)

McCulloch, A. J.; Speirs, R. W.; Wissenberg, S. H.; Tielen, R. P. M.; Sparkes, B. M.; Scholten, R. E.

2018-04-01

We demonstrate a method for the deterministic production of single ions by exploiting the correlation between an electron and associated ion following ionization. Coincident detection and feedback in combination with Coulomb-driven particle selection allows for high-fidelity heralding of ions at a high repetition rate. Extension of the scheme beyond time-correlated feedback to position- and momentum-correlated feedback will provide a general and powerful means to optimize the ion beam brightness for the development of next-generation focused ion beam technologies.

Control design for robust stability in linear regulators: Application to aerospace flight control

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1986-01-01

Time domain stability robustness analysis and design for linear multivariable uncertain systems with bounded uncertainties is the central theme of the research. After reviewing the recently developed upper bounds on the linear elemental (structured), time varying perturbation of an asymptotically stable linear time invariant regulator, it is shown that it is possible to further improve these bounds by employing state transformations. Then introducing a quantitative measure called the stability robustness index, a state feedback conrol design algorithm is presented for a general linear regulator problem and then specialized to the case of modal systems as well as matched systems. The extension of the algorithm to stochastic systems with Kalman filter as the state estimator is presented. Finally an algorithm for robust dynamic compensator design is presented using Parameter Optimization (PO) procedure. Applications in a aircraft control and flexible structure control are presented along with a comparison with other existing methods.

Safety implications of providing real-time feedback to distracted drivers.

PubMed

Donmez, Birsen; Boyle, Linda Ng; Lee, John D

2007-05-01

A driving simulator study was conducted to assess whether real-time feedback on a driver's state can influence the driver's interaction with in-vehicle information systems (IVIS). Previous studies have shown that IVIS tasks can undermine driver safety by increasing driver distraction. Thus, mitigating driver distraction using a feedback mechanism appears promising. This study was designed to test real-time feedback that alerts drivers based on their off-road eye glances. Feedback was displayed in two display locations (vehicle-centered, and IVIS-centered) to 16 young and 13 middle-aged drivers. Distraction was observed as problematic for both age groups with delayed responses to a lead vehicle-braking event as indicated by delayed accelerator releases. Significant benefits were not observed for braking and steering behavior for this experiment, but there was a significant change in drivers' interaction with IVIS. When given feedback on their distracted state, drivers looked at the in-vehicle display less frequently regardless of where feedback was displayed in the vehicle. This indicates that real-time feedback based on the driver state can positively alter driver's engagement in distracting activities, helping them attend better to the roadway.

Virtual reality environments for post-stroke arm rehabilitation.

PubMed

Subramanian, Sandeep; Knaut, Luiz A; Beaudoin, Christian; McFadyen, Bradford J; Feldman, Anatol G; Levin, Mindy F

2007-06-22

Optimal practice and feedback elements are essential requirements for maximal motor recovery in patients with motor deficits due to central nervous system lesions. A virtual environment (VE) was created that incorporates practice and feedback elements necessary for maximal motor recovery. It permits varied and challenging practice in a motivating environment that provides salient feedback. The VE gives the user knowledge of results feedback about motor behavior and knowledge of performance feedback about the quality of pointing movements made in a virtual elevator. Movement distances are related to length of body segments. We describe an immersive and interactive experimental protocol developed in a virtual reality environment using the CAREN system. The VE can be used as a training environment for the upper limb in patients with motor impairments.

Biased feedback in brain-computer interfaces.

PubMed

Barbero, Alvaro; Grosse-Wentrup, Moritz

2010-07-27

Even though feedback is considered to play an important role in learning how to operate a brain-computer interface (BCI), to date no significant influence of feedback design on BCI-performance has been reported in literature. In this work, we adapt a standard motor-imagery BCI-paradigm to study how BCI-performance is affected by biasing the belief subjects have on their level of control over the BCI system. Our findings indicate that subjects already capable of operating a BCI are impeded by inaccurate feedback, while subjects normally performing on or close to chance level may actually benefit from an incorrect belief on their performance level. Our results imply that optimal feedback design in BCIs should take into account a subject's current skill level.

Task-dependent vestibular feedback responses in reaching.

PubMed

Keyser, Johannes; Medendorp, W Pieter; Selen, Luc P J

2017-07-01

When reaching for an earth-fixed object during self-rotation, the motor system should appropriately integrate vestibular signals and sensory predictions to compensate for the intervening motion and its induced inertial forces. While it is well established that this integration occurs rapidly, it is unknown whether vestibular feedback is specifically processed dependent on the behavioral goal. Here, we studied whether vestibular signals evoke fixed responses with the aim to preserve the hand trajectory in space or are processed more flexibly, correcting trajectories only in task-relevant spatial dimensions. We used galvanic vestibular stimulation to perturb reaching movements toward a narrow or a wide target. Results show that the same vestibular stimulation led to smaller trajectory corrections to the wide than the narrow target. We interpret this reduced compensation as a task-dependent modulation of vestibular feedback responses, tuned to minimally intervene with the task-irrelevant dimension of the reach. These task-dependent vestibular feedback corrections are in accordance with a central prediction of optimal feedback control theory and mirror the sophistication seen in feedback responses to mechanical and visual perturbations of the upper limb. NEW & NOTEWORTHY Correcting limb movements for external perturbations is a hallmark of flexible sensorimotor behavior. While visual and mechanical perturbations are corrected in a task-dependent manner, it is unclear whether a vestibular perturbation, naturally arising when the body moves, is selectively processed in reach control. We show, using galvanic vestibular stimulation, that reach corrections to vestibular perturbations are task dependent, consistent with a prediction of optimal feedback control theory. Copyright © 2017 the American Physiological Society.

Switching of the positive feedback for RAS activation by a concerted function of SOS membrane association domains.

PubMed

Nakamura, Yuki; Hibino, Kayo; Yanagida, Toshio; Sako, Yasushi

2016-01-01

Son of sevenless (SOS) is a guanine nucleotide exchange factor that regulates cell behavior by activating the small GTPase RAS. Recent in vitro studies have suggested that an interaction between SOS and the GTP-bound active form of RAS generates a positive feedback loop that propagates RAS activation. However, it remains unclear how the multiple domains of SOS contribute to the regulation of the feedback loop in living cells. Here, we observed single molecules of SOS in living cells to analyze the kinetics and dynamics of SOS behavior. The results indicate that the histone fold and Grb2-binding domains of SOS concertedly produce an intermediate state of SOS on the cell surface. The fraction of the intermediated state was reduced in positive feedback mutants, suggesting that the feedback loop functions during the intermediate state. Translocation of RAF, recognizing the active form of RAS, to the cell surface was almost abolished in the positive feedback mutants. Thus, the concerted functions of multiple membrane-associating domains of SOS governed the positive feedback loop, which is crucial for cell fate decision regulated by RAS.

Time-delayed feedback control of coherence resonance chimeras

NASA Astrophysics Data System (ADS)

Zakharova, Anna; Semenova, Nadezhda; Anishchenko, Vadim; Schöll, Eckehard

2017-11-01

Using the model of a FitzHugh-Nagumo system in the excitable regime, we investigate the influence of time-delayed feedback on noise-induced chimera states in a network with nonlocal coupling, i.e., coherence resonance chimeras. It is shown that time-delayed feedback allows for the control of the range of parameter values where these chimera states occur. Moreover, for the feedback delay close to the intrinsic period of the system, we find a novel regime which we call period-two coherence resonance chimera.

An exact algebraic solution of the infimum in H-infinity optimization with output feedback

NASA Technical Reports Server (NTRS)

Chen, Ben M.; Saberi, Ali; Ly, Uy-Loi

1991-01-01

This paper presents a simple and noniterative procedure for the computation of the exact value of the infimum in the standard H-infinity-optimal control with output feedback. The problem formulation is general and does not place any restrictions on the direct feedthrough terms between the control input and the controlled output variables, and between the disturbance input and the measurement output variables. The method is applicable to systems that satisfy (1) the transfer function from the control input to the controlled output is right-invertible and has no invariant zeros on the j(w) axis and, (2) the transfer function from the disturbance to the measurement output is left-invertible and has no invariant zeros on the j(w) axis. A set of necessary and sufficient conditions for the solvability of H-infinity-almost disturbance decoupling problem via measurement feedback with internal stability is also given.

Operating wind turbines in strong wind conditions by using feedforward-feedback control

NASA Astrophysics Data System (ADS)

Feng, Ju; Sheng, Wen Zhong

2014-12-01

Due to the increasing penetration of wind energy into power systems, it becomes critical to reduce the impact of wind energy on the stability and reliability of the overall power system. In precedent works, Shen and his co-workers developed a re-designed operation schema to run wind turbines in strong wind conditions based on optimization method and standard PI feedback control, which can prevent the typical shutdowns of wind turbines when reaching the cut-out wind speed. In this paper, a new control strategy combing the standard PI feedback control with feedforward controls using the optimization results is investigated for the operation of variable-speed pitch-regulated wind turbines in strong wind conditions. It is shown that the developed control strategy is capable of smoothening the power output of wind turbine and avoiding its sudden showdown at high wind speeds without worsening the loads on rotor and blades.

Vibrotactile sensory substitution for object manipulation: amplitude versus pulse train frequency modulation.

PubMed

Stepp, Cara E; Matsuoka, Yoky

2012-01-01

Incorporating sensory feedback with prosthetic devices is now possible, but the optimal methods of providing such feedback are still unknown. The relative utility of amplitude and pulse train frequency modulated stimulation paradigms for providing vibrotactile feedback for object manipulation was assessed in 10 participants. The two approaches were studied during virtual object manipulation using a robotic interface as a function of presentation order and a simultaneous cognitive load. Despite the potential pragmatic benefits associated with pulse train frequency modulated vibrotactile stimulation, comparison of the approach with amplitude modulation indicates that amplitude modulation vibrotactile stimulation provides superior feedback for object manipulation.

Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Zhang, Huaguang; Lin, Chong

2016-01-01

This paper focuses on the problem of adaptive neural network (NN) control for a class of nonlinear nonstrict-feedback systems via output feedback. A novel adaptive NN backstepping output-feedback control approach is first proposed for nonlinear nonstrict-feedback systems. The monotonicity of system bounding functions and the structure character of radial basis function (RBF) NNs are used to overcome the difficulties that arise from nonstrict-feedback structure. A state observer is constructed to estimate the immeasurable state variables. By combining adaptive backstepping technique with approximation capability of radial basis function NNs, an output-feedback adaptive NN controller is designed through backstepping approach. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. Two examples are used to illustrate the effectiveness of the proposed approach.

Low-Latency Digital Signal Processing for Feedback and Feedforward in Quantum Computing and Communication

NASA Astrophysics Data System (ADS)

Salathé, Yves; Kurpiers, Philipp; Karg, Thomas; Lang, Christian; Andersen, Christian Kraglund; Akin, Abdulkadir; Krinner, Sebastian; Eichler, Christopher; Wallraff, Andreas

2018-03-01

Quantum computing architectures rely on classical electronics for control and readout. Employing classical electronics in a feedback loop with the quantum system allows us to stabilize states, correct errors, and realize specific feedforward-based quantum computing and communication schemes such as deterministic quantum teleportation. These feedback and feedforward operations are required to be fast compared to the coherence time of the quantum system to minimize the probability of errors. We present a field-programmable-gate-array-based digital signal processing system capable of real-time quadrature demodulation, a determination of the qubit state, and a generation of state-dependent feedback trigger signals. The feedback trigger is generated with a latency of 110 ns with respect to the timing of the analog input signal. We characterize the performance of the system for an active qubit initialization protocol based on the dispersive readout of a superconducting qubit and discuss potential applications in feedback and feedforward algorithms.

When Playing Meets Learning: Methodological Framework for Designing Educational Games

NASA Astrophysics Data System (ADS)

Linek, Stephanie B.; Schwarz, Daniel; Bopp, Matthias; Albert, Dietrich

Game-based learning builds upon the idea of using the motivational potential of video games in the educational context. Thus, the design of educational games has to address optimizing enjoyment as well as optimizing learning. Within the EC-project ELEKTRA a methodological framework for the conceptual design of educational games was developed. Thereby state-of-the-art psycho-pedagogical approaches were combined with insights of media-psychology as well as with best-practice game design. This science-based interdisciplinary approach was enriched by enclosed empirical research to answer open questions on educational game-design. Additionally, several evaluation-cycles were implemented to achieve further improvements. The psycho-pedagogical core of the methodology can be summarized by the ELEKTRA's 4Ms: Macroadaptivity, Microadaptivity, Metacognition, and Motivation. The conceptual framework is structured in eight phases which have several interconnections and feedback-cycles that enable a close interdisciplinary collaboration between game design, pedagogy, cognitive science and media psychology.

Natural Circulation Level Optimization and the Effect during ULOF Accident in the SPINNOR Reactors

NASA Astrophysics Data System (ADS)

Abdullah, Ade Gafar; Su'ud, Zaki; Kurniadi, Rizal; Kurniasih, Neny; Yulianti, Yanti

2010-12-01

Natural circulation level optimization and the effect during loss of flow accident in the 250 MWt MOX fuelled small Pb-Bi Cooled non-refueling nuclear reactors (SPINNOR) have been performed. The simulation was performed using FI-ITB safety code which has been developed in ITB. The simulation begins with steady state calculation of neutron flux, power distribution and temperature distribution across the core, hot pool and cool pool, and also steam generator. When the accident is started due to the loss of pumping power the power distribution and the temperature distribution of core, hot pool and cool pool, and steam generator change. Then the feedback reactivity calculation is conducted, followed by kinetic calculation. The process is repeated until the optimum power distribution is achieved. The results show that the SPINNOR reactor has inherent safety capability against this accident.

Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

NASA Technical Reports Server (NTRS)

Wada, Ben K. (Editor); Fanson, James L. (Editor); Miura, Koryo (Editor)

1991-01-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

NASA Astrophysics Data System (ADS)

Wada, Ben K.; Fanson, James L.; Miura, Koryo

1991-11-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

Computer-Supported Feedback Message Tailoring for Healthcare Providers in Malawi: Proof-of-Concept.

PubMed

Landis-Lewis, Zach; Douglas, Gerald P; Hochheiser, Harry; Kam, Matthew; Gadabu, Oliver; Bwanali, Mwatha; Jacobson, Rebecca S

2015-01-01

Although performance feedback has the potential to help clinicians improve the quality and safety of care, healthcare organizations generally lack knowledge about how this guidance is best provided. In low-resource settings, tools for theory-informed feedback tailoring may enhance limited clinical supervision resources. Our objectives were to establish proof-of-concept for computer-supported feedback message tailoring in Malawi, Africa. We conducted this research in five stages: clinical performance measurement, modeling the influence of feedback on antiretroviral therapy (ART) performance, creating a rule-based message tailoring process, generating tailored messages for recipients, and finally analysis of performance and message tailoring data. We retrospectively generated tailored messages for 7,448 monthly performance reports from 11 ART clinics. We found that tailored feedback could be routinely generated for four guideline-based performance indicators, with 35% of reports having messages prioritized to optimize the effect of feedback. This research establishes proof-of-concept for a novel approach to improving the use of clinical performance feedback in low-resource settings and suggests possible directions for prospective evaluations comparing alternative designs of feedback messages.

Period locking due to delayed feedback in a laser with saturable absorber.

