Consideration of computer limitations in implementing on-line controls. M.S. Thesis

NASA Technical Reports Server (NTRS)

Roberts, G. K.

1976-01-01

A formal statement of the optimal control problem which includes the interval of dicretization as an optimization parameter, and extend this to include selection of a control algorithm as part of the optimization procedure, is formulated. The performance of the scalar linear system depends on the discretization interval. Discrete-time versions of the output feedback regulator and an optimal compensator, and the use of these results in presenting an example of a system for which fast partial-state-feedback control better minimizes a quadratic cost than either a full-state feedback control or a compensator, are developed.

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,

Feedback control for manipulating magnetization in spin-exchange optical pumping system

NASA Astrophysics Data System (ADS)

Zhang, Ke; Li, Jun; Jiang, Min; Zhao, Nan; Peng, XinHua

2018-08-01

Control of magnetization plays an important role in the scientific and technological field of manipulating spin systems. In this work, we study the problem of manipulating nuclear magnetization in the spin-exchange optical pumping system, including accelerating the recovery of nuclear polarization and fixing it on a specific desired state. A real-time feedback control strategy is exploited here. We have also done some numerical simulations, with the results clearly demonstrating the effectiveness of our method, that the nuclear magnetization is able to be driven towards the equilibrium state at a much faster speed and also can be stabilized to a target state. We expect that our feedback control method can find applications in gyro experiments.

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.

Rapid control and feedback rates enhance neuroprosthetic control

PubMed Central

Shanechi, Maryam M.; Orsborn, Amy L.; Moorman, Helene G.; Gowda, Suraj; Dangi, Siddharth; Carmena, Jose M.

2017-01-01

Brain-machine interfaces (BMI) create novel sensorimotor pathways for action. Much as the sensorimotor apparatus shapes natural motor control, the BMI pathway characteristics may also influence neuroprosthetic control. Here, we explore the influence of control and feedback rates, where control rate indicates how often motor commands are sent from the brain to the prosthetic, and feedback rate indicates how often visual feedback of the prosthetic is provided to the subject. We developed a new BMI that allows arbitrarily fast control and feedback rates, and used it to dissociate the effects of each rate in two monkeys. Increasing the control rate significantly improved control even when feedback rate was unchanged. Increasing the feedback rate further facilitated control. We also show that our high-rate BMI significantly outperformed state-of-the-art methods due to higher control and feedback rates, combined with a different point process mathematical encoding model. Our BMI paradigm can dissect the contribution of different elements in the sensorimotor pathway, providing a unique tool for studying neuroprosthetic control mechanisms. PMID:28059065

Rapid control and feedback rates enhance neuroprosthetic control

NASA Astrophysics Data System (ADS)

Shanechi, Maryam M.; Orsborn, Amy L.; Moorman, Helene G.; Gowda, Suraj; Dangi, Siddharth; Carmena, Jose M.

2017-01-01

Brain-machine interfaces (BMI) create novel sensorimotor pathways for action. Much as the sensorimotor apparatus shapes natural motor control, the BMI pathway characteristics may also influence neuroprosthetic control. Here, we explore the influence of control and feedback rates, where control rate indicates how often motor commands are sent from the brain to the prosthetic, and feedback rate indicates how often visual feedback of the prosthetic is provided to the subject. We developed a new BMI that allows arbitrarily fast control and feedback rates, and used it to dissociate the effects of each rate in two monkeys. Increasing the control rate significantly improved control even when feedback rate was unchanged. Increasing the feedback rate further facilitated control. We also show that our high-rate BMI significantly outperformed state-of-the-art methods due to higher control and feedback rates, combined with a different point process mathematical encoding model. Our BMI paradigm can dissect the contribution of different elements in the sensorimotor pathway, providing a unique tool for studying neuroprosthetic control mechanisms.

Flatness-based control and Kalman filtering for a continuous-time macroeconomic model

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Ghosh, T.; Busawon, K.; Binns, R.

2017-11-01

The article proposes flatness-based control for a nonlinear macro-economic model of the UK economy. The differential flatness properties of the model are proven. This enables to introduce a transformation (diffeomorphism) of the system's state variables and to express the state-space description of the model in the linear canonical (Brunowsky) form in which both the feedback control and the state estimation problem can be solved. For the linearized equivalent model of the macroeconomic system, stabilizing feedback control can be achieved using pole placement methods. Moreover, to implement stabilizing feedback control of the system by measuring only a subset of its state vector elements the Derivative-free nonlinear Kalman Filter is used. This consists of the Kalman Filter recursion applied on the linearized equivalent model of the financial system and of an inverse transformation that is based again on differential flatness theory. The asymptotic stability properties of the control scheme are confirmed.

Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with time delays.