PubMed

Carr, T W

2003-08-01

We consider laser with saturable absorber operating in the pulsating regime that is subject to delayed feedback. Alone, both the saturable absorber and delayed feedback cause the clockwise output to become unstable to periodic output via Hopf bifurcations. The delay feedback causes the laser pulse period to lock to an integer fraction of the feedback time. We derive a map from the original model to describe the periodic pulsations of the laser. Equations for the period of the laser predict the occurrence of the different locking states as well as the value of the pump when there is a switch between the locked states.

Dynamics of Team Reflexivity after Feedback

ERIC Educational Resources Information Center

Gabelica, Catherine; Van den Bossche, Piet; Segers, Mien; Gijselaers, Wim

2014-01-01

A great deal of work has been generated on feedback in teams and has shown that giving performance feedback to teams is not sufficient to improve performance. To achieve the potential of feedback, it is stated that teams need to proactively process this feedback and thus collectively evaluate their performance and strategies, look for…

A bottom-up approach to identifying the maximum operational adaptive capacity of water resource systems to a changing climate

NASA Astrophysics Data System (ADS)

Culley, S.; Noble, S.; Yates, A.; Timbs, M.; Westra, S.; Maier, H. R.; Giuliani, M.; Castelletti, A.

2016-09-01

Many water resource systems have been designed assuming that the statistical characteristics of future inflows are similar to those of the historical record. This assumption is no longer valid due to large-scale changes in the global climate, potentially causing declines in water resource system performance, or even complete system failure. Upgrading system infrastructure to cope with climate change can require substantial financial outlay, so it might be preferable to optimize existing system performance when possible. This paper builds on decision scaling theory by proposing a bottom-up approach to designing optimal feedback control policies for a water system exposed to a changing climate. This approach not only describes optimal operational policies for a range of potential climatic changes but also enables an assessment of a system's upper limit of its operational adaptive capacity, beyond which upgrades to infrastructure become unavoidable. The approach is illustrated using the Lake Como system in Northern Italy—a regulated system with a complex relationship between climate and system performance. By optimizing system operation under different hydrometeorological states, it is shown that the system can continue to meet its minimum performance requirements for more than three times as many states as it can under current operations. Importantly, a single management policy, no matter how robust, cannot fully utilize existing infrastructure as effectively as an ensemble of flexible management policies that are updated as the climate changes.

A vibratory stimulation-based inhibition system for nocturnal bruxism: a clinical report.

PubMed

Watanabe, T; Baba, K; Yamagata, K; Ohyama, T; Clark, G T

2001-03-01

For the single subject tested to date, the bruxism-contingent vibratory-feedback system for occlusal appliances effectively inhibited bruxism without inducing substantial sleep disturbance. Whether the reduction in bruxism would continue if the device no longer provided feedback and whether the force levels applied are optimal to induce suppression remain to be determined.

Providing Feedback on Computer-Based Algebra Homework in Middle-School Classrooms

ERIC Educational Resources Information Center

Fyfe, Emily R.

2016-01-01

Homework is transforming at a rapid rate with continuous advances in educational technology. Computer-based homework, in particular, is gaining popularity across a range of schools, with little empirical evidence on how to optimize student learning. The current aim was to test the effects of different types of feedback on computer-based homework.…

Optimal locations and orientations of piezoelectric transducers on cylindrical shell based on gramians of contributed and undesired Rayleigh-Ritz modes using genetic algorithm

NASA Astrophysics Data System (ADS)

Biglar, Mojtaba; Mirdamadi, Hamid Reza; Danesh, Mohammad

2014-02-01

In this study, the active vibration control and configurational optimization of a cylindrical shell are analyzed by using piezoelectric transducers. The piezoelectric patches are attached to the surface of the cylindrical shell. The Rayleigh-Ritz method is used for deriving dynamic modeling of cylindrical shell and piezoelectric sensors and actuators based on the Donnel-Mushtari shell theory. The major goal of this study is to find the optimal locations and orientations of piezoelectric sensors and actuators on the cylindrical shell. The optimization procedure is designed based on desired controllability and observability of each contributed and undesired mode. Further, in order to limit spillover effects, the residual modes are taken into consideration. The optimization variables are the positions and orientations of piezoelectric patches. Genetic algorithm is utilized to evaluate the optimal configurations. In this article, for improving the maximum power and capacity of actuators for amplitude depreciation of negative velocity feedback strategy, we have proposed a new control strategy, called "Saturated Negative Velocity Feedback Rule (SNVF)". The numerical results show that the optimization procedure is effective for vibration reduction, and specifically, by locating actuators and sensors in their optimal locations and orientations, the vibrations of cylindrical shell are suppressed more quickly.

Robust Assignment Of Eigensystems For Flexible Structures

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Lim, Kyong B.; Junkins, John L.

1992-01-01

Improved method for placement of eigenvalues and eigenvectors of closed-loop control system by use of either state or output feedback. Applied to reduced-order finite-element mathematical model of NASA's MAST truss beam structure. Model represents deployer/retractor assembly, inertial properties of Space Shuttle, and rigid platforms for allocation of sensors and actuators. Algorithm formulated in real arithmetic for efficient implementation. Choice of open-loop eigenvector matrix and its closest unitary matrix believed suitable for generating well-conditioned eigensystem with small control gains. Implication of this approach is that element of iterative search for "optimal" unitary matrix appears unnecessary in practice for many test problems.

Time-optimal Aircraft Pursuit-evasion with a Weapon Envelope Constraint

NASA Technical Reports Server (NTRS)

Menon, P. K. A.

1990-01-01

The optimal pursuit-evasion problem between two aircraft including a realistic weapon envelope is analyzed using differential game theory. Six order nonlinear point mass vehicle models are employed and the inclusion of an arbitrary weapon envelope geometry is allowed. The performance index is a linear combination of flight time and the square of the vehicle acceleration. Closed form solution to this high-order differential game is then obtained using feedback linearization. The solution is in the form of a feedback guidance law together with a quartic polynomial for time-to-go. Due to its modest computational requirements, this nonlinear guidance law is useful for on-board real-time implementation.

Feedback Valence Affects Auditory Perceptual Learning Independently of Feedback Probability

PubMed Central

Amitay, Sygal; Moore, David R.; Molloy, Katharine; Halliday, Lorna F.

2015-01-01

Previous studies have suggested that negative feedback is more effective in driving learning than positive feedback. We investigated the effect on learning of providing varying amounts of negative and positive feedback while listeners attempted to discriminate between three identical tones; an impossible task that nevertheless produces robust learning. Four feedback conditions were compared during training: 90% positive feedback or 10% negative feedback informed the participants that they were doing equally well, while 10% positive or 90% negative feedback informed them they were doing equally badly. In all conditions the feedback was random in relation to the listeners’ responses (because the task was to discriminate three identical tones), yet both the valence (negative vs. positive) and the probability of feedback (10% vs. 90%) affected learning. Feedback that informed listeners they were doing badly resulted in better post-training performance than feedback that informed them they were doing well, independent of valence. In addition, positive feedback during training resulted in better post-training performance than negative feedback, but only positive feedback indicating listeners were doing badly on the task resulted in learning. As we have previously speculated, feedback that better reflected the difficulty of the task was more effective in driving learning than feedback that suggested performance was better than it should have been given perceived task difficulty. But contrary to expectations, positive feedback was more effective than negative feedback in driving learning. Feedback thus had two separable effects on learning: feedback valence affected motivation on a subjectively difficult task, and learning occurred only when feedback probability reflected the subjective difficulty. To optimize learning, training programs need to take into consideration both feedback valence and probability. PMID:25946173

No more 'business as usual' with audit and feedback interventions: towards an agenda for a reinvigorated intervention.

PubMed

Ivers, Noah M; Sales, Anne; Colquhoun, Heather; Michie, Susan; Foy, Robbie; Francis, Jill J; Grimshaw, Jeremy M

2014-01-17

Audit and feedback interventions in healthcare have been found to be effective, but there has been little progress with respect to understanding their mechanisms of action or identifying their key 'active ingredients.' Given the increasing use of audit and feedback to improve quality of care, it is imperative to focus further research on understanding how and when it works best. In this paper, we argue that continuing the 'business as usual' approach to evaluating two-arm trials of audit and feedback interventions against usual care for common problems and settings is unlikely to contribute new generalizable findings. Future audit and feedback trials should incorporate evidence- and theory-based best practices, and address known gaps in the literature. We offer an agenda for high-priority research topics for implementation researchers that focuses on reviewing best practices for designing audit and feedback interventions to optimize effectiveness.

Feedback-Equivalence of Nonlinear Systems with Applications to Power System Equations.

NASA Astrophysics Data System (ADS)

Marino, Riccardo

The key concept of the dissertation is feedback equivalence among systems affine in control. Feedback equivalence to linear systems in Brunovsky canonical form and the construction of the corresponding feedback transformation are used to: (i) design a nonlinear regulator for a detailed nonlinear model of a synchronous generator connected to an infinite bus; (ii) establish which power system network structures enjoy the feedback linearizability property and design a stabilizing control law for these networks with a constraint on the control space which comes from the use of d.c. lines. It is also shown that the feedback linearizability property allows the use of state feedback to contruct a linear controllable system with a positive definite linear Hamiltonian structure for the uncontrolled part if the state space is even; a stabilizing control law is derived for such systems. Feedback linearizability property is characterized by the involutivity of certain nested distributions for strongly accessible analytic systems; if the system is defined on a manifold M diffeomorphic to the Euclidean space, it is established that the set where the property holds is a submanifold open and dense in M. If an analytic output map is defined, a set of nested involutive distributions can be always defined and that allows the introduction of an observability property which is the dual concept, in some sense, to feedback linearizability: the goal is to investigate when a nonlinear system affine in control with an analytic output map is feedback equivalent to a linear controllable and observable system. Finally a nested involutive structure of distributions is shown to guarantee the existence of a state feedback that takes a nonlinear system affine in control to a single input one, both feedback equivalent to linear controllable systems, preserving one controlled vector field.

Information-theoretic approach to interactive learning

NASA Astrophysics Data System (ADS)

Still, S.

2009-01-01

The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.

Optimal helicopter trajectory planning for terrain following flight

NASA Technical Reports Server (NTRS)

Menon, P. K. A.

1990-01-01

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

How you provide corrective feedback makes a difference: the motivating role of communicating in an autonomy-supporting way.

PubMed

Mouratidis, Athanasios; Lens, Willy; Vansteenkiste, Maarten

2010-10-01

We relied on self-determination theory (SDT; Deci & Ryan, 2000) to investigate to what extent autonomy-supporting corrective feedback (i.e., feedback that coaches communicate to their athletes after poor performance or mistakes) is associated with athletes' optimal motivation and well-being. To test this hypothesis, we conducted a cross-sectional study with 337 (67.1% males) Greek adolescent athletes (age M = 15.59, SD = 2.37) from various sports. Aligned with SDT, we found through path analysis that an autonomy-supporting versus controlling communication style was positively related to future intentions to persist and well-being and negatively related to ill-being. These relations were partially mediated by the perceived legitimacy of the corrective feedback (i.e., the degree of acceptance of corrective feedback), and, in turn, by intrinsic motivation, identified regulation, and external regulation for doing sports. Results indicate that autonomy-supporting feedback can be still motivating even in cases in which such feedback conveys messages of still too low competence.

High alpha feedback control for agile half-loop maneuvers of the F-18 airplane

NASA Technical Reports Server (NTRS)

Stalford, Harold

1988-01-01

A nonlinear feedback control law for the F/A-18 airplane that provides time-optimal or agile maneuvering of the half-loop maneuver at high angles of attack is given. The feedback control law was developed using the mathematical approach of singular perturbations, in which the control devices considered were conventional aerodynamic control surfaces and thrusting. The derived nonlinear control law was used to simulate F/A-18 half-loop maneuvers. The simulated results at Mach 0.6 and 0.9 compared well with pilot simulations conducted at NASA.

Switching of the positive feedback for RAS activation by a concerted function of SOS membrane association domains

PubMed Central

Nakamura, Yuki; Hibino, Kayo; Yanagida, Toshio; Sako, Yasushi

2016-01-01

Son of sevenless (SOS) is a guanine nucleotide exchange factor that regulates cell behavior by activating the small GTPase RAS. Recent in vitro studies have suggested that an interaction between SOS and the GTP-bound active form of RAS generates a positive feedback loop that propagates RAS activation. However, it remains unclear how the multiple domains of SOS contribute to the regulation of the feedback loop in living cells. Here, we observed single molecules of SOS in living cells to analyze the kinetics and dynamics of SOS behavior. The results indicate that the histone fold and Grb2-binding domains of SOS concertedly produce an intermediate state of SOS on the cell surface. The fraction of the intermediated state was reduced in positive feedback mutants, suggesting that the feedback loop functions during the intermediate state. Translocation of RAF, recognizing the active form of RAS, to the cell surface was almost abolished in the positive feedback mutants. Thus, the concerted functions of multiple membrane-associating domains of SOS governed the positive feedback loop, which is crucial for cell fate decision regulated by RAS. PMID:27924253

Kernel-based least squares policy iteration for reinforcement learning.

PubMed

Xu, Xin; Hu, Dewen; Lu, Xicheng

2007-07-01

In this paper, we present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. By using KLSPI, near-optimal control policies can be obtained without much a priori knowledge on dynamic models of control plants. In KLSPI, Mercer kernels are used in the policy evaluation of a policy iteration process, where a new kernel-based least squares temporal-difference algorithm called KLSTD-Q is proposed for efficient policy evaluation. To keep the sparsity and improve the generalization ability of KLSTD-Q solutions, a kernel sparsification procedure based on approximate linear dependency (ALD) is performed. Compared to the previous works on approximate RL methods, KLSPI makes two progresses to eliminate the main difficulties of existing results. One is the better convergence and (near) optimality guarantee by using the KLSTD-Q algorithm for policy evaluation with high precision. The other is the automatic feature selection using the ALD-based kernel sparsification. Therefore, the KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs). Experimental results on a typical RL task for a stochastic chain problem demonstrate that KLSPI can consistently achieve better learning efficiency and policy quality than the previous least squares policy iteration (LSPI) algorithm. Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller performance using little a priori information of uncertain dynamic systems. It is also demonstrated that KLSPI can be applied to online learning control by incorporating an initial controller to ensure online performance.

Essays on the Economics of Climate Change, Biofuel and Food Prices

NASA Astrophysics Data System (ADS)

Seguin, Charles

Climate change is likely to be the most important global pollution problem that humanity has had to face so far. In this dissertation, I tackle issues directly and indirectly related to climate change, bringing my modest contribution to the body of human creativity trying to deal with climate change. First, I look at the impact of non-convex feedbacks on the optimal climate policy. Second, I try to derive the optimal biofuel policy acknowledging the potential negative impacts that biofuel production might have on food supply. Finally, I test empirically for the presence of loss aversion in food purchases, which might play a role in the consumer response to food price changes brought about by biofuel production. Non-convexities in feedback processes are increasingly found to be important in the climate system. To evaluate their impact on the optimal greenhouse gas (GHG) abate- ment policy, I introduce non-convex feedbacks in a stochastic pollution control model. I numerically calibrate the model to represent the mitigation of greenhouse gas (GHG) emissions contributing to global climate change. This approach makes two contributions to the literature. First, it develops a framework to tackle stochastic non-convex pollu- tion management problems. Second, it applies this framework to the problem of climate change. This approach is in contrast to most of the economic literature on climate change that focuses either on linear feedbacks or environmental thresholds. I find that non-convex feedbacks lead to a decision threshold in the optimal mitigation policy, and I characterize how this threshold depends on feedback parameters and stochasticity. There is great hope that biofuel can help reduce greenhouse gas emissions from fossil fuel. However, there are some concerns that biofuel would increase food prices. In an optimal control model, a co-author and I look at the optimal biofuel production when it competes for land with food production. In addition oil is not exhaustible and output is subject to climate change induced damages. We find that the competitive outcome does not necessarily yield an underproduction of biofuels, but when it does, second best policies like subsidies and mandates can improve welfare. In marketing, there has been extensive empirical research to ascertain whether there is evidence of loss aversion as predicted by several reference price preference theories. Most of that literature finds that there is indeed evidence of loss aversion for many different goods. I argue that it is possible that some of that evidence seemingly supporting loss aversion arises because price endogeneity is not properly taken into account. Using scanner data I study four product categories: bread, chicken, corn and tortilla chips, and pasta. Taking prices as exogenous, I find evidence of loss aversion for bread and corn and tortilla chips. However, when instrumenting prices, the "loss aversion evidence" disappears.

Indirect Identification of Linear Stochastic Systems with Known Feedback Dynamics

NASA Technical Reports Server (NTRS)

Huang, Jen-Kuang; Hsiao, Min-Hung; Cox, David E.

1996-01-01

An algorithm is presented for identifying a state-space model of linear stochastic systems operating under known feedback controller. In this algorithm, only the reference input and output of closed-loop data are required. No feedback signal needs to be recorded. The overall closed-loop system dynamics is first identified. Then a recursive formulation is derived to compute the open-loop plant dynamics from the identified closed-loop system dynamics and known feedback controller dynamics. The controller can be a dynamic or constant-gain full-state feedback controller. Numerical simulations and test data of a highly unstable large-gap magnetic suspension system are presented to demonstrate the feasibility of this indirect identification method.

E-Pad: a comfortable electrocutaneous-based tactile feedback display

NASA Astrophysics Data System (ADS)

Wang, Jiabin; Zhao, Lu; Liu, Yue; Wang, Yongtian; Cai, Yi

2018-01-01

The devices with touchscreen are becoming more popular recently; however, most of them suffer from the crucial drawbacks of lacking accurate tactile feedback. A novel electrocutaneous-based tactile device with the name of E-pad is proposed to provide a dynamic and static low-voltage feedback for touchscreen. We optimize the key parameters of the output voltage and design custom-made hardwares to guarantee a comfortable user experience. Users could move their fingers freely across the touchscreen of the proposed device to really feel virtual objects. Two preliminary experiments are conducted to evaluate the interactive performance of the proposed device and the experimental results show that the proposed device can provide a comfortable and distinct tactile feedback.

A survey of telerobotic surface finishing

NASA Astrophysics Data System (ADS)

Höglund, Thomas; Alander, Jarmo; Mantere, Timo

2018-05-01

This is a survey of research published on the subjects of telerobotics, haptic feedback, and mixed reality applied to surface finishing. The survey especially focuses on how visuo-haptic feedback can be used to improve a grinding process using a remote manipulator or robot. The benefits of teleoperation and reasons for using haptic feedback are presented. The use of genetic algorithms for optimizing haptic sensing is briefly discussed. Ways of augmenting the operator's vision are described. Visual feedback can be used to find defects and analyze the quality of the surface resulting from the surface finishing process. Visual cues can also be used to aid a human operator in manipulating a robot precisely and avoiding collisions.

Feedforward/feedback control synthesis for performance and robustness

NASA Technical Reports Server (NTRS)

Wie, Bong; Liu, Qiang

1990-01-01

Both feedforward and feedback control approaches for uncertain dynamical systems are investigated. The control design objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant modeling uncertainty. Preshapong of an ideal, time-optimal control input using a 'tapped-delay' filter is shown to provide a rapid maneuver with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. The proposed feedforward/feedback control approach is robust for a certain class of uncertain dynamical systems, since the control input command computed for a given desired output does not depend on the plant parameters.

Approximate optimal tracking control for near-surface AUVs with wave disturbances

NASA Astrophysics Data System (ADS)

Yang, Qing; Su, Hao; Tang, Gongyou

2016-10-01

This paper considers the optimal trajectory tracking control problem for near-surface autonomous underwater vehicles (AUVs) in the presence of wave disturbances. An approximate optimal tracking control (AOTC) approach is proposed. Firstly, a six-degrees-of-freedom (six-DOF) AUV model with its body-fixed coordinate system is decoupled and simplified and then a nonlinear control model of AUVs in the vertical plane is given. Also, an exosystem model of wave disturbances is constructed based on Hirom approximation formula. Secondly, the time-parameterized desired trajectory which is tracked by the AUV's system is represented by the exosystem. Then, the coupled two-point boundary value (TPBV) problem of optimal tracking control for AUVs is derived from the theory of quadratic optimal control. By using a recently developed successive approximation approach to construct sequences, the coupled TPBV problem is transformed into a problem of solving two decoupled linear differential sequences of state vectors and adjoint vectors. By iteratively solving the two equation sequences, the AOTC law is obtained, which consists of a nonlinear optimal feedback item, an expected output tracking item, a feedforward disturbances rejection item, and a nonlinear compensatory term. Furthermore, a wave disturbances observer model is designed in order to solve the physically realizable problem. Simulation is carried out by using the Remote Environmental Unit (REMUS) AUV model to demonstrate the effectiveness of the proposed algorithm.

Is Performance Feedback for Educators an Evidence-Based Practice? A Systematic Review and Evaluation Based on Single-Case Research

ERIC Educational Resources Information Center

Fallon, Lindsay M.; Collier-Meek, Melissa A.; Maggin, Daniel M.; Sanetti, Lisa M. H.; Johnson, Austin H.

2015-01-01

Optimal levels of treatment fidelity, a critical moderator of intervention effectiveness, are often difficult to sustain in applied settings. It is unknown whether performance feedback, a widely researched method for increasing educators' treatment fidelity, is an evidence-based practice. The purpose of this review was to evaluate the current…

Psychophysiological Control of Acognitive Task Using Adaptive Automation

NASA Technical Reports Server (NTRS)

Freeman, Frederick; Pope, Alan T. (Technical Monitor)

2001-01-01

The major focus of the present proposal was to examine psychophysiological variables related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding worker performance. Byrne and Parasuraman have argued for the use of psychophysiological measures in the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a cognitive vigilance task. Previous research in our laboratory, supported by NASA, has demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative than a positive, feedback condition. In addition, this condition produces less subjective workload and larger P300 event related potentials to auditory stimuli presented in a concurrent oddball task. We have also recently shown that the closed-loop system used to control the level of automation in a tracking task can also be used to control the event rate of stimuli in a vigilance monitoring task. By changing the event rate based on the subject's index of arousal, we have been able to produce improved monitoring, relative to various control groups. We have demonstrated in our initial closed-loop experiments with the the vigilance paradigm that using a negative feedback contingency (i.e. increasing event rates when the EEG index is low and decreasing event rates when the EEG index is high) results in a marked decrease of the vigilance decrement over a 40 minute session. This effect is in direct contrast to performance of a positive feedback group, as well as a number of other control groups which demonstrated the typical vigilance decrement. Interestingly, however, the negative feedback group performed at virtually the same level as a yoked control group. The yoked control group received the same order of changes in event rate that were generated by the negative feedback subjects using the closed-loop system. Thus it would appear to be possible to optimize vigilance performance by controlling the stimuli which subjects are asked to process.

Comprehensive joint feedback control for standing by functional neuromuscular stimulation-a simulation study.

PubMed

Nataraj, Raviraj; Audu, Musa L; Kirsch, Robert F; Triolo, Ronald J

2010-12-01

Previous investigations of feedback control of standing after spinal cord injury (SCI) using functional neuromuscular stimulation (FNS) have primarily targeted individual joints. This study assesses the potential efficacy of comprehensive (trunk, hips, knees, and ankles) joint feedback control against postural disturbances using a bipedal, 3-D computer model of SCI stance. Proportional-derivative feedback drove an artificial neural network trained to produce muscle excitation patterns consistent with maximal joint stiffness values achievable about neutral stance given typical SCI muscle properties. Feedback gains were optimized to minimize upper extremity (UE) loading required to stabilize against disturbances. Compared to the baseline case of maximum constant muscle excitations used clinically, the controller reduced UE loading by 55% in resisting external force perturbations and by 84% during simulated one-arm functional tasks. Performance was most sensitive to inaccurate measurements of ankle plantar/dorsiflexion position and hip ab/adduction velocity feedback. In conclusion, comprehensive joint feedback demonstrates potential to markedly improve FNS standing function. However, alternative control structures capable of effective performance with fewer sensor-based feedback parameters may better facilitate clinical usage.

Comprehensive Joint Feedback Control for Standing by Functional Neuromuscular Stimulation – a Simulation Study

PubMed Central

Nataraj, Raviraj; Audu, Musa L.; Kirsch, Robert F.; Triolo, Ronald J.

2013-01-01

Previous investigations of feedback control of standing after spinal cord injury (SCI) using functional neuromuscular stimulation (FNS) have primarily targeted individual joints. This study assesses the potential efficacy of comprehensive (trunk, hips, knees, and ankles) joint-feedback control against postural disturbances using a bipedal, three-dimensional computer model of SCI stance. Proportional-derivative feedback drove an artificial neural network trained to produce muscle excitation patterns consistent with maximal joint stiffness values achievable about neutral stance given typical SCI muscle properties. Feedback gains were optimized to minimize upper extremity (UE) loading required to stabilize against disturbances. Compared to the baseline case of maximum constant muscle excitations used clinically, the controller reduced UE loading by 55% in resisting external force perturbations and by 84% during simulated one-arm functional tasks. Performance was most sensitive to inaccurate measurements of ankle plantar/dorsiflexion position and hip ab/adduction velocity feedback. In conclusion, comprehensive joint-feedback demonstrates potential to markedly improve FNS standing function. However, alternative control structures capable of effective performance with fewer sensor-based feedback parameters may better facilitate clinical usage. PMID:20923741

Perioperative feedback in surgical training: A systematic review.

PubMed

McKendy, Katherine M; Watanabe, Yusuke; Lee, Lawrence; Bilgic, Elif; Enani, Ghada; Feldman, Liane S; Fried, Gerald M; Vassiliou, Melina C

2017-07-01

Changes in surgical training have raised concerns about residents' operative exposure and preparedness for independent practice. One way of addressing this concern is by optimizing teaching and feedback in the operating room (OR). The objective of this study was to perform a systematic review on perioperative teaching and feedback. A systematic literature search identified articles from 1994 to 2014 that addressed teaching, feedback, guidance, or debriefing in the perioperative period. Data was extracted according to ENTREQ guidelines, and a qualitative analysis was performed. Thematic analysis of the 26 included studies identified four major topics. Observation of teaching behaviors in the OR described current teaching practices. Identification of effective teaching strategies analyzed teaching behaviors, differentiating positive and negative teaching strategies. Perceptions of teaching behaviors described resident and attending satisfaction with teaching in the OR. Finally models for delivering structured feedback cited examples of feedback strategies and measured their effectiveness. This study provides an overview of perioperative teaching and feedback for surgical trainees and identifies a need for improved quality and quantity of structured feedback. Copyright © 2016 Elsevier Inc. All rights reserved.

Universal photonic quantum computation via time-delayed feedback

PubMed Central

Pichler, Hannes; Choi, Soonwon; Zoller, Peter; Lukin, Mikhail D.

2017-01-01

We propose and analyze a deterministic protocol to generate two-dimensional photonic cluster states using a single quantum emitter via time-delayed quantum feedback. As a physical implementation, we consider a single atom or atom-like system coupled to a 1D waveguide with a distant mirror, where guided photons represent the qubits, while the mirror allows the implementation of feedback. We identify the class of many-body quantum states that can be produced using this approach and characterize them in terms of 2D tensor network states. PMID:29073057

Delay-controlled primary and stochastic resonances of the SD oscillator with stiffness nonlinearities

NASA Astrophysics Data System (ADS)

Yang, Tao; Cao, Qingjie

2018-03-01

This work presents analytical studies of the stiffness nonlinearities SD (smooth and discontinuous) oscillator under displacement and velocity feedback control with a time delay. The SD oscillator can capture the qualitative characteristics of quasi-zero-stiffness and negative-stiffness. We focus mainly on the primary resonance of the quasi-zero-stiffness SD oscillator and the stochastic resonance (SR) of the negative-stiffness SD oscillator. Using the averaging method, we have been analyzed the amplitude response of the quasi-zero-stiffness SD oscillator. In this regard, the optimum time delay for changing the control intensity according to the optimization standard proposed can be obtained. For the optimum time delay, increasing the displacement feedback intensity is advantageous to suppress the vibrations in resonant regime where vibration isolation is needed, however, increasing the velocity feedback intensity is advantageous to strengthen the vibrations. Moreover, the effects of time-delayed feedback on the SR of the negative-stiffness SD oscillator are investigated under harmonic forcing and Gaussian white noise, based on the Langevin and Fokker-Planck approaches. The time-delayed feedback can enhance the SR phenomenon where vibrational energy harvesting is needed. This paper established the relationship between the parameters and vibration properties of a stiffness nonlinearities SD which provides the guidance for optimizing time-delayed control for vibration isolation and vibrational energy harvesting of the nonlinear systems.

Decentralized stabilization of semi-active vibrating structures

NASA Astrophysics Data System (ADS)

Pisarski, Dominik

2018-02-01

A novel method of decentralized structural vibration control is presented. The control is assumed to be realized by a semi-active device. The objective is to stabilize a vibrating system with the optimal rates of decrease of the energy. The controller relies on an easily implemented decentralized switched state-feedback control law. It uses a set of communication channels to exchange the state information between the neighboring subcontrollers. The performance of the designed method is validated by means of numerical experiments performed for a double cantilever system equipped with a set of elastomers with controlled viscoelastic properties. In terms of the assumed objectives, the proposed control strategy significantly outperforms the passive damping cases and is competitive with a standard centralized control. The presented methodology can be applied to a class of bilinear control systems concerned with smart structural elements.

Coherent control of alkali cluster fragmentation dynamics

NASA Astrophysics Data System (ADS)

Lindinger, Albrecht; Lupulescu, Cosmin; Bartelt, Andreas; Vajda, Štefan; Wöste, Ludger

2003-06-01

Metal clusters exhibit extraordinary chemical and catalytic properties, which sensitively depend upon their size. This behavior makes them interesting candidates for the real-time analysis of ultrafast photo-induced processes—ultimately leading to coherent control scenarii. We have performed transient multi-photon ionization experiments on small alkali clusters of different size in order to probe their wave packet dynamics, structural reorientations, charge transfers and dissociative events in different vibrationally excited electronic states including their ground state. The observed processes were highly dependent on the irradiated pulse parameters, like its phase, amplitude and duration; an emphasis to employ a feedback control system for generating the optimum pulse shapes. Their spectral and temporal behavior reflects interesting properties about the investigated system and the irradiated photochemical process. We present first the vibrational dynamics of bound, dissociated, and pre-dissociated electronically excited states of alkali dimers and trimers. The scheme for observing the wave packet dynamics in the electronic ground state using stimulated Raman-pumping is shown. Since the employed pulse parameters significantly influence the efficiency of the irradiated dynamic pathways photo-induced fragmentation experiments on bifurcating reaction channels were carried out. In these experiments different branching ionization and fragmentation pathways of electronically excited Na 2K were investigated. By employing an evolutionary algorithm for optimizing the phase and amplitude of the applied laser field, the yield of the resulting parent or fragment ions could significantly be influenced and interesting features could be concluded from the obtained optimum pulse shapes revealing the characteristic molecular oscillation period. Moreover, the influence on the optimal pulse shape due to fragmentation from larger clusters into NaK is obtained. The substructure of the optimal pulse shape thereby offers new insight into the fragmentation channel during the control process. Characteristic motions of the involved wave packets are proposed, in order to explain the optimized dynamic dissociation pathways.