PubMed

Tong, Shao Cheng; Li, Yong Ming; Zhang, Hua-Guang

2011-07-01

In this paper, two adaptive neural network (NN) decentralized output feedback control approaches are proposed for a class of uncertain nonlinear large-scale systems with immeasurable states and unknown time delays. Using NNs to approximate the unknown nonlinear functions, an NN state observer is designed to estimate the immeasurable states. By combining the adaptive backstepping technique with decentralized control design principle, an adaptive NN decentralized output feedback control approach is developed. In order to overcome the problem of "explosion of complexity" inherent in the proposed control approach, the dynamic surface control (DSC) technique is introduced into the first adaptive NN decentralized control scheme, and a simplified adaptive NN decentralized output feedback DSC approach is developed. It is proved that the two proposed control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the observer errors and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approaches.

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.

Iterative LQG Controller Design Through Closed-Loop Identification

NASA Technical Reports Server (NTRS)

Hsiao, Min-Hung; Huang, Jen-Kuang; Cox, David E.

1996-01-01

This paper presents an iterative Linear Quadratic Gaussian (LQG) controller design approach for a linear stochastic system with an uncertain open-loop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQC controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.

Study to eliminate ground resonance using active controls

NASA Technical Reports Server (NTRS)

Straub, F. K.

1984-01-01

The effectiveness of active control blade feathering in increasing rotor body damping and the possibility to eliminate ground resonance instabilities were investigated. An analytical model representing rotor flapping and lead-lag degrees of freedom and body pitch, roll, longitudinal and lateral motion is developed. Active control blade feathering is implemented as state variable feedback through a conventional swashplate. The influence of various feedback states, feedback gain, and weighting between the cyclic controls is studied through stability and response analyses. It is shown that blade cyclic inplane motion, roll rate and roll acceleration feedback can add considerable damping to the system and eliminate ground resonance instabilities, which the feedback phase is also a powerful parameter, if chosen properly, it maximizes augmentation of the inherent regressing lag mode damping. It is shown that rotor configuration parameters, like blade root hinge offset, flapping stiffness, and precone considerably influence the control effectiveness. It is found that active control is particularly powerful for hingeless and bearingless rotor systems.

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.

Investigation, development and application of optimal output feedback theory. Volume 2: Development of an optimal, limited state feedback outer-loop digital flight control system for 3-D terminal area operation

NASA Technical Reports Server (NTRS)

Broussard, J. R.; Halyo, N.

1984-01-01

This report contains the development of a digital outer-loop three dimensional radio navigation (3-D RNAV) flight control system for a small commercial jet transport. The outer-loop control system is designed using optimal stochastic limited state feedback techniques. Options investigated using the optimal limited state feedback approach include integrated versus hierarchical control loop designs, 20 samples per second versus 5 samples per second outer-loop operation and alternative Type 1 integration command errors. Command generator tracking techniques used in the digital control design enable the jet transport to automatically track arbitrary curved flight paths generated by waypoints. The performance of the design is demonstrated using detailed nonlinear aircraft simulations in the terminal area, frequency domain multi-input sigma plots, frequency domain single-input Bode plots and closed-loop poles. The response of the system to a severe wind shear during a landing approach is also presented.

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

Solid state light source driver establishing buck or boost operation

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

Palmer, Fred

A solid state light source driver circuit that operates in either a buck convertor or a boost convertor configuration is provided. The driver circuit includes a controller, a boost switch circuit and a buck switch circuit, each coupled to the controller, and a feedback circuit, coupled to the light source. The feedback circuit provides feedback to the controller, representing a DC output of the driver circuit. The controller controls the boost switch circuit and the buck switch circuit in response to the feedback signal, to regulate current to the light source. The controller places the driver circuit in its boostmore » converter configuration when the DC output is less than a rectified AC voltage coupled to the driver circuit at an input node. The controller places the driver circuit in its buck converter configuration when the DC output is greater than the rectified AC voltage at the input node.« less

Stabilization of an inverted pendulum-cart system by fractional PI-state feedback.

PubMed

Bettayeb, M; Boussalem, C; Mansouri, R; Al-Saggaf, U M

2014-03-01

This paper deals with pole placement PI-state feedback controller design to control an integer order system. The fractional aspect of the control law is introduced by a dynamic state feedback as u(t)=K(p)x(t)+K(I)I(α)(x(t)). The closed loop characteristic polynomial is thus fractional for which the roots are complex to calculate. The proposed method allows us to decompose this polynomial into a first order fractional polynomial and an integer order polynomial of order n-1 (n being the order of the integer system). This new stabilization control algorithm is applied for an inverted pendulum-cart test-bed, and the effectiveness and robustness of the proposed control are examined by experiments. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Shock and Vibration Control of a Golf-Swing Robot at Impacting the Ball

NASA Astrophysics Data System (ADS)

Hoshino, Yohei; Kobayashi, Yukinori

A golf swing robot is a kind of fast motion manipulator with a flexible link. A robot manipulator is greatly affected by Corioli's and centrifugal forces during fast motion. Nonlinearity due to these forces can have an adverse effect on the performance of feedback control. In the same way, ordinary state observers of a linear system cannot accurately estimate the states of nonlinear systems. This paper uses a state observer that considers disturbances to improve the performance of state estimation and feedback control. A mathematical model of the golf robot is derived by Hamilton's principle. A linear quadratic regulator (LQR) that considers the vibration of the club shaft is used to stop the robot during the follow-through action. The state observer that considers disturbances estimates accurate state variables when the disturbances due to Corioli's and centrifugal forces, and impact forces work on the robot. As a result, the performance of the state feedback control is improved. The study compares the results of the numerical simulations with experimental results.

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.

Incremental passivity and output regulation for switched nonlinear systems

NASA Astrophysics Data System (ADS)

Pang, Hongbo; Zhao, Jun

2017-10-01

This paper studies incremental passivity and global output regulation for switched nonlinear systems, whose subsystems are not required to be incrementally passive. A concept of incremental passivity for switched systems is put forward. First, a switched system is rendered incrementally passive by the design of a state-dependent switching law. Second, the feedback incremental passification is achieved by the design of a state-dependent switching law and a set of state feedback controllers. Finally, we show that once the incremental passivity for switched nonlinear systems is assured, the output regulation problem is solved by the design of global nonlinear regulator controllers comprising two components: the steady-state control and the linear output feedback stabilising controllers, even though the problem for none of subsystems is solvable. Two examples are presented to illustrate the effectiveness of the proposed approach.

State feedback integral control for a rotary direct drive servo valve using a Lyapunov function approach.

PubMed

Yu, Jue; Zhuang, Jian; Yu, Dehong

2015-01-01

This paper concerns a state feedback integral control using a Lyapunov function approach for a rotary direct drive servo valve (RDDV) while considering parameter uncertainties. Modeling of this RDDV servovalve reveals that its mechanical performance is deeply influenced by friction torques and flow torques; however, these torques are uncertain and mutable due to the nature of fluid flow. To eliminate load resistance and to achieve satisfactory position responses, this paper develops a state feedback control that integrates an integral action and a Lyapunov function. The integral action is introduced to address the nonzero steady-state error; in particular, the Lyapunov function is employed to improve control robustness by adjusting the varying parameters within their value ranges. This new controller also has the advantages of simple structure and ease of implementation. Simulation and experimental results demonstrate that the proposed controller can achieve higher control accuracy and stronger robustness. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Servo control of an optical trap.

PubMed

Wulff, Kurt D; Cole, Daniel G; Clark, Robert L

2007-08-01

A versatile optical trap has been constructed to control the position of trapped objects and ultimately to apply specified forces using feedback control. While the design, development, and use of optical traps has been extensive and feedback control has played a critical role in pushing the state of the art, few comprehensive examinations of feedback control of optical traps have been undertaken. Furthermore, as the requirements are pushed to ever smaller distances and forces, the performance of optical traps reaches limits. It is well understood that feedback control can result in both positive and negative effects in controlled systems. We give an analysis of the trapping limits as well as introducing an optical trap with a feedback control scheme that dramatically improves an optical trap's sensitivity at low frequencies.

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

NASA Astrophysics Data System (ADS)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

Model-Free control performance improvement using virtual reference feedback tuning and reinforcement Q-learning

NASA Astrophysics Data System (ADS)

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

2017-04-01

This paper proposes the combination of two model-free controller tuning techniques, namely linear virtual reference feedback tuning (VRFT) and nonlinear state-feedback Q-learning, referred to as a new mixed VRFT-Q learning approach. VRFT is first used to find stabilising feedback controller using input-output experimental data from the process in a model reference tracking setting. Reinforcement Q-learning is next applied in the same setting using input-state experimental data collected under perturbed VRFT to ensure good exploration. The Q-learning controller learned with a batch fitted Q iteration algorithm uses two neural networks, one for the Q-function estimator and one for the controller, respectively. The VRFT-Q learning approach is validated on position control of a two-degrees-of-motion open-loop stable multi input-multi output (MIMO) aerodynamic system (AS). Extensive simulations for the two independent control channels of the MIMO AS show that the Q-learning controllers clearly improve performance over the VRFT controllers.