Output Containment Control of Linear Heterogeneous Multi-Agent Systems Using Internal Model Principle.

PubMed

Zuo, Shan; Song, Yongduan; Lewis, Frank L; Davoudi, Ali

2017-01-04

This paper studies the output containment control of linear heterogeneous multi-agent systems, where the system dynamics and even the state dimensions can generally be different. Since the states can have different dimensions, standard results from state containment control do not apply. Therefore, the control objective is to guarantee the convergence of the output of each follower to the dynamic convex hull spanned by the outputs of leaders. This can be achieved by making certain output containment errors go to zero asymptotically. Based on this formulation, two different control protocols, namely, full-state feedback and static output-feedback, are designed based on internal model principles. Sufficient local conditions for the existence of the proposed control protocols are developed in terms of stabilizing the local followers' dynamics and satisfying a certain H∞ criterion. Unified design procedures to solve the proposed two control protocols are presented by formulation and solution of certain local state-feedback and static output-feedback problems, respectively. Numerical simulations are given to validate the proposed control protocols.

Emotion: The Self-regulatory Sense

PubMed Central

2014-01-01

While emotion is a central component of human health and well-being, traditional approaches to understanding its biological function have been wanting. A dynamic systems model, however, broadly redefines and recasts emotion as a primary sensory system—perhaps the first sensory system to have emerged, serving the ancient autopoietic function of “self-regulation.” Drawing upon molecular biology and revelations from the field of epigenetics, the model suggests that human emotional perceptions provide an ongoing stream of “self-relevant” sensory information concerning optimally adaptive states between the organism and its immediate environment, along with coupled behavioral corrections that honor a universal self-regulatory logic, one still encoded within cellular signaling and immune functions. Exemplified by the fundamental molecular circuitry of sensorimotor control in the E coli bacterium, the model suggests that the hedonic (affective) categories emerge directly from positive and negative feedback processes, their good/bad binary appraisals relating to dual self-regulatory behavioral regimes—evolutionary purposes, through which organisms actively participate in natural selection, and through which humans can interpret optimal or deficit states of balanced being and becoming. The self-regulatory sensory paradigm transcends anthropomorphism, unites divergent theoretical perspectives and isolated bodies of literature, while challenging time-honored assumptions. While suppressive regulatory strategies abound, it suggests that emotions are better understood as regulating us, providing a service crucial to all semantic language, learning systems, evaluative decision-making, and fundamental to optimal physical, mental, and social health. PMID:24808986

Vibrotactile grasping force and hand aperture feedback for myoelectric forearm prosthesis users.

PubMed

Witteveen, Heidi J B; Rietman, Hans S; Veltink, Peter H

2015-06-01

User feedback about grasping force and hand aperture is very important in object handling with myoelectric forearm prostheses but is lacking in current prostheses. Vibrotactile feedback increases the performance of healthy subjects in virtual grasping tasks, but no extensive validation on potential users has been performed. Investigate the performance of upper-limb loss subjects in grasping tasks with vibrotactile stimulation, providing hand aperture, and grasping force feedback. Cross-over trial. A total of 10 subjects with upper-limb loss performed virtual grasping tasks while perceiving vibrotactile feedback. Hand aperture feedback was provided through an array of coin motors and grasping force feedback through a single miniature stimulator or an array of coin motors. Objects with varying sizes and weights had to be grasped by a virtual hand. Percentages correctly applied hand apertures and correct grasping force levels were all higher for the vibrotactile feedback condition compared to the no-feedback condition. With visual feedback, the results were always better compared to the vibrotactile feedback condition. Task durations were comparable for all feedback conditions. Vibrotactile grasping force and hand aperture feedback improves grasping performance of subjects with upper-limb loss. However, it should be investigated whether this is of additional value in daily-life tasks. This study is a first step toward the implementation of sensory vibrotactile feedback for users of myoelectric forearm prostheses. Grasping force feedback is crucial for optimal object handling, and hand aperture feedback is essential for reduction of required visual attention. Grasping performance with feedback is evaluated for the potential users. © The International Society for Prosthetics and Orthotics 2014.

EDITORIAL: Focus on Quantum Control

NASA Astrophysics Data System (ADS)

Rabitz, Herschel

2009-10-01

Control of quantum phenomena has grown from a dream to a burgeoning field encompassing wide-ranging experimental and theoretical activities. Theoretical research in this area primarily concerns identification of the principles for controlling quantum phenomena, the exploration of new experimental applications and the development of associated operational algorithms to guide such experiments. Recent experiments with adaptive feedback control span many applications including selective excitation, wave packet engineering and control in the presence of complex environments. Practical procedures are also being developed to execute real-time feedback control considering the resultant back action on the quantum system. This focus issue includes papers covering many of the latest advances in the field. Focus on Quantum Control Contents Control of quantum phenomena: past, present and future Constantin Brif, Raj Chakrabarti and Herschel Rabitz Biologically inspired molecular machines driven by light. Optimal control of a unidirectional rotor Guillermo Pérez-Hernández, Adam Pelzer, Leticia González and Tamar Seideman Simulating quantum search algorithm using vibronic states of I2 manipulated by optimally designed gate pulses Yukiyoshi Ohtsuki Efficient coherent control by sequences of pulses of finite duration Götz S Uhrig and Stefano Pasini Control by decoherence: weak field control of an excited state objective Gil Katz, Mark A Ratner and Ronnie Kosloff Multi-qubit compensation sequences Y Tomita, J T Merrill and K R Brown Environment-invariant measure of distance between evolutions of an open quantum system Matthew D Grace, Jason Dominy, Robert L Kosut, Constantin Brif and Herschel Rabitz Simplified quantum process tomography M P A Branderhorst, J Nunn, I A Walmsley and R L Kosut Achieving 'perfect' molecular discrimination via coherent control and stimulated emission Stephen D Clow, Uvo C Holscher and Thomas C Weinacht A convenient method to simulate and visually represent two-photon power spectra of arbitrarily and adaptively shaped broadband laser pulses M A Montgomery and N H Damrauer Accurate and efficient implementation of the von Neumann representation for laser pulses with discrete and finite spectra Frank Dimler, Susanne Fechner, Alexander Rodenberg, Tobias Brixner and David J Tannor Coherent strong-field control of multiple states by a single chirped femtosecond laser pulse M Krug, T Bayer, M Wollenhaupt, C Sarpe-Tudoran, T Baumert, S S Ivanov and N V Vitanov Quantum-state measurement of ionic Rydberg wavepackets X Zhang and R R Jones On the paradigm of coherent control: the phase-dependent light-matter interaction in the shaping window Tiago Buckup, Jurgen Hauer and Marcus Motzkus Use of the spatial phase of a focused laser beam to yield mechanistic information about photo-induced chemical reactions V J Barge, Z Hu and R J Gordon Coherent control of multiple vibrational excitations for optimal detection S D McGrane, R J Scharff, M Greenfield and D S Moore Mode selectivity with polarization shaping in the mid-IR David B Strasfeld, Chris T Middleton and Martin T Zanni Laser-guided relativistic quantum dynamics Chengpu Liu, Markus C Kohler, Karen Z Hatsagortsyan, Carsten Muller and Christoph H Keitel Continuous quantum error correction as classical hybrid control Hideo Mabuchi Quantum filter reduction for measurement-feedback control via unsupervised manifold learning Anne E B Nielsen, Asa S Hopkins and Hideo Mabuchi Control of the temporal profile of the local electromagnetic field near metallic nanostructures Ilya Grigorenko and Anatoly Efimov Laser-assisted molecular orientation in gaseous media: new possibilities and applications Dmitry V Zhdanov and Victor N Zadkov Optimization of laser field-free orientation of a state-selected NO molecular sample Arnaud Rouzee, Arjan Gijsbertsen, Omair Ghafur, Ofer M Shir, Thomas Back, Steven Stolte and Marc J J Vrakking Controlling the sense of molecular rotation Sharly Fleischer, Yuri Khodorkovsky, Yehiam Prior and Ilya Sh Averbukh Optimal control of interacting particles: a multi-configuration time-dependent Hartree-Fock approach Michael Mundt and David J Tannor Exact quantum dissipative dynamics under external time-dependent driving fields Jian Xu, Rui-Xue Xu and Yi Jing Yan Pulse trains in molecular dynamics and coherent spectroscopy: a theoretical study J Voll and R de Vivie-Riedle Quantum control of electron localization in molecules driven by trains of half-cycle pulses Emil Persson, Joachim Burgdorfer and Stefanie Grafe Quantum control design by Lyapunov trajectory tracking for dipole and polarizability coupling Jean-Michel Coron, Andreea Grigoriu, Catalin Lefter and Gabriel Turinici Sliding mode control of quantum systems Daoyi Dong and Ian R Petersen Implementation of fault-tolerant quantum logic gates via optimal control R Nigmatullin and S G Schirmer Generalized filtering of laser fields in optimal control theory: application to symmetry filtering of quantum gate operations Markus Schroder and Alex Brown

Effect of feedback mode and task difficulty on quality of timing decisions in a zero-sum game.

PubMed

Tikuisis, Peter; Vartanian, Oshin; Mandel, David R

2014-09-01

The objective was to investigate the interaction between the mode of performance outcome feedback and task difficulty on timing decisions (i.e., when to act). Feedback is widely acknowledged to affect task performance. However, the extent to which feedback display mode and its impact on timing decisions is moderated by task difficulty remains largely unknown. Participants repeatedly engaged a zero-sum game involving silent duels with a computerized opponent and were given visual performance feedback after each engagement. They were sequentially tested on three different levels of task difficulty (low, intermediate, and high) in counterbalanced order. Half received relatively simple "inside view" binary outcome feedback, and the other half received complex "outside view" hit rate probability feedback. The key dependent variables were response time (i.e., time taken to make a decision) and survival outcome. When task difficulty was low to moderate, participants were more likely to learn and perform better from hit rate probability feedback than binary outcome feedback. However, better performance with hit rate feedback exacted a higher cognitive cost manifested by higher decision response time. The beneficial effect of hit rate probability feedback on timing decisions is partially moderated by task difficulty. Performance feedback mode should be judiciously chosen in relation to task difficulty for optimal performance in tasks involving timing decisions.

Can Performance Feedback during Instruction Boost Knowledge Acquisition? Contrasting Criterion-Based and Social Comparison Feedback

ERIC Educational Resources Information Center

Kollöffel, Bas; de Jong, Ton

2016-01-01

Feedback indicating how well students are performing during a learning task can be very stimulating. In this study with a pre- and post-test design, the effects of two types of performance feedback on learning results were compared: feedback during a learning task was either stated in terms of how well the students were performing relative to…

Reliable numerical computation in an optimal output-feedback design

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1991-01-01

A reliable algorithm is presented for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters. The algorithm is a part of a design algorithm for optimal linear dynamic output-feedback controller that minimizes a finite-time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control-law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed-loop eigensystem. This approach through the use of an accurate Pade series approximation does not require the closed-loop system matrix to be diagonalizable. The algorithm was included in a control design package for optimal robust low-order controllers. Usefulness of the proposed numerical algorithm was demonstrated using numerous practical design cases where degeneracies occur frequently in the closed-loop system under an arbitrary controller design initialization and during the numerical search.

Theoretic aspects of the identification of the parameters in the optimal control model

NASA Technical Reports Server (NTRS)

Vanwijk, R. A.; Kok, J. J.

1977-01-01

The identification of the parameters of the optimal control model from input-output data of the human operator is considered. Accepting the basic structure of the model as a cascade of a full-order observer and a feedback law, and suppressing the inherent optimality of the human controller, the parameters to be identified are the feedback matrix, the observer gain matrix, and the intensity matrices of the observation noise and the motor noise. The identification of the parameters is a statistical problem, because the system and output are corrupted by noise, and therefore the solution must be based on the statistics (probability density function) of the input and output data of the human operator. However, based on the statistics of the input-output data of the human operator, no distinction can be made between the observation and the motor noise, which shows that the model suffers from overparameterization.

Tuning of active vibration controllers for ACTEX by genetic algorithm

NASA Astrophysics Data System (ADS)

Kwak, Moon K.; Denoyer, Keith K.

1999-06-01

This paper is concerned with the optimal tuning of digitally programmable analog controllers on the ACTEX-1 smart structures flight experiment. The programmable controllers for each channel include a third order Strain Rate Feedback (SRF) controller, a fifth order SRF controller, a second order Positive Position Feedback (PPF) controller, and a fourth order PPF controller. Optimal manual tuning of several control parameters can be a difficult task even though the closed-loop control characteristics of each controller are well known. Hence, the automatic tuning of individual control parameters using Genetic Algorithms is proposed in this paper. The optimal control parameters of each control law are obtained by imposing a constraint on the closed-loop frequency response functions using the ACTEX mathematical model. The tuned control parameters are then uploaded to the ACTEX electronic control electronics and experiments on the active vibration control are carried out in space. The experimental results on ACTEX will be presented.

Active relearning for robust supervised classification of pulmonary emphysema

NASA Astrophysics Data System (ADS)

Raghunath, Sushravya; Rajagopalan, Srinivasan; Karwoski, Ronald A.; Bartholmai, Brian J.; Robb, Richard A.

2012-03-01

Radiologists are adept at recognizing the appearance of lung parenchymal abnormalities in CT scans. However, the inconsistent differential diagnosis, due to subjective aggregation, mandates supervised classification. Towards optimizing Emphysema classification, we introduce a physician-in-the-loop feedback approach in order to minimize uncertainty in the selected training samples. Using multi-view inductive learning with the training samples, an ensemble of Support Vector Machine (SVM) models, each based on a specific pair-wise dissimilarity metric, was constructed in less than six seconds. In the active relearning phase, the ensemble-expert label conflicts were resolved by an expert. This just-in-time feedback with unoptimized SVMs yielded 15% increase in classification accuracy and 25% reduction in the number of support vectors. The generality of relearning was assessed in the optimized parameter space of six different classifiers across seven dissimilarity metrics. The resultant average accuracy improved to 21%. The co-operative feedback method proposed here could enhance both diagnostic and staging throughput efficiency in chest radiology practice.

Progress feedback and the OQ-system: The past and the future.

PubMed

Lambert, Michael J

2015-12-01

A serious problem in routine clinical practice is clinician optimism about the benefit clients derive from the therapy that they offer compared to measured benefits. The consequence of seeing the silver lining is a failure to identify cases that, in the end, leave treatment worse-off than when they started or are simply unaffected. It has become clear that some methods of measuring, monitoring, and providing feedback to clinicians about client mental health status over the course of routine care improves treatment outcomes for clients at risk of treatment failure (Shimokawa, Lambert, & Smart, 2010) and thus is a remedy for therapist optimism by identifying cases at risk for poor outcomes. The current article presents research findings related to use of the Outcome Questionnaire-45 and Clinical Support Tools for this purpose. The necessary characteristics of feedback systems that work to benefit client's well-being are identified. In addition, suggestions for future research and use in routine care are presented. (c) 2015 APA, all rights reserved).