Adaptive Nonlinear Tracking Control of Kinematically Redundant Robot Manipulators with Sub-Task Extensions

DTIC Science & Technology

2005-01-01

C. Hughes, Spacecraft Attitude Dynamics, New York, NY: Wiley, 1994. [8] H. K. Khalil, “Adaptive Output Feedback Control of Non- linear Systems...Closed-Loop Manipulator Control Using Quaternion Feedback ”, IEEE Trans. Robotics and Automation, Vol. 4, No. 4, pp. 434-440, (1988). [23] E...full-state feedback quaternion based controller de- veloped in [5] and focuses on the design of a general sub-task controller. This sub-task controller

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

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

Leader-following control of multiple nonholonomic systems over directed communication graphs

NASA Astrophysics Data System (ADS)

Dong, Wenjie; Djapic, Vladimir

2016-06-01

This paper considers the leader-following control problem of multiple nonlinear systems with directed communication topology and a leader. If the state of each system is measurable, distributed state feedback controllers are proposed using neighbours' state information with the aid of Lyapunov techniques and properties of Laplacian matrix for time-invariant communication graph and time-varying communication graph. It is shown that the state of each system exponentially converges to the state of a leader. If the state of each system is not measurable, distributed observer-based output feedback control laws are proposed. As an application of the proposed results, formation control of wheeled mobile robots is studied. The simulation results show the effectiveness of the proposed results.

Sensor Data Fusion for Body State Estimation in a Bipedal Robot and Its Feedback Control Application for Stable Walking

PubMed Central

Chen, Ching-Pei; Chen, Jing-Yi; Huang, Chun-Kai; Lu, Jau-Ching; Lin, Pei-Chun

2015-01-01

We report on a sensor data fusion algorithm via an extended Kalman filter for estimating the spatial motion of a bipedal robot. Through fusing the sensory information from joint encoders, a 6-axis inertial measurement unit and a 2-axis inclinometer, the robot’s body state at a specific fixed position can be yielded. This position is also equal to the CoM when the robot is in the standing posture suggested by the detailed CAD model of the robot. In addition, this body state is further utilized to provide sensory information for feedback control on a bipedal robot with walking gait. The overall control strategy includes the proposed body state estimator as well as the damping controller, which regulates the body position state of the robot in real-time based on instant and historical position tracking errors. Moreover, a posture corrector for reducing unwanted torque during motion is addressed. The body state estimator and the feedback control structure are implemented in a child-size bipedal robot and the performance is experimentally evaluated. PMID:25734644

Microgravity vibration isolation: Optimal preview and feedback control

NASA Technical Reports Server (NTRS)

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

1992-01-01

In order to achieve adequate low-frequency vibration isolation for certain space experiments an active control is needed, due to inherent passive-isolator limitations. Proposed here are five possible state-space models for a one-dimensional vibration isolation system with a quadratic performance index. The five models are subsets of a general set of nonhomogeneous state space equations which includes disturbance terms. An optimal control is determined, using a differential equations approach, for this class of problems. This control is expressed in terms of constant, Linear Quadratic Regulator (LQR) feedback gains and constant feedforward (preview) gains. The gains can be easily determined numerically. They result in a robust controller and offers substantial improvements over a control that uses standard LQR feedback alone.

Closed-Loop Control of Vortex Formation in Separated Flows

NASA Technical Reports Server (NTRS)

Colonius, Tim; Joe, Won Tae; MacMynowski, Doug; Rowley, Clancy; Taira, Sam; Ahuja, Sunil

2010-01-01

In order to phase lock the flow at the desired shedding cycle, particularly at Phi,best, We designed a feedback compensator. (Even though the open-loop forcing at Wf below Wn can lead to phase-locked limit cycles with a high average lift,) This feedback controller resulted in the phase-locked limit cycles that the open-loop control could not achieve for alpha=30 and 40 Particularly for alpha=40, the feedback was able to stabilize the limit cycle that was not stable with any of the open-loop periodic forcing. This results in stable phase-locked limit cycles for a larger range of forcing frequencies than the open-loop control. Also, it was shown that the feedback achieved the high-lift unsteady flow states that open-loop control could not sustain even after the states have been achieved for a long period of time.

Rotor-state feedback in the design of flight control laws for a hovering helicopter

NASA Technical Reports Server (NTRS)

Takahashi, Marc D.

1994-01-01

The use of rigid-body and rotor-state feedback gains in the design of helicopter flight control laws was investigated analytically on a blade element, articulated rotor, helicopter model. The study was conducted while designing a control law to meet an existing military rotorcraft handling qualities design specification (ADS-33C) in low-speed flight. A systematic approach to meet this specification was developed along with an assessment of the function of these gains in the feedback loops. Using the results of this assessment, the pitch and roll crossover behavior was easily modified by adjusting the body attitude and rotor-flap feedback gains. Critical to understanding the feedback gains is that the roll and pitch rate dynamics each have second-order behavior, not the classic first-order behavior, which arises from a quasi-static rotor, six degree-of-freedom model.