Active vibration control for flexible rotor by optimal direct-output feedback control

NASA Technical Reports Server (NTRS)

Nonami, Kenzou; Dirusso, Eliseo; Fleming, David P.

1989-01-01

Experimental research tests were performed to actively control the rotor vibrations of a flexible rotor mounted on flexible bearing supports. The active control method used in the tests is called optimal direct-output feedback control. This method uses four electrodynamic actuators to apply control forces directly to the bearing housings in order to achieve effective vibration control of the rotor. The force actuators are controlled by an analog controller that accepts rotor displacement as input. The controller is programmed with experimentally determined feedback coefficients; the output is a control signal to the force actuators. The tests showed that this active control method reduced the rotor resonance peaks due to unbalance from approximately 250 micrometers down to approximately 25 micrometers (essentially runout level). The tests were conducted over a speed range from 0 to 10,000 rpm; the rotor system had nine critical speeds within this speed range. The method was effective in significantly reducing the rotor vibration for all of the vibration modes and critical speeds.

Active vibration control for flexible rotor by optimal direct-output feedback control

NASA Technical Reports Server (NTRS)

Nonami, K.; Dirusso, E.; Fleming, D. P.

1989-01-01

Experimental research tests were performed to actively control the rotor vibrations of a flexible rotor mounted on flexible bearing supports. The active control method used in the tests is called optimal direct-output feedback control. This method uses four electrodynamic actuators to apply control forces directly to the bearing housings in order to achieve effective vibration control of the rotor. The force actuators are controlled by an analog controller that accepts rotor displacement as input. The controller is programmed with experimentally determined feedback coefficients; the output is a control signal to the force actuators. The tests showed that this active control method reduced the rotor resonance peaks due to unbalance from approximately 250 microns down to approximately 25 microns (essentially runout level). The tests were conducted over a speed range from 0 to 10,000 rpm; the rotor system had nine critical speeds within this speed range. The method was effective in significantly reducing the rotor vibration for all of the vibration modes and critical speeds.

Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-09-07

In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.

Understanding Optimal Decision-Making in Wargaming III

DTIC Science & Technology

2015-10-01

attention - deficit / hyperactivity disorder assessed by the Keio version of the Wisconsin card sorting test. Brain and Development, 34(5), 354-359...immediate feedback regarding friendly, enemy, and total damage. In addition to latency response (LR), attention to feedback also was measured by...measures can detect poor attention allocation. This material is based upon work supported in part by the Army Research Office (62626- NS). The

Delayed excitatory and inhibitory feedback shape neural information transmission

NASA Astrophysics Data System (ADS)

Chacron, Maurice J.; Longtin, André; Maler, Leonard

2005-11-01

Feedback circuitry with conduction and synaptic delays is ubiquitous in the nervous system. Yet the effects of delayed feedback on sensory processing of natural signals are poorly understood. This study explores the consequences of delayed excitatory and inhibitory feedback inputs on the processing of sensory information. We show, through numerical simulations and theory, that excitatory and inhibitory feedback can alter the firing frequency response of stochastic neurons in opposite ways by creating dynamical resonances, which in turn lead to information resonances (i.e., increased information transfer for specific ranges of input frequencies). The resonances are created at the expense of decreased information transfer in other frequency ranges. Using linear response theory for stochastically firing neurons, we explain how feedback signals shape the neural transfer function for a single neuron as a function of network size. We also find that balanced excitatory and inhibitory feedback can further enhance information tuning while maintaining a constant mean firing rate. Finally, we apply this theory to in vivo experimental data from weakly electric fish in which the feedback loop can be opened. We show that it qualitatively predicts the observed effects of inhibitory feedback. Our study of feedback excitation and inhibition reveals a possible mechanism by which optimal processing may be achieved over selected frequency ranges.

Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state.

PubMed

Ge, Hao; Wu, Pingping; Qian, Hong; Xie, Xiaoliang Sunney

2018-03-01

Within an isogenic population, even in the same extracellular environment, individual cells can exhibit various phenotypic states. The exact role of stochastic gene-state switching regulating the transition among these phenotypic states in a single cell is not fully understood, especially in the presence of positive feedback. Recent high-precision single-cell measurements showed that, at least in bacteria, switching in gene states is slow relative to the typical rates of active transcription and translation. Hence using the lac operon as an archetype, in such a region of operon-state switching, we present a fluctuating-rate model for this classical gene regulation module, incorporating the more realistic operon-state switching mechanism that was recently elucidated. We found that the positive feedback mechanism induces bistability (referred to as deterministic bistability), and that the parameter range for its occurrence is significantly broadened by stochastic operon-state switching. We further show that in the absence of positive feedback, operon-state switching must be extremely slow to trigger bistability by itself. However, in the presence of positive feedback, which stabilizes the induced state, the relatively slow operon-state switching kinetics within the physiological region are sufficient to stabilize the uninduced state, together generating a broadened parameter region of bistability (referred to as stochastic bistability). We illustrate the opposite phenotype-transition rate dependence upon the operon-state switching rates in the two types of bistability, with the aid of a recently proposed rate formula for fluctuating-rate models. The rate formula also predicts a maximal transition rate in the intermediate region of operon-state switching, which is validated by numerical simulations in our model. Overall, our findings suggest a biological function of transcriptional "variations" among genetically identical cells, for the emergence of bistability and transition between phenotypic states.

Neural signatures of experience-based improvements in deterministic decision-making.

PubMed

Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

2016-12-15

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural signatures of experience-based improvements in deterministic decision-making

PubMed Central

Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

2016-01-01

Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

Continental Growth and Mantle Hydration as Earth System Feedback Cycles and possible Effects of the Biosphere

NASA Astrophysics Data System (ADS)

Höning, D.; Spohn, T.

2016-12-01

The evolution of Earth is charcterized by intertwined feedback cycles. We focus on two feedback cycles that include the mantle water budget and the continental crust and study possible effects of the Earth's biosphere. The first feedback loop includes cycling of water into the mantle at subduction zones and outgassing at volcanic chains and mid-ocean ridges. Water will reduce the viscosity of mantle rock, and therefore the speed of mantle convection and plate subduction will increase with the mantle water concentration, eventually enhancing the rates of mantle water regassing and outgassing. A second feedback loop includes the production and erosion of continental crust. Continents grow by volcanism above subduction zones, whose total length is determined by the total area of the continents. Furthermore, the erosion rate of the continents is proportional to the total surface area of continental crust. The rate of sediment subduction affects the rate of transport of water to the mantle and the production rate of new continental crust. We present a model that includes both cycles and show how the system develops stable and unstable fixed points in a plane defined by mantle water concentration and surface are of continents. The stable points represent either an Earth mostly covered by continents and a wet mantle or an Earth mostly covered by oceans with a dry mantle. The presently observed Earth is inbetween these extreme states but the state is intrinsically unstable. We couple the feedback model to a parameterized thermal evolution model. We show how Earth evolved towards its present unstable state. We argue that other feedback cycles such as the carbonate silicate cycle may act to stabilize the present state, however. By enhancing continental weathering and erosion, and eventually the sediment transport into subduction zones, the biosphere impacts both feedback cycles and might play a crucial role in regulating Earth's system and keep continental crust coverage and mantle water budget at its present day state.

Modulation of dynamic modes by interplay between positive and negative feedback loops in gene regulatory networks

NASA Astrophysics Data System (ADS)

Wang, Liu-Suo; Li, Ning-Xi; Chen, Jing-Jia; Zhang, Xiao-Peng; Liu, Feng; Wang, Wei

2018-04-01

A positive and a negative feedback loop can induce bistability and oscillation, respectively, in biological networks. Nevertheless, they are frequently interlinked to perform more elaborate functions in many gene regulatory networks. Coupled positive and negative feedback loops may exhibit either oscillation or bistability depending on the intensity of the stimulus in some particular networks. It is less understood how the transition between the two dynamic modes is modulated by the positive and negative feedback loops. We developed an abstract model of such systems, largely based on the core p53 pathway, to explore the mechanism for the transformation of dynamic behaviors. Our results show that enhancing the positive feedback may promote or suppress oscillations depending on the strength of both feedback loops. We found that the system oscillates with low amplitudes in response to a moderate stimulus and switches to the on state upon a strong stimulus. When the positive feedback is activated much later than the negative one in response to a strong stimulus, the system exhibits long-term oscillations before switching to the on state. We explain this intriguing phenomenon using quasistatic approximation. Moreover, early switching to the on state may occur when the system starts from a steady state in the absence of stimuli. The interplay between the positive and negative feedback plays a key role in the transitions between oscillation and bistability. Of note, our conclusions should be applicable only to some specific gene regulatory networks, especially the p53 network, in which both oscillation and bistability exist in response to a certain type of stimulus. Our work also underscores the significance of transient dynamics in determining cellular outcome.

Improving Challenge/Skill Ratio in a Multimodal Interface by Simultaneously Adapting Game Difficulty and Haptic Assistance through Psychophysiological and Performance Feedback

PubMed Central

Rodriguez-Guerrero, Carlos; Knaepen, Kristel; Fraile-Marinero, Juan C.; Perez-Turiel, Javier; Gonzalez-de-Garibay, Valentin; Lefeber, Dirk

2017-01-01

In order to harmonize robotic devices with human beings, the robots should be able to perceive important psychosomatic impact triggered by emotional states such as frustration or boredom. This paper presents a new type of biocooperative control architecture, which acts toward improving the challenge/skill relation perceived by the user when interacting with a robotic multimodal interface in a cooperative scenario. In the first part of the paper, open-loop experiments revealed which physiological signals were optimal for inclusion in the feedback loop. These were heart rate, skin conductance level, and skin conductance response frequency. In the second part of the paper, the proposed controller, consisting of a biocooperative architecture with two degrees of freedom, simultaneously modulating game difficulty and haptic assistance through performance and psychophysiological feedback, is presented. With this setup, the perceived challenge can be modulated by means of the game difficulty and the perceived skill by means of the haptic assistance. A new metric (FlowIndex) is proposed to numerically quantify and visualize the challenge/skill relation. The results are contrasted with comparable previously published work and show that the new method afforded a higher FlowIndex (i.e., a superior challenge/skill relation) and an improved balance between augmented performance and user satisfaction (higher level of valence, i.e., a more enjoyable and satisfactory experience). PMID:28507503

Paradigms for restoration of somatosensory feedback via stimulation of the peripheral nervous system.

PubMed

Pasluosta, Cristian; Kiele, Patrick; Stieglitz, Thomas

2018-04-01

The somatosensory system contributes substantially to the integration of multiple sensor modalities into perception. Tactile sensations, proprioception and even temperature perception are integrated to perceive embodiment of our limbs. Damage of somatosensory networks can severely affect the execution of daily life activities. Peripheral injuries are optimally corrected via direct interfacing of the peripheral nerves. Recent advances in implantable devices, stimulation paradigms, and biomimetic sensors enabled the restoration of natural sensations after amputation of the limb. The refinement of stimulation patterns to deliver natural feedback that can be interpreted intuitively such to prescind from long-learning sessions is crucial to function restoration. For this review, we collected state-of-the-art knowledge on the evolution of stimulation paradigms from single fiber stimulation to the eliciting of multisensory sensations. Data from the literature are structured into six sections: (a) physiology of the somatosensory system; (b) stimulation of single fibers; (c) restoral of multisensory percepts; (d) closure of the control loop in hand prostheses; (e) sensory restoration and the sense of embodiment, and (f) methodologies to assess stimulation outcomes. Full functional recovery demands further research on multisensory integration and brain plasticity, which will bring new paradigms for intuitive sensory feedback in the next generation of limb prostheses. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

A kinesthetic washout filter for force-feedback rendering.

PubMed

Danieau, Fabien; Lecuyer, Anatole; Guillotel, Philippe; Fleureau, Julien; Mollet, Nicolas; Christie, Marc

2015-01-01

Today haptic feedback can be designed and associated to audiovisual content (haptic-audiovisuals or HAV). Although there are multiple means to create individual haptic effects, the issue of how to properly adapt such effects on force-feedback devices has not been addressed and is mostly a manual endeavor. We propose a new approach for the haptic rendering of HAV, based on a washout filter for force-feedback devices. A body model and an inverse kinematics algorithm simulate the user's kinesthetic perception. Then, the haptic rendering is adapted in order to handle transitions between haptic effects and to optimize the amplitude of effects regarding the device capabilities. Results of a user study show that this new haptic rendering can successfully improve the HAV experience.

Develop feedback system for intelligent dynamic resource allocation to improve application performance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gentile, Ann C.; Brandt, James M.; Tucker, Thomas

2011-09-01

This report provides documentation for the completion of the Sandia Level II milestone 'Develop feedback system for intelligent dynamic resource allocation to improve application performance'. This milestone demonstrates the use of a scalable data collection analysis and feedback system that enables insight into how an application is utilizing the hardware resources of a high performance computing (HPC) platform in a lightweight fashion. Further we demonstrate utilizing the same mechanisms used for transporting data for remote analysis and visualization to provide low latency run-time feedback to applications. The ultimate goal of this body of work is performance optimization in the facemore » of the ever increasing size and complexity of HPC systems.« less

UAV State Estimation Modeling Techniques in AHRS

NASA Astrophysics Data System (ADS)

Razali, Shikin; Zhahir, Amzari

2017-11-01

Autonomous unmanned aerial vehicle (UAV) system is depending on state estimation feedback to control flight operation. Estimation on the correct state improves navigation accuracy and achieves flight mission safely. One of the sensors configuration used in UAV state is Attitude Heading and Reference System (AHRS) with application of Extended Kalman Filter (EKF) or feedback controller. The results of these two different techniques in estimating UAV states in AHRS configuration are displayed through position and attitude graphs.

Optimal integral force feedback for active vibration control

NASA Astrophysics Data System (ADS)

Teo, Yik R.; Fleming, Andrew J.

2015-11-01

This paper proposes an improvement to Integral Force Feedback (IFF), which is a popular method for active vibration control of structures and mechanical systems. Benefits of IFF include robustness, guaranteed stability and simplicity. However, the maximum damping performance is dependent on the stiffness of the system; hence, some systems cannot be adequately controlled. In this paper, an improvement to the classical force feedback control scheme is proposed. The improved method achieves arbitrary damping for any mechanical system by introducing a feed-through term. The proposed improvement is experimentally demonstrated by actively damping an objective lens assembly for a high-speed confocal microscope.

Catchments Under Change: Assessing Impacts and Feedbacks from New Biomass Crops in the Agricultural Midwestern USA

NASA Astrophysics Data System (ADS)

Yaeger, Mary; Housh, Mashor; Ng, Tze Ling; Cai, Ximing; Sivapalan, Murugesu

2013-04-01

In order to meet the challenges of future change, it is essential to understand the environmental response to current conditions and historical changes. The central Midwestern US is an example of anthropogenic change and environmental feedbacks, having been transformed from a natural grassland system to an artificially-drained agricultural system. Environmental feedbacks from reduced soil residence times coupled with increasing crop fertilization have manifested as a hypoxic zone in the Gulf of Mexico. In an effort to address these feedbacks while meeting new crop demands, large-scale planting of high-yielding perennial biomass crops has been proposed. This could be detrimental to both human and environmental streamflow users because these plants require more water than do current crops. The lowest natural flows in this shallow groundwater-dependent region coincide with the peak of the growing season, thus compounding the problem. Therefore, for large-scale biomass crop production to be sustainable, these tradeoffs between water quality and water quantity must be fully understood. To better understand the catchment response to current conditions, we have analyzed streamflow data in a central Illinois agricultural watershed. To deal with future changes, we have developed an integrated systems model which provides, among other outputs, the land usage that maximizes the benefit to the human system. This land use is then implemented in a separate hydrologic model to determine the impact to the environmental system. Interactively running the two models, taking into account the catchment response to human actions as well as possible anthropogenic responses to the environment, allows us to examine the feedbacks between the two systems. This lets us plot the trajectory of the state of the system, which we hypothesize will show emergent internal properties of the coupled system. Initial tests of this modeling framework show promise that this may indeed be the case. External economic forcings were applied to the human system, resulting in greatly-reduced streamflow due to a large percentage of the watershed planted with the new crops. The anthropogenic response to this environmental feedback was an imposed minimum flow requirement in the integrated model, which resulted in a new optimized land use that improved environmental conditions, but not to the previous state. Further refinement of this experiment will provide thresholds, both where crop types change, and where environmental damage becomes evident. Preliminary results revealed added complexity, as tributary and mainstem subcatchments do not respond equally, even in this homogenous region; thus the spatial context also becomes important.

Optimizing Tailored Communications for Health Risk Assessment: A Randomized Factorial Experiment of the Effects of Expectancy Priming, Autonomy Support, and Exemplification

PubMed Central

Ribisl, Kurt M; Mayer, Deborah K; Tate, Deborah F

2018-01-01

Background Health risk assessments with tailored feedback plus health education have been shown to be effective for promoting health behavior change. However, there is limited evidence to guide the development and delivery of online automated tailored feedback. Objective The goal of this study was to optimize tailored feedback messages for an online health risk assessment to promote enhanced user engagement, self-efficacy, and behavioral intentions for engaging in healthy behaviors. We examined the effects of three theory-based message factors used in developing tailored feedback messages on levels of engagement, self-efficacy, and behavioral intentions. Methods We conducted a randomized factorial experiment to test three different components of tailored feedback messages: tailored expectancy priming, autonomy support, and use of an exemplar. Individuals (N=1945) were recruited via Amazon Mechanical Turk and randomly assigned to one of eight different experimental conditions within one of four behavioral assessment and feedback modules (tobacco use, physical activity [PA], eating habits, and weight). Participants reported self-efficacy and behavioral intentions pre- and postcompletion of an online health behavior assessment with tailored feedback. Engagement and message perceptions were assessed at follow-up. Results For the tobacco module, there was a significant main effect of the exemplar factor (P=.04); participants who received exemplar messages (mean 3.31, SE 0.060) rated their self-efficacy to quit tobacco higher than those who did not receive exemplar messages (mean 3.14, SE 0.057). There was a three-way interaction between the effect of message conditions on self-efficacy to quit tobacco (P=.02), such that messages with tailored priming and an exemplar had the greatest impact on self-efficacy to quit tobacco. Across PA, eating habits, and weight modules, there was a three-way interaction among conditions on self-efficacy (P=.048). The highest self-efficacy scores were reported among those who were in the standard priming condition and received both autonomy supportive and exemplar messages. In the PA module, autonomy supportive messages had a stronger effect on self-efficacy for PA in the standard priming condition. For PA, eating habits, and weight-related behaviors, the main effect of exemplar messages on behavioral intentions was in the hypothesized direction but did not reach statistical significance (P=.08). When comparing the main effects of different message conditions, there were no differences in engagement and message perceptions. Conclusions Findings suggest that tailored feedback messages that use exemplars helped improve self-efficacy related to tobacco cessation, PA, eating habits, and weight control. Combining standard priming and autonomy supportive message components shows potential for optimizing tailored feedback for tobacco cessation and PA behaviors. PMID:29496652

Self-tuning bistable parametric feedback oscillator: Near-optimal amplitude maximization without model information

NASA Astrophysics Data System (ADS)

Braun, David J.; Sutas, Andrius; Vijayakumar, Sethu

2017-01-01

Theory predicts that parametrically excited oscillators, tuned to operate under resonant condition, are capable of large-amplitude oscillation useful in diverse applications, such as signal amplification, communication, and analog computation. However, due to amplitude saturation caused by nonlinearity, lack of robustness to model uncertainty, and limited sensitivity to parameter modulation, these oscillators require fine-tuning and strong modulation to generate robust large-amplitude oscillation. Here we present a principle of self-tuning parametric feedback excitation that alleviates the above-mentioned limitations. This is achieved using a minimalistic control implementation that performs (i) self-tuning (slow parameter adaptation) and (ii) feedback pumping (fast parameter modulation), without sophisticated signal processing past observations. The proposed approach provides near-optimal amplitude maximization without requiring model-based control computation, previously perceived inevitable to implement optimal control principles in practical application. Experimental implementation of the theory shows that the oscillator self-tunes itself near to the onset of dynamic bifurcation to achieve extreme sensitivity to small resonant parametric perturbations. As a result, it achieves large-amplitude oscillations by capitalizing on the effect of nonlinearity, despite substantial model uncertainties and strong unforeseen external perturbations. We envision the present finding to provide an effective and robust approach to parametric excitation when it comes to real-world application.

Accounting for soil biotic effects on soil health and crop productivity in the design of crop rotations.

PubMed

Dias, Teresa; Dukes, Angela; Antunes, Pedro M

2015-02-01

There is an urgent need for novel agronomic improvements capable of boosting crop yields while alleviating environmental impacts. One such approach is the use of optimized crop rotations. However, a set of measurements that can serve as guiding principles for the design of crop rotations is lacking. Crop rotations take advantage of niche complementarity, enabling the optimization of nutrient use and the reduction of pests and specialist pathogen loads. However, despite the recognized importance of plant-soil microbial interactions and feedbacks for crop yield and soil health, this is ignored in the selection and management of crops for rotation systems. We review the literature and propose criteria for the design of crop rotations focusing on the roles of soil biota and feedback on crop productivity and soil health. We consider that identifying specific key organisms or consortia capable of influencing plant productivity is more important as a predictor of soil health and crop productivity than assessing the overall soil microbial diversity per se. As such, we propose that setting up soil feedback studies and applying genetic sequencing tools towards the development of soil biotic community databases has a strong potential to enable the establishment of improved soil health indicators for optimized crop rotations. © 2014 Society of Chemical Industry.

Patient-focused and feedback research in psychotherapy: Where are we and where do we want to go?

PubMed

Lutz, Wolfgang; De Jong, Kim; Rubel, Julian

2015-01-01

In the last 15 years feedback interventions have had a significant impact on the field of psychotherapy research and have demonstrated their potential to enhance treatment outcomes, especially for patients with an increased risk of treatment failure. This article serves as an introduction to the special issue on "Patient-focused and feedback research in psychotherapy: Where are we and where do we want to go?" Current investigations on feedback research are concerned with potential moderators and mediators of these effects, as well as the design and the implementation of feedback into routine care. This introduction summarizes the current state of feedback research and provides an overview of the three main research topics in this issue: (1) How to implement feedback systems into routine practice and how do therapist and patient attitudes influence its effects?, (2) How to design feedback reports and decision support tools?, and (3) What are the reasons for patients to become at risk of treatment failure and how should therapists intervene with these patients? We believe that the studies included in this special issue reflect the current state of feedback research and provide promising pathways for future endeavors that will enhance our understanding of feedback effects.

Clinical workplace learning: perceived learning value of individual and group feedback in a collectivistic culture.

PubMed

Suhoyo, Yoyo; Schönrock-Adema, Johanna; Emilia, Ova; Kuks, Jan B M; Cohen-Schotanus, Janke

2018-04-19

Feedback is essential for workplace learning. Most papers in this field concern individual feedback. In collectivistic cultures, however, group feedback is common educational practice. This study was conducted to investigate the perceived learning value and characteristics of individual and group feedback in a collectivistic culture. During two weeks, on a daily basis, clerkship students (n = 215) from 12 clinical departments at Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia, recorded individual and group feedback moments by using a structured form: the providers, focus and perceived learning value of feedback. Data were analysed with logistic regression and multilevel techniques. Students reported 2687 group and 1535 individual feedback moments. Group feedback more often focused on history taking, clinical judgment, patient management, patient counselling, and professional behaviour (OR ranging from 1.232, p < .01, to 2.152, p < .001), but less often on physical examination (OR = .836, p < .01). Group feedback less often aimed at correcting performance deficiencies (OR = .523, p < .001) and more often at comparing performance to the standard (OR = 2.447, p < .001) and planning action to improve performance (OR = 1.759, p < .001). Group feedback was perceived as more valuable than individual feedback (M = 4.08 and 3.96, respectively, β group  = .065, SE = .026, p < .01). In collectivistic cultures, group feedback may add to the array of educational measures that optimize student learning. Congruence between culture and type of feedback may be important for the effectiveness of feedback.

Feedback control of plasma instabilities with charged particle beams and study of plasma turbulence

NASA Technical Reports Server (NTRS)

Tham, Philip Kin-Wah

1994-01-01

A new non-perturbing technique for feedback control of plasma instabilities has been developed in the Columbia Linear Machine (CLM). The feedback control scheme involves the injection of a feedback modulated ion beam as a remote suppressor. The ion beam was obtained from a compact ion beam source which was developed for this purpose. A Langmuir probe was used as the feedback sensor. The feedback controller consisted of a phase-shifter and amplifiers. This technique was demonstrated by stabilizing various plasma instabilities to the background noise level, like the trapped particle instability, the ExB instability and the ion-temperature-gradient (ITG) driven instability. An important feature of this scheme is that the injected ion beam is non-perturbing to the plasma equilibrium parameters. The robustness of this feedback stabilization scheme was also investigated. The principal result is that the scheme is fairly robust, tolerating about 100% variation about the nominal parameter values. Next, this scheme is extended to the unsolved general problem of controlling multimode plasma instabilities simultaneously with a single sensor-suppressor pair. A single sensor-suppressor pair of feedback probes is desirable to reduce the perturbation caused by the probes. Two plasma instabilities the ExB and the ITG modes, were simultaneously stabilized. A simple 'state' feedback type method was used where more state information was generated from the single sensor Langmuir probe by appropriate signal processing, in this case, by differentiation. This proof-of-principle experiment demonstrated for the first time that by designing a more sophisticated electronic feedback controller, many plasma instabilities may be simultaneously controlled. Simple theoretical models showed generally good agreement with the feedback experimental results. On a parallel research front, a better understanding of the saturated state of a plasma instability was sought partly with the help of feedback. A plasma instability is usually observed in its saturated state and appears as a single feature in the frequency spectrum with a single azimuthal and parallel wavenumbers. The physics of the non-zero spectral width was investigated in detail because the finite spectral width can cause "turbulent" transport. One aspect of the "turbulence" was investigated by obtaining the scaling of the linear growth rate of the instabilities with the fluctuation levels. The linear growth rates were measured with the established gated feedback technique. The research showed that the ExB instability evolves into a quasi-coherent state when the fluctuation level is high. The coherent aspects were studied with a bispectral analysis. Moreover, the single spectral feature was discovered to be actually composed of a few radial harmonics. The radial harmonics play a role in the nonlinear saturation of the instability via three-wave coupling.

Understanding constructive feedback: a commitment between teachers and students for academic and professional development.

PubMed

Hamid, Yasir; Mahmood, Sajid

2010-03-01

This review highlights the need in the Pakistani medical education system for teachers and students to be able to: define constructive feedback; provide constructive feedback; identify standards for constructive feedback; identify a suitable model for the provision of constructive feedback and evaluate the use of constructive feedback. For the purpose of literature review we had defined the key word glossary as: feedback, constructive feedback, teaching constructive feedback, models for feedback, models for constructive feedback and giving and receiving feedback. The data bases for the search include: Medline (EBSCO), Web of Knowledge, SCOPUS, TRIP, ScienceDirect, Pubmed, U.K. Pubmed Central, ZETOC, University of Dundee Library catalogue, SCIRUS (Elsevier) and Google Scholar. This article states that the Pakistani medical schools do not reflect on or use the benefits of the constructive feedback process. The discussion about constructive feedback suggests that in the context of Pakistan, constructive feedback will facilitate the teaching and learning activities.

No more ‘business as usual’ with audit and feedback interventions: towards an agenda for a reinvigorated intervention

PubMed Central

2014-01-01

Background Audit and feedback interventions in healthcare have been found to be effective, but there has been little progress with respect to understanding their mechanisms of action or identifying their key ‘active ingredients.’ Discussion Given the increasing use of audit and feedback to improve quality of care, it is imperative to focus further research on understanding how and when it works best. In this paper, we argue that continuing the ‘business as usual’ approach to evaluating two-arm trials of audit and feedback interventions against usual care for common problems and settings is unlikely to contribute new generalizable findings. Future audit and feedback trials should incorporate evidence- and theory-based best practices, and address known gaps in the literature. Summary We offer an agenda for high-priority research topics for implementation researchers that focuses on reviewing best practices for designing audit and feedback interventions to optimize effectiveness. PMID:24438584

Robust Frequency-Domain Constrained Feedback Design via a Two-Stage Heuristic Approach.

PubMed

Li, Xianwei; Gao, Huijun

2015-10-01

Based on a two-stage heuristic method, this paper is concerned with the design of robust feedback controllers with restricted frequency-domain specifications (RFDSs) for uncertain linear discrete-time systems. Polytopic uncertainties are assumed to enter all the system matrices, while RFDSs are motivated by the fact that practical design specifications are often described in restricted finite frequency ranges. Dilated multipliers are first introduced to relax the generalized Kalman-Yakubovich-Popov lemma for output feedback controller synthesis and robust performance analysis. Then a two-stage approach to output feedback controller synthesis is proposed: at the first stage, a robust full-information (FI) controller is designed, which is used to construct a required output feedback controller at the second stage. To improve the solvability of the synthesis method, heuristic iterative algorithms are further formulated for exploring the feedback gain and optimizing the initial FI controller at the individual stage. The effectiveness of the proposed design method is finally demonstrated by the application to active control of suspension systems.

Evolving autonomous learning in cognitive networks.

PubMed

Sheneman, Leigh; Hintze, Arend

2017-12-01

There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

PubMed

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.

Comparative study of flare control laws

NASA Technical Reports Server (NTRS)

Nadkarni, A. A.

1981-01-01

The development of a digital, three dimensional, automatic control law designed to achieve an optimal transition of a B-737 aircraft between glide slope conditions and the desired final touchdown condition is presented. The digital control law is a time invariant, state estimate feedback law, and the design is capable of using the microwave landing system. Major emphasis is placed on the reduction of aircraft noise in communities surroundings airports, the reduction of fuel consumption, the reduction of the effects of adverse weather conditions on aircraft operations, and the efficient use of airspace in congested terminal areas. Attention is also given to the development of the capability to perform automatic flares from steep glide slopes to precise touchdown locations.

Feedback System Control Optimized Electrospinning for Fabrication of an Excellent Superhydrophobic Surface.