Using Arrays of Microelectrodes Implanted in Residual Peripheral Nerves to Provide Dextrous Control of, and Modulated Sensory Feedback from, a Hand Prosthesis

DTIC Science & Technology

2015-10-01

Modulated Sensory Feedback from, a Hand Prosthesis PRINCIPAL INVESTIGATOR: Bradley Greger, PhD CONTRACTING ORGANIZATION: Arizona State University...Residual Peripheral Nerves to Provide Dextrous Control of, and Modulated Sensory Feedback from, a Hand Prosthesis 5a. CONTRACT NUMBER 5b. GRANT...Peripheral Nerve Interface, Prosthetic Hand, Neural Prosthesis , Sensory Feedback, Micro-stimulation, Electrophysiology, Action Potentials, Micro

Linear-Quadratic-Gaussian Regulator Developed for a Magnetic Bearing

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.

2002-01-01

Linear-Quadratic-Gaussian (LQG) control is a modern state-space technique for designing optimal dynamic regulators. It enables us to trade off regulation performance and control effort, and to take into account process and measurement noise. The Structural Mechanics and Dynamics Branch at the NASA Glenn Research Center has developed an LQG control for a fault-tolerant magnetic bearing suspension rig to optimize system performance and to reduce the sensor and processing noise. The LQG regulator consists of an optimal state-feedback gain and a Kalman state estimator. The first design step is to seek a state-feedback law that minimizes the cost function of regulation performance, which is measured by a quadratic performance criterion with user-specified weighting matrices, and to define the tradeoff between regulation performance and control effort. The next design step is to derive a state estimator using a Kalman filter because the optimal state feedback cannot be implemented without full state measurement. Since the Kalman filter is an optimal estimator when dealing with Gaussian white noise, it minimizes the asymptotic covariance of the estimation error.

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

Differential flatness properties and adaptive control of the hypothalamic-pituitary-adrenal axis model

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos

2016-12-01

It is shown that the model of the hypothalamic-pituitary-adrenal gland axis is a differentially flat one and this permits to transform it to the so-called linear canonical form. For the new description of the system's dynamics the transformed control inputs contain unknown terms which depend on the system's parameters. To identify these terms an adaptive fuzzy approximator is used in the control loop. Thus an adaptive fuzzy control scheme is implemented in which the unknown or unmodeled system dynamics is approximated by neurofuzzy networks and next this information is used by a feedback controller that makes the state variables (CRH - corticotropin releasing hormone, adenocortocotropic hormone - ACTH, cortisol) of the hypothalamic-pituitary-adrenal gland axis model converge to the desirable levels (setpoints). This adaptive control scheme is exclusively implemented with the use of output feedback, while the state vector elements which are not directly measured are estimated with the use of a state observer that operates in the control loop. The learning rate of the adaptive fuzzy system is suitably computed from Lyapunov analysis, so as to assure that both the learning procedure for the unknown system's parameters, the dynamics of the observer and the dynamics of the control loop will remain stable. The performed Lyapunov stability analysis depends on two Riccati equations, one associated with the feedback controller and one associated with the state observer. Finally, it is proven that for the control scheme that comprises the feedback controller, the state observer and the neurofuzzy approximator, an H-infinity tracking performance can be succeeded.

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.

Microprocessor based implementation of attitude and shape control of large space structures

NASA Technical Reports Server (NTRS)

Reddy, A. S. S. R.

1984-01-01

The feasibility of off the shelf eight bit and 16 bit microprocessors to implement linear state variable feedback control laws and assessing the real time response to spacecraft dynamics is studied. The complexity of the dynamic model is described along with the appropriate software. An experimental setup of a beam, microprocessor system for implementing the control laws and the needed generalized software to implement any state variable feedback control system is included.

A Design Method for a State Feedback Microcomputer Controller of a Wide Bandwidth Analog Plant.

DTIC Science & Technology

1983-12-01

Il IIIz NAVAL POSTGRADUATE SCHOOLMonterey, California THESIS A A DESIGN METHOD FOR A STATE FEEDBACK MICROCOMPUTER CONTROLLER OF A WIDE BANDWIDTH...of a microcomputer regulator, continuous or discrete method can be applied. The o:bjective of this thesis is to provide a continuous controller ...estimation and control type problem. In this thesis , a wide bandwidth analog computer system is chosen as the plant so that the effect of transport

Reinforcement learning for stabilizing an inverted pendulum naturally leads to intermittent feedback control as in human quiet standing.

PubMed

Michimoto, Kenjiro; Suzuki, Yasuyuki; Kiyono, Ken; Kobayashi, Yasushi; Morasso, Pietro; Nomura, Taishin

2016-08-01

Intermittent feedback control for stabilizing human upright stance is a promising strategy, alternative to the standard time-continuous stiffness control. Here we show that such an intermittent controller can be established naturally through reinforcement learning. To this end, we used a single inverted pendulum model of the upright posture and a very simple reward function that gives a certain amount of punishments when the inverted pendulum falls or changes its position in the state space. We found that the acquired feedback controller exhibits hallmarks of the intermittent feedback control strategy, namely the action of the feedback controller is switched-off intermittently when the state of the pendulum is located near the stable manifold of the unstable saddle-type upright equilibrium of the inverted pendulum with no active control: this action provides an opportunity to exploit transiently converging dynamics toward the unstable upright position with no help of the active feedback control. We then speculate about a possible physiological mechanism of such reinforcement learning, and suggest that it may be related to the neural activity in the pedunculopontine tegmental nucleus (PPN) of the brainstem. This hypothesis is supported by recent evidence indicating that PPN might play critical roles for generation and regulation of postural tonus, reward prediction, as well as postural instability in patients with Parkinson's disease.

Output-Feedback Model Predictive Control of a Pasteurization Pilot Plant based on an LPV model

NASA Astrophysics Data System (ADS)

Karimi Pour, Fatemeh; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-01-01

This paper presents a model predictive control (MPC) of a pasteurization pilot plant based on an LPV model. Since not all the states are measured, an observer is also designed, which allows implementing an output-feedback MPC scheme. However, the model of the plant is not completely observable when augmented with the disturbance models. In order to solve this problem, the following strategies are used: (i) the whole system is decoupled into two subsystems, (ii) an inner state-feedback controller is implemented into the MPC control scheme. A real-time example based on the pasteurization pilot plant is simulated as a case study for testing the behavior of the approaches.

Perturbed cooperative-state feedback strategy for model predictive networked control of interconnected systems.

PubMed

Tran, Tri; Ha, Q P

2018-01-01

A perturbed cooperative-state feedback (PSF) strategy is presented for the control of interconnected systems in this paper. The subsystems of an interconnected system can exchange data via the communication network that has multiple connection topologies. The PSF strategy can resolve both issues, the sensor data losses and the communication network breaks, thanks to the two components of the control including a cooperative-state feedback and a perturbation variable, e.g., u i =K ij x j +w i . The PSF is implemented in a decentralized model predictive control scheme with a stability constraint and a non-monotonic storage function (ΔV(x(k))≥0), derived from the dissipative systems theory. Numerical simulation for the automatic generation control problem in power systems is studied to illustrate the effectiveness of the presented PSF strategy. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Fuzzy Adaptive Output Feedback Control of Uncertain Nonlinear Systems With Prescribed Performance.

PubMed

Zhang, Jin-Xi; Yang, Guang-Hong

2018-05-01

This paper investigates the tracking control problem for a family of strict-feedback systems in the presence of unknown nonlinearities and immeasurable system states. A low-complexity adaptive fuzzy output feedback control scheme is proposed, based on a backstepping method. In the control design, a fuzzy adaptive state observer is first employed to estimate the unmeasured states. Then, a novel error transformation approach together with a new modification mechanism is introduced to guarantee the finite-time convergence of the output error to a predefined region and ensure the closed-loop stability. Compared with the existing methods, the main advantages of our approach are that: 1) without using extra command filters or auxiliary dynamic surface control techniques, the problem of explosion of complexity can still be addressed and 2) the design procedures are independent of the initial conditions. Finally, two practical examples are performed to further illustrate the above theoretic findings.

Delayed feedback control in quantum transport.

PubMed

Emary, Clive

2013-09-28

Feedback control in quantum transport has been predicted to give rise to several interesting effects, among them quantum state stabilization and the realization of a mesoscopic Maxwell's daemon. These results were derived under the assumption that control operations on the system are affected instantaneously after the measurement of electronic jumps through it. In this contribution, I describe how to include a delay between detection and control operation in the master equation theory of feedback-controlled quantum transport. I investigate the consequences of delay for the state stabilization and Maxwell's daemon schemes. Furthermore, I describe how delay can be used as a tool to probe coherent oscillations of electrons within a transport system and how this formalism can be used to model finite detector bandwidth.

Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, D.; Peng, Z. H.

2017-09-01

Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

Reduced-order dynamic output feedback control of uncertain discrete-time Markov jump linear systems

NASA Astrophysics Data System (ADS)

Morais, Cecília F.; Braga, Márcio F.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.