PubMed

Yang, Jian; Liu, Chuangui; Wang, Boqian; Ding, Xianting

2017-10-13

Superhydrophobic surface, as a promising micro/nano material, has tremendous applications in biological and artificial investigations. The electrohydrodynamics (EHD) technique is a versatile and effective method for fabricating micro- to nanoscale fibers and particles from a variety of materials. A combination of critical parameters, such as mass fraction, ratio of N, N-Dimethylformamide (DMF) to Tetrahydrofuran (THF), inner diameter of needle, feed rate, receiving distance, applied voltage as well as temperature, during electrospinning process, to determine the morphology of the electrospun membranes, which in turn determines the superhydrophobic property of the membrane. In this study, we applied a recently developed feedback system control (FSC) scheme for rapid identification of the optimal combination of these controllable parameters to fabricate superhydrophobic surface by one-step electrospinning method without any further modification. Within five rounds of experiments by testing totally forty-six data points, FSC scheme successfully identified an optimal parameter combination that generated electrospun membranes with a static water contact angle of 160 degrees or larger. Scanning electron microscope (SEM) imaging indicates that the FSC optimized surface attains unique morphology. The optimized setup introduced here therefore serves as a one-step, straightforward, and economic approach to fabricate superhydrophobic surface with electrospinning approach.

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

PubMed

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

Optimal Fault-Tolerant Control for Discrete-Time Nonlinear Strict-Feedback Systems Based on Adaptive Critic Design.

PubMed

Wang, Zhanshan; Liu, Lei; Wu, Yanming; Zhang, Huaguang

2018-06-01

This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highlight is the adaptive auxiliary signal of the actuator fault, which is designed to offset the effect of the fault. The considered systems are in strict-feedback forms and involve unknown nonlinear functions, which will result in the causal problem. To solve this problem, the original nonlinear systems are transformed into a novel system by employing the diffeomorphism theory. Besides, the action neural networks (ANNs) are utilized to approximate a predefined unknown function in the backstepping design procedure. Combined the strategic utility function and the ACD technique, a reinforcement learning algorithm is proposed to set up an optimal FTC, in which the critic neural networks (CNNs) provide an approximate structure of the cost function. In this case, it not only guarantees the stability of the systems, but also achieves the optimal control performance as well. In the end, two simulation examples are used to show the effectiveness of the proposed optimal FTC strategy.

Dynamics of gene expression with positive feedback to histone modifications at bivalent domains

NASA Astrophysics Data System (ADS)

Huang, Rongsheng; Lei, Jinzhi

2018-03-01

Experiments have shown that in embryonic stem cells, the promoters of many lineage-control genes contain “bivalent domains”, within which the nucleosomes possess both active (H3K4me3) and repressive (H3K27me3) marks. Such bivalent modifications play important roles in maintaining pluripotency in embryonic stem cells. Here, to investigate gene expression dynamics when there are regulations in bivalent histone modifications and random partition in cell divisions, we study how positive feedback to histone methylation/demethylation controls the transition dynamics of the histone modification patterns along with cell cycles. We constructed a computational model that includes dynamics of histone marks, three-stage chromatin state transitions, transcription and translation, feedbacks from protein product to enzymes to regulate the addition and removal of histone marks, and the inheritance of nucleosome state between cell cycles. The model reveals how dynamics of both nucleosome state transition and gene expression are dependent on the enzyme activities and feedback regulations. Results show that the combination of stochastic histone modification at each cell division and the deterministic feedback regulation work together to adjust the dynamics of chromatin state transition in stem cell regenerations.

Model-Based Optimal Experimental Design for Complex Physical Systems

DTIC Science & Technology

2015-12-03

for public release. magnitude reduction in estimator error required to make solving the exact optimal design problem tractable. Instead of using a naive...for designing a sequence of experiments uses suboptimal approaches: batch design that has no feedback, or greedy ( myopic ) design that optimally...approved for public release. Equation 1 is difficult to solve directly, but can be expressed in an equivalent form using the principle of dynamic programming

State-Dependent Riccati Equation Regulation of Systems with State and Control Nonlinearities

NASA Technical Reports Server (NTRS)

Beeler, Scott C.; Cox, David E. (Technical Monitor)

2004-01-01

The state-dependent Riccati equations (SDRE) is the basis of a technique for suboptimal feedback control of a nonlinear quadratic regulator (NQR) problem. It is an extension of the Riccati equation used for feedback control of linear problems, with the addition of nonlinearities in the state dynamics of the system resulting in a state-dependent gain matrix as the solution of the equation. In this paper several variations on the SDRE-based method will be considered for the feedback control problem with control nonlinearities. The control nonlinearities may result in complications in the numerical implementation of the control, which the different versions of the SDRE method must try to overcome. The control methods will be applied to three test problems and their resulting performance analyzed.

Nonlinear Feedback Controllers and Compensators: A State-Dependent Riccati Equation Approach

DTIC Science & Technology

2003-01-01

Nonlinear Feedback Controllers and Compensators: A State-Dependent Riccati Equation Approach H. T. Banks∗ B. M. Lewis † H. T. Tran‡ Department of...Mathematics Center for Research in Scientific Computation North Carolina State University Raleigh, NC 27695 Abstract State-dependent Riccati equation ...estimating the solution of the Hamilton- Jacobi-Bellman (HJB) equation can be found in a comprehensive review article [5]. Each of these ∗htbanks

Consensus positive position feedback control for vibration attenuation of smart structures

NASA Astrophysics Data System (ADS)

Omidi, Ehsan; Nima Mahmoodi, S.

2015-04-01

This paper presents a new network-based approach for active vibration control in smart structures. In this approach, a network with known topology connects collocated actuator/sensor elements of the smart structure to one another. Each of these actuators/sensors, i.e., agent or node, is enhanced by a separate multi-mode positive position feedback (PPF) controller. The decentralized PPF controlled agents collaborate with each other in the designed network, under a certain consensus dynamics. The consensus constraint forces neighboring agents to cooperate with each other such that the disagreement between the time-domain actuation of the agents is driven to zero. The controller output of each agent is calculated using state-space variables; hence, optimal state estimators are designed first for the proposed observer-based consensus PPF control. The consensus controller is numerically investigated for a flexible smart structure, i.e., a thin aluminum beam that is clamped at its both ends. Results demonstrate that the consensus law successfully imposes synchronization between the independently controlled agents, as the disagreements between the decentralized PPF controller variables converge to zero in a short time. The new consensus PPF controller brings extra robustness to vibration suppression in smart structures, where malfunctions of an agent can be compensated for by referencing the neighboring agents’ performance. This is demonstrated in the results by comparing the new controller with former centralized PPF approach.

Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds

NASA Technical Reports Server (NTRS)

Jardin, Matthew R.

2004-01-01

A computationally efficient algorithm for minimizing the flight time of an aircraft in a variable wind field has been invented. The algorithm, referred to as Neighboring Optimal Wind Routing (NOWR), is based upon neighboring-optimal-control (NOC) concepts and achieves minimum-time paths by adjusting aircraft heading according to wind conditions at an arbitrary number of wind measurement points along the flight route. The NOWR algorithm may either be used in a fast-time mode to compute minimum- time routes prior to flight, or may be used in a feedback mode to adjust aircraft heading in real-time. By traveling minimum-time routes instead of direct great-circle (direct) routes, flights across the United States can save an average of about 7 minutes, and as much as one hour of flight time during periods of strong jet-stream winds. The neighboring optimal routes computed via the NOWR technique have been shown to be within 1.5 percent of the absolute minimum-time routes for flights across the continental United States. On a typical 450-MHz Sun Ultra workstation, the NOWR algorithm produces complete minimum-time routes in less than 40 milliseconds. This corresponds to a rate of 25 optimal routes per second. The closest comparable optimization technique runs approximately 10 times slower. Airlines currently use various trial-and-error search techniques to determine which of a set of commonly traveled routes will minimize flight time. These algorithms are too computationally expensive for use in real-time systems, or in systems where many optimal routes need to be computed in a short amount of time. Instead of operating in real-time, airlines will typically plan a trajectory several hours in advance using wind forecasts. If winds change significantly from forecasts, the resulting flights will no longer be minimum-time. The need for a computationally efficient wind-optimal routing algorithm is even greater in the case of new air-traffic-control automation concepts. For air-traffic-control automation, thousands of wind-optimal routes may need to be computed and checked for conflicts in just a few minutes. These factors motivated the need for a more efficient wind-optimal routing algorithm.

When Antimicrobial Stewardship Isn′t Watching: The Educational Impact of Critical Care Prospective Audit and Feedback

PubMed Central

Fleming, Dimitra; Ali, Karim F.; Matelski, John; D'Sa, Ryan; Powis, Jeff

2016-01-01

Prospective audit and feedback (PAF) is an effective strategy to optimize antimicrobial use in the critical care setting, yet whether skills gained during PAF influence future antimicrobial prescribing is uncertain. This multisite study demonstrates that knowledge learned during PAF is translated and incorporated into the practice of critical care physicians even when not supported by an antimicrobial stewardship program. PMID:27382599

Operating Room of the Future: Advanced Technologies in Safe and Efficient Operating Rooms

DTIC Science & Technology

2008-10-01

fit” or compatibility with different tasks. Ideally, the optimal match between tasks and well-designed display alternatives will be self -apparent...hierarchical display environment. The FARO robot arm is used as an accurate and reliable tracker to control a virtual camera. The virtual camera pose is...in learning outcomes due to self -feedback, improvements in learning outcomes due to instructor feedback and synchronous versus asynchronous

Active vibration mitigation of distributed parameter, smart-type structures using Pseudo-Feedback Optimal Control (PFOC)

NASA Technical Reports Server (NTRS)

Patten, W. N.; Robertshaw, H. H.; Pierpont, D.; Wynn, R. H.

1989-01-01

A new, near-optimal feedback control technique is introduced that is shown to provide excellent vibration attenuation for those distributed parameter systems that are often encountered in the areas of aeroservoelasticity and large space systems. The technique relies on a novel solution methodology for the classical optimal control problem. Specifically, the quadratic regulator control problem for a flexible vibrating structure is first cast in a weak functional form that admits an approximate solution. The necessary conditions (first-order) are then solved via a time finite-element method. The procedure produces a low dimensional, algebraic parameterization of the optimal control problem that provides a rigorous basis for a discrete controller with a first-order like hold output. Simulation has shown that the algorithm can successfully control a wide variety of plant forms including multi-input/multi-output systems and systems exhibiting significant nonlinearities. In order to firmly establish the efficacy of the algorithm, a laboratory control experiment was implemented to provide planar (bending) vibration attenuation of a highly flexible beam (with a first clamped-free mode of approximately 0.5 Hz).

Perpetual extraction of work from a nonequilibrium dynamical system under Markovian feedback control

NASA Astrophysics Data System (ADS)

Kosugi, Taichi

2013-09-01

By treating both control parameters and dynamical variables as probabilistic variables, we develop a succinct theory of perpetual extraction of work from a generic classical nonequilibrium system subject to a heat bath via repeated measurements under a Markovian feedback control. It is demonstrated that a problem for perpetual extraction of work in a nonequilibrium system is reduced to a problem of Markov chain in the higher-dimensional phase space. We derive a version of the detailed fluctuation theorem, which was originally derived for classical nonequilibrium systems by Horowitz and Vaikuntanathan [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.82.061120 82, 061120 (2010)], in a form suitable for the analyses of perpetual extraction of work. Since our theory is formulated for generic dynamics of probability distribution function in phase space, its application to a physical system is straightforward. As simple applications of the theory, two exactly solvable models are analyzed. The one is a nonequilibrium two-state system and the other is a particle confined to a one-dimensional harmonic potential in thermal equilibrium. For the former example, it is demonstrated that the observer on the transitory steps to the stationary state can lose energy and that work larger than that achieved in the stationary state can be extracted. For the latter example, it is demonstrated that the optimal protocol for the extraction of work via repeated measurements can differ from that via a single measurement. The validity of our version of the detailed fluctuation theorem, which determines the upper bound of the expected work in the stationary state, is also confirmed for both examples. These observations provide useful insights into exploration for realistic modeling of a machine that extracts work from its environment.

Modal analysis and control of flexible manipulator arms. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Neto, O. M.

1974-01-01

The possibility of modeling and controlling flexible manipulator arms was examined. A modal approach was used for obtaining the mathematical model and control techniques. The arm model was represented mathematically by a state space description defined in terms of joint angles and mode amplitudes obtained from truncation on the distributed systems, and included the motion of a two link two joint arm. Three basic techniques were used for controlling the system: pole allocation with gains obtained from the rigid system with interjoint feedbacks, Simon-Mitter algorithm for pole allocation, and sensitivity analysis with respect to parameter variations. An improvement in arm bandwidth was obtained. Optimization of some geometric parameters was undertaken to maximize bandwidth for various payload sizes and programmed tasks. The controlled system is examined under constant gains and using the nonlinear model for simulations following a time varying state trajectory.

Vibration energy harvesting with polyphase AC transducers

NASA Astrophysics Data System (ADS)

McCullagh, James J.; Scruggs, Jeffrey T.; Asai, Takehiko

2016-04-01

Three-phase transduction affords certain advantages in the efficient electromechanical conversion of energy, especially at higher power scales. This paper considers the use of a three-phase electric machine for harvesting energy from vibrations. We consider the use of vector control techniques, which are common in the area of industrial electronics, for optimizing the feedback loops in a stochastically-excited energy harvesting system. To do this, we decompose the problem into two separate feedback loops for direct and quadrature current components, and illustrate how each might be separately optimized to maximize power output. In a simple analytical example, we illustrate how these techniques might be used to gain insight into the tradeoffs in the design of the electronic hardware and the choice of bus voltage.

Design of Distributed Controllers Seeking Optimal Power Flow Solutions Under Communication Constraints

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Simonetto, Andrea; Dhople, Sairaj

This paper focuses on power distribution networks featuring inverter-interfaced distributed energy resources (DERs), and develops feedback controllers that drive the DER output powers to solutions of time-varying AC optimal power flow (OPF) problems. Control synthesis is grounded on primal-dual-type methods for regularized Lagrangian functions, as well as linear approximations of the AC power-flow equations. Convergence and OPF-solution-tracking capabilities are established while acknowledging: i) communication-packet losses, and ii) partial updates of control signals. The latter case is particularly relevant since it enables asynchronous operation of the controllers where DER setpoints are updated at a fast time scale based on local voltagemore » measurements, and information on the network state is utilized if and when available, based on communication constraints. As an application, the paper considers distribution systems with high photovoltaic integration, and demonstrates that the proposed framework provides fast voltage-regulation capabilities, while enabling the near real-time pursuit of solutions of AC OPF problems.« less

Design of Distributed Controllers Seeking Optimal Power Flow Solutions under Communication Constraints: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Simonetto, Andrea; Dhople, Sairaj

This paper focuses on power distribution networks featuring inverter-interfaced distributed energy resources (DERs), and develops feedback controllers that drive the DER output powers to solutions of time-varying AC optimal power flow (OPF) problems. Control synthesis is grounded on primal-dual-type methods for regularized Lagrangian functions, as well as linear approximations of the AC power-flow equations. Convergence and OPF-solution-tracking capabilities are established while acknowledging: i) communication-packet losses, and ii) partial updates of control signals. The latter case is particularly relevant since it enables asynchronous operation of the controllers where DER setpoints are updated at a fast time scale based on local voltagemore » measurements, and information on the network state is utilized if and when available, based on communication constraints. As an application, the paper considers distribution systems with high photovoltaic integration, and demonstrates that the proposed framework provides fast voltage-regulation capabilities, while enabling the near real-time pursuit of solutions of AC OPF problems.« less

A Mathematical Formulation of the SCOLE Control Problem. Part 2: Optimal Compensator Design

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1988-01-01

The study initiated in Part 1 of this report is concluded and optimal feedback control (compensator) design for stability augmentation is considered, following the mathematical formulation developed in Part 1. Co-located (rate) sensors and (force and moment) actuators are assumed, and allowing for both sensor and actuator noise, stabilization is formulated as a stochastic regulator problem. Specializing the general theory developed by the author, a complete, closed form solution (believed to be new with this report) is obtained, taking advantage of the fact that the inherent structural damping is light. In particular, it is possible to solve in closed form the associated infinite-dimensional steady-state Riccati equations. The SCOLE model involves associated partial differential equations in a single space variable, but the compensator design theory developed is far more general since it is given in the abstract wave equation formulation. The results thus hold for any multibody system so long as the basic model is linear.