2017-11-01

This paper deals with the problem of designing reduced-order robust dynamic output feedback controllers for discrete-time Markov jump linear systems (MJLS) with polytopic state space matrices and uncertain transition probabilities. Starting from a full order, mode-dependent and polynomially parameter-dependent dynamic output feedback controller, sufficient linear matrix inequality based conditions are provided for the existence of a robust reduced-order dynamic output feedback stabilising controller with complete, partial or none mode dependency assuring an upper bound to the ? or the ? norm of the closed-loop system. The main advantage of the proposed method when compared to the existing approaches is the fact that the dynamic controllers are exclusively expressed in terms of the decision variables of the problem. In other words, the matrices that define the controller realisation do not depend explicitly on the state space matrices associated with the modes of the MJLS. As a consequence, the method is specially suitable to handle order reduction or cluster availability constraints in the context of ? or ? dynamic output feedback control of discrete-time MJLS. Additionally, as illustrated by means of numerical examples, the proposed approach can provide less conservative results than other conditions in the literature.

Feedback quantum control of molecular electronic population transfer

NASA Astrophysics Data System (ADS)

Bardeen, Christopher J.; Yakovlev, Vladislav V.; Wilson, Kent R.; Carpenter, Scott D.; Weber, Peter M.; Warren, Warren S.

1997-11-01

Feedback quantum control, where the sample `teaches' a computer-controlled arbitrary lightform generator to find the optimal light field, is experimentally demonstrated for a molecular system. Femtosecond pulses tailored by a computer-controlled acousto-optic pulse shaper excite fluorescence from laser dye molecules in solution. Fluorescence and laser power are monitored, and the computer uses the experimental data and a genetic algorithm to optimize population transfer from ground to first excited state. Both efficiency (the ratio of excited state population to laser energy) and effectiveness (total excited state population) are optimized. Potential use as an `automated theory tester' is discussed.

Cooperative Solutions in Multi-Person Quadratic Decision Problems: Finite-Horizon and State-Feedback Cost-Cumulant Control Paradigm

DTIC Science & Technology

2007-01-01

CONTRACT NUMBER Problems: Finite -Horizon and State-Feedback Cost-Cumulant Control Paradigm (PREPRINT) 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...cooperative cost-cumulant control regime for the class of multi-person single-objective decision problems characterized by quadratic random costs and... finite -horizon integral quadratic cost associated with a linear stochastic system . Since this problem formation is parameterized by the number of cost

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

Response of microchip solid-state laser to external frequency-shifted feedback and its applications

PubMed Central

Tan, Yidong; Zhang, Shulian; Zhang, Song; Zhang, Yongqing; Liu, Ning

2013-01-01

The response of the microchip solid-state Nd:YAG laser, which is subjected to external frequency-shifted feedback, is experimentally and theoretically analysed. The continuous weak response of the laser to the phase and amplitude of the feedback light is achieved by controlling the feedback power level, and this system can be used to achieve contact-free measurement of displacement, vibration, liquid evaporation and thermal expansion with nanometre accuracy in common room conditions without precise environmental control. Furthermore, a strong response, including chaotic harmonic and parametric oscillation, is observed, and the spectrum of this response, as examined by a frequency-stabilised Nd:YAG laser, indicates laser spectral linewidth broadening. PMID:24105389

Response of microchip solid-state laser to external frequency-shifted feedback and its applications.

PubMed

Tan, Yidong; Zhang, Shulian; Zhang, Song; Zhang, Yongqing; Liu, Ning

2013-10-09

The response of the microchip solid-state Nd:YAG laser, which is subjected to external frequency-shifted feedback, is experimentally and theoretically analysed. The continuous weak response of the laser to the phase and amplitude of the feedback light is achieved by controlling the feedback power level, and this system can be used to achieve contact-free measurement of displacement, vibration, liquid evaporation and thermal expansion with nanometre accuracy in common room conditions without precise environmental control. Furthermore, a strong response, including chaotic harmonic and parametric oscillation, is observed, and the spectrum of this response, as examined by a frequency-stabilised Nd:YAG laser, indicates laser spectral linewidth broadening.

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.

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Return Difference Feedback Design for Robust Uncertainty Tolerance in Stochastic Multivariable Control Systems.

DTIC Science & Technology

1982-11-01

D- R136 495 RETURN DIFFERENCE FEEDBACK DESIGN FOR ROBUSTj/ UNCERTAINTY TOLERANCE IN STO..(U) UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES DEPT OF...State and ZIP Code) 7. b6 ADORESS (City. Staft and ZIP Code) Department of Electrical Engineering -’M Directorate of Mathematical & Information Systems ...13. SUBJECT TERMS Continur on rverse ineeesaty and identify by block nmber) FIELD GROUP SUE. GR. Systems theory; control; feedback; automatic control

A new approach to approximating the linear quadratic optimal control law for hereditary systems with control delays

NASA Technical Reports Server (NTRS)

Milman, M. H.

1985-01-01

A factorization approach is presented for deriving approximations to the optimal feedback gain 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 feedback kernels.