Recognition of the optical packet header for two channels utilizing the parallel reservoir computing based on a semiconductor ring laser

NASA Astrophysics Data System (ADS)

Bao, Xiurong; Zhao, Qingchun; Yin, Hongxi; Qin, Jie

2018-05-01

In this paper, an all-optical parallel reservoir computing (RC) system with two channels for the optical packet header recognition is proposed and simulated, which is based on a semiconductor ring laser (SRL) with the characteristic of bidirectional light paths. The parallel optical loops are built through the cross-feedback of the bidirectional light paths where every optical loop can independently recognize each injected optical packet header. Two input signals are mapped and recognized simultaneously by training all-optical parallel reservoir, which is attributed to the nonlinear states in the laser. The recognition of optical packet headers for two channels from 4 bits to 32 bits is implemented through the simulation optimizing system parameters and therefore, the optimal recognition error ratio is 0. Since this structure can combine with the wavelength division multiplexing (WDM) optical packet switching network, the wavelength of each channel of optical packet headers for recognition can be different, and a better recognition result can be obtained.

Effect of external viscous load on head movement

NASA Technical Reports Server (NTRS)

Nam, M.-H.; Lakshminarayanan, V.; Stark, L. W.

1984-01-01

Quantitative measurements of horizontal head rotation were obtained from normal human subjects intending to make 'time optimal' trajectories between targets. By mounting large, lightweight vanes on the head, viscous damping B, up to 15 times normal could be added to the usual mechanical load of the head. With the added viscosity, the head trajectory was slowed and of larger duration (as expected) since fixed and maximal (for that amplitude) muscle forces had to accelerate the added viscous load. This decreased acceleration and velocity and longer duration movement still ensued in spite of adaptive compensation; this provided evidence that quasi-'time optimal' movements do indeed employ maximal muscle forces. The adaptation to this added load was rapid. Then the 'adapted state' subjects produced changed trajectories. The adaptation depended in part on the differing detailed instructions given to the subjects. This differential adaptation provided evidence for the existence of preprogrammed controller signals, sensitive to intended criterion, and neurologically ballistic or open loop rather than modified by feedback from proprioceptors or vision.

Nonlinear zero-sum differential game analysis by singular perturbation methods

NASA Technical Reports Server (NTRS)

Sinar, J.; Farber, N.

1982-01-01

A class of nonlinear, zero-sum differential games, exhibiting time-scale separation properties, can be analyzed by singular-perturbation techniques. The merits of such an analysis, leading to an approximate game solution, as well as the 'well-posedness' of the formulation, are discussed. This approach is shown to be attractive for investigating pursuit-evasion problems; the original multidimensional differential game is decomposed to a 'simple pursuit' (free-stream) game and two independent (boundary-layer) optimal-control problems. Using multiple time-scale boundary-layer models results in a pair of uniformly valid zero-order composite feedback strategies. The dependence of suboptimal strategies on relative geometry and own-state measurements is demonstrated by a three dimensional, constant-speed example. For game analysis with realistic vehicle dynamics, the technique of forced singular perturbations and a variable modeling approach is proposed. Accuracy of the analysis is evaluated by comparison with the numerical solution of a time-optimal, variable-speed 'game of two cars' in the horizontal plane.

Geometric foundations of the theory of feedback equivalence

NASA Technical Reports Server (NTRS)

Hermann, R.

1987-01-01

A description of feedback control is presented within the context of differential equations, differential geometry, and Lie theory. Work related to the integration of differential geometry with the control techniques of feedback linearization is summarized. Particular attention is given to the application of the theory of vector field systems. Feedback invariants for control systems in state space form are also addressed.

Theoretical modeling of the dynamics of a semiconductor laser subject to double-reflector optical feedback

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bakry, A.; Abdulrhmann, S.; Ahmed, M., E-mail: mostafa.farghal@mu.edu.eg

2016-06-15

We theoretically model the dynamics of semiconductor lasers subject to the double-reflector feedback. The proposed model is a new modification of the time-delay rate equations of semiconductor lasers under the optical feedback to account for this type of the double-reflector feedback. We examine the influence of adding the second reflector to dynamical states induced by the single-reflector feedback: periodic oscillations, period doubling, and chaos. Regimes of both short and long external cavities are considered. The present analyses are done using the bifurcation diagram, temporal trajectory, phase portrait, and fast Fourier transform of the laser intensity. We show that adding themore » second reflector attracts the periodic and perioddoubling oscillations, and chaos induced by the first reflector to a route-to-continuous-wave operation. During this operation, the periodic-oscillation frequency increases with strengthening the optical feedback. We show that the chaos induced by the double-reflector feedback is more irregular than that induced by the single-reflector feedback. The power spectrum of this chaos state does not reflect information on the geometry of the optical system, which then has potential for use in chaotic (secure) optical data encryption.« less

A proposal for climate stability on H2-greenhouse planets

NASA Astrophysics Data System (ADS)

Abbot, D. S.

2015-12-01

A terrestrial planet in an orbit far outside of the standard habitable zone could maintain surface liquid water as a result of H2-H2 collision-induced absorption by a thick H2 atmosphere. Without a stabilizing climate feedback, however, habitability would be accidental and likely brief. We propose a stabilizing climate feedback for such a planet that requires only biological production of H2 to balance net loss to space that has some optimal temperature, and operates less efficiently at higher temperatures. A stable feedback is possible on such a planet through which a perturbation increasing temperature decreases H2 production, which decreases H2 greenhouse warming and therefore temperature. The potential of such a feedback makes H2-warmed planets more attractive astrobiological targets.

Providing rapid feedback to residents on their teaching skills: an educational strategy for contemporary trainees.

PubMed

Katz-Sidlow, Rachel J; Baer, Tamar G; Gershel, Jeffrey C

2016-03-20

The objective of this study was to assess the attitudes of contemporary residents toward receiving rapid feedback on their teaching skills from their medical student learners. Participants consisted of 20 residents in their second post-graduate training year. These residents facilitated 44 teaching sessions with medical students within our Resident-as-Teacher program. Structured, written feedback from students was returned to the resident within 3 days following each session. Residents completed a short survey about the utility of the feedback, whether they would make a change to future teaching sessions based on the feedback, and what specifically they might change. The survey utilized a 4-point scale ("Not helpful/likely=1" to "Very helpful/likely=4"), and allowed for one free-text response. Free-text responses were hand-coded and underwent qualitative analysis to identify themes. There were 182 student feedback encounters resulting from 44 teaching sessions. The survey response rate was 73% (32/44). Ninety-four percent of residents rated the rapid feedback as "very helpful," and 91% would "very likely" make a change to subsequent sessions based on student feedback. Residents' proposed changes included modifications to session content and/or their personal teaching style. Residents found that rapid feedback received from medical student learners was highly valuable to them in their roles as teachers. A rapid feedback strategy may facilitate an optimal educational environment for contemporary trainees.

Experiences of community pharmacists involved in the delivery of a specialist asthma service in Australia.

PubMed

Emmerton, Lynne M; Smith, Lorraine; LeMay, Kate S; Krass, Ines; Saini, Bandana; Bosnic-Anticevich, Sinthia Z; Reddel, Helen K; Burton, Deborah L; Stewart, Kay; Armour, Carol L

2012-06-18

The role of community pharmacists in disease state management has been mooted for some years. Despite a number of trials of disease state management services, there is scant literature into the engagement of, and with, pharmacists in such trials. This paper reports pharmacists' feedback as providers of a Pharmacy Asthma Management Service (PAMS), a trial coordinated across four academic research centres in Australia in 2009. We also propose recommendations for optimal involvement of pharmacists in academic research. Feedback about the pharmacists' experiences was sought via their participation in either a focus group or telephone interview (for those unable to attend their scheduled focus group) at one of three time points. A semi-structured interview guide focused discussion on the pharmacists' training to provide the asthma service, their interactions with health professionals and patients as per the service protocol, and the future for this type of service. Focus groups were facilitated by two researchers, and the individual interviews were shared between three researchers, with data transcribed verbatim and analysed manually. Of 93 pharmacists who provided the PAMS, 25 were involved in a focus group and seven via telephone interview. All pharmacists approached agreed to provide feedback. In general, the pharmacists engaged with both the service and research components, and embraced their roles as innovators in the trial of a new service. Some experienced challenges in the recruitment of patients into the service and the amount of research-related documentation, and collaborative patient-centred relationships with GPs require further attention. Specific service components, such as the spirometry, were well received by the pharmacists and their patients. Professional rewards included satisfaction from their enhanced practice, and pharmacists largely envisaged a future for the service. The PAMS provided pharmacists an opportunity to become involved in an innovative service delivery model, supported by the researchers, yet trained and empowered to implement the clinical service throughout the trial period and beyond. The balance between support and independence appeared crucial in the pharmacists' engagement with the trial. Their feedback was overwhelmingly positive, while useful suggestions were identified for future academic trials.

Experiences of community pharmacists involved in the delivery of a specialist asthma service in Australia

PubMed Central

2012-01-01

Background The role of community pharmacists in disease state management has been mooted for some years. Despite a number of trials of disease state management services, there is scant literature into the engagement of, and with, pharmacists in such trials. This paper reports pharmacists’ feedback as providers of a Pharmacy Asthma Management Service (PAMS), a trial coordinated across four academic research centres in Australia in 2009. We also propose recommendations for optimal involvement of pharmacists in academic research. Methods Feedback about the pharmacists’ experiences was sought via their participation in either a focus group or telephone interview (for those unable to attend their scheduled focus group) at one of three time points. A semi-structured interview guide focused discussion on the pharmacists’ training to provide the asthma service, their interactions with health professionals and patients as per the service protocol, and the future for this type of service. Focus groups were facilitated by two researchers, and the individual interviews were shared between three researchers, with data transcribed verbatim and analysed manually. Results Of 93 pharmacists who provided the PAMS, 25 were involved in a focus group and seven via telephone interview. All pharmacists approached agreed to provide feedback. In general, the pharmacists engaged with both the service and research components, and embraced their roles as innovators in the trial of a new service. Some experienced challenges in the recruitment of patients into the service and the amount of research-related documentation, and collaborative patient-centred relationships with GPs require further attention. Specific service components, such as the spirometry, were well received by the pharmacists and their patients. Professional rewards included satisfaction from their enhanced practice, and pharmacists largely envisaged a future for the service. Conclusions The PAMS provided pharmacists an opportunity to become involved in an innovative service delivery model, supported by the researchers, yet trained and empowered to implement the clinical service throughout the trial period and beyond. The balance between support and independence appeared crucial in the pharmacists’ engagement with the trial. Their feedback was overwhelmingly positive, while useful suggestions were identified for future academic trials. PMID:22709371

Employing quality control and feedback to the EQ-5D-5L valuation protocol to improve the quality of data collection.

PubMed

Purba, Fredrick Dermawan; Hunfeld, Joke A M; Iskandarsyah, Aulia; Fitriana, Titi Sahidah; Sadarjoen, Sawitri S; Passchier, Jan; Busschbach, Jan J V

2017-05-01

In valuing health states using generic questionnaires such as EQ-5D, there are unrevealed issues with the quality of the data collection. The aims were to describe the problems encountered during valuation and to evaluate a quality control report and subsequent retraining of interviewers in improving this valuation. Data from the first 266 respondents in an EQ-5D-5L valuation study were used. Interviewers were trained and answered questions regarding problems during these initial interviews. Thematic analysis was used, and individual feedback was provided. After completion of 98 interviews, a first quantitative quality control (QC) report was generated, followed by a 1-day retraining program. Subsequently individual feedback was also given on the basis of follow-up QCs. The Wilcoxon signed-rank test was used to assess improvements based on 7 indicators of quality as identified in the first QC and the QC conducted after a further 168 interviews. Interviewers encountered problems in recruiting respondents. Solutions provided were: optimization of the time of interview, the use of broader networks and the use of different scripts to explain the project's goals to respondents. For problems in interviewing process, solutions applied were: developing the technical and personal skills of the interviewers and stimulating the respondents' thought processes. There were also technical problems related to hardware, software and internet connections. There was an improvement in all 7 indicators of quality after the second QC. Training before and during a study, and individual feedback on the basis of a quantitative QC, can increase the validity of values obtained from generic questionnaires.

Interaction in Spoken Word Recognition Models: Feedback Helps.

PubMed

Magnuson, James S; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis.

Interaction in Spoken Word Recognition Models: Feedback Helps

PubMed Central

Magnuson, James S.; Mirman, Daniel; Luthra, Sahil; Strauss, Ted; Harris, Harlan D.

2018-01-01

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spoken word recognition, the latter view was apparently supported by simulations using the interactive activation model, TRACE, with and without feedback: as many words were recognized more quickly without feedback as were recognized faster with feedback, However, these simulations used only a small set of words and did not address a primary motivation for interaction: making a model robust in noise. We conducted simulations using hundreds of words, and found that the majority were recognized more quickly with feedback than without. More importantly, as we added noise to inputs, accuracy and recognition times were better with feedback than without. We follow these simulations with a critical review of recent arguments that online feedback in interactive activation models like TRACE is distinct from other potentially helpful forms of feedback. We conclude that in addition to providing the benefits demonstrated in our simulations, online feedback provides a plausible means of implementing putatively distinct forms of feedback, supporting the interactive activation hypothesis. PMID:29666593

Robust decentralised stabilisation of uncertain large-scale interconnected nonlinear descriptor systems via proportional plus derivative feedback

NASA Astrophysics Data System (ADS)

Li, Jian; Zhang, Qingling; Ren, Junchao; Zhang, Yanhao

2017-10-01

This paper studies the problem of robust stability and stabilisation for uncertain large-scale interconnected nonlinear descriptor systems via proportional plus derivative state feedback or proportional plus derivative output feedback. The basic idea of this work is to use the well-known differential mean value theorem to deal with the nonlinear model such that the considered nonlinear descriptor systems can be transformed into linear parameter varying systems. By using a parameter-dependent Lyapunov function, a decentralised proportional plus derivative state feedback controller and decentralised proportional plus derivative output feedback controller are designed, respectively such that the closed-loop system is quadratically normal and quadratically stable. Finally, a hypersonic vehicle practical simulation example and numerical example are given to illustrate the effectiveness of the results obtained in this paper.

Generalized fast feedback system in the SLC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hendrickson, L.; Allison, S.; Gromme, T.

A generalized fast feedback system has been developed to stabilize beams at various locations in the SLC. The system is designed to perform measurements and change actuator settings to control beam states such as position, angle and energy on a pulse to pulse basis. The software design is based on the state space formalism of digital control theory. The system is database-driven, facilitating the addition of new loops without requiring additional software. A communications system, KISNet, provides fast communications links between microprocessors for feedback loops which involve multiple micros. Feedback loops have been installed in seventeen locations throughout the SLCmore » and have proven to be invaluable in stabilizing the machine.« less