Robust H(infinity) tracking control of boiler-turbine systems.

PubMed

Wu, J; Nguang, S K; Shen, J; Liu, G; Li, Y G

2010-07-01

In this paper, the problem of designing a fuzzy H(infinity) state feedback tracking control of a boiler-turbine is solved. First, the Takagi and Sugeno fuzzy model is used to model a boiler-turbine system. Next, based on the Takagi and Sugeno fuzzy model, sufficient conditions for the existence of a fuzzy H(infinity) nonlinear state feedback tracking control are derived in terms of linear matrix inequalities. The advantage of the proposed tracking control design is that it does not involve feedback linearization technique and complicated adaptive scheme. An industrial boiler-turbine system is used to illustrate the effectiveness of the proposed design as compared with a linearized approach. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Design of state-feedback controllers including sensitivity reduction, with applications to precision pointing

NASA Technical Reports Server (NTRS)

Hadass, Z.

1974-01-01

The design procedure of feedback controllers was described and the considerations for the selection of the design parameters were given. The frequency domain properties of single-input single-output systems using state feedback controllers are analyzed, and desirable phase and gain margin properties are demonstrated. Special consideration is given to the design of controllers for tracking systems, especially those designed to track polynomial commands. As an example, a controller was designed for a tracking telescope with a polynomial tracking requirement and some special features such as actuator saturation and multiple measurements, one of which is sampled. The resulting system has a tracking performance comparing favorably with a much more complicated digital aided tracker. The parameter sensitivity reduction was treated by considering the variable parameters as random variables. A performance index is defined as a weighted sum of the state and control convariances that sum from both the random system disturbances and the parameter uncertainties, and is minimized numerically by adjusting a set of free parameters.

Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

PubMed

Tong, Shaocheng; Sui, Shuai; Li, Yongming

2015-12-01

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics.

PubMed

Tong, Shaocheng; Li, Yongming

2017-02-01

This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is independent of switching signals is designed to solve the problem of unmeasured states. Fuzzy logic systems are used to identify unknown lumped nonlinear functions so that the problem of unstructured uncertainties can be solved. By combining adaptive backstepping design principle and small-gain approach, a novel robust adaptive fuzzy output feedback stabilization control approach is developed. The stability of the closed-loop system is proved via the common Lyapunov function theory and small-gain theorem. Finally, the simulation results are given to demonstrate the validity and performance of the proposed control strategy.

Mixed H2/Hinfinity output-feedback control of second-order neutral systems with time-varying state and input delays.

PubMed

Karimi, Hamid Reza; Gao, Huijun

2008-07-01

A mixed H2/Hinfinity output-feedback control design methodology is presented in this paper for second-order neutral linear systems with time-varying state and input delays. Delay-dependent sufficient conditions for the design of a desired control are given in terms of linear matrix inequalities (LMIs). A controller, which guarantees asymptotic stability and a mixed H2/Hinfinity performance for the closed-loop system of the second-order neutral linear system, is then developed directly instead of coupling the model to a first-order neutral system. A Lyapunov-Krasovskii method underlies the LMI-based mixed H2/Hinfinity output-feedback control design using some free weighting matrices. The simulation results illustrate the effectiveness of the proposed methodology.

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.

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.

Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

PubMed

Fei, Juntao; Lu, Cheng

2018-04-01

In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

Feedback-controlled heat transport in quantum devices: theory and solid-state experimental proposal

NASA Astrophysics Data System (ADS)

Campisi, Michele; Pekola, Jukka; Fazio, Rosario

2017-05-01

A theory of feedback-controlled heat transport in quantum systems is presented. It is based on modelling heat engines as driven multipartite systems subject to projective quantum measurements and measurement-conditioned unitary evolutions. The theory unifies various results presented previously in the literature. Feedback control breaks time reversal invariance. This in turn results in the fluctuation relation not being obeyed. Its restoration occurs through appropriate accounting of the gain and use of information via measurements and feedback. We further illustrate an experimental proposal for the realisation of a Maxwell demon using superconducting circuits and single-photon on-chip calorimetry. A two-level qubit acts as a trap-door, which, conditioned on its state, is coupled to either a hot resistor or a cold one. The feedback mechanism alters the temperatures felt by the qubit and can result in an effective inversion of temperature gradient, where heat flows from cold to hot thanks to the gain and use of information.

Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces.

PubMed

Benyamini, Miri; Zacksenhouse, Miriam

2015-01-01

Recent experiments with brain-machine-interfaces (BMIs) indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus, we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal.

Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces

PubMed Central

Benyamini, Miri; Zacksenhouse, Miriam

2015-01-01

Recent experiments with brain-machine-interfaces (BMIs) indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus, we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal. PMID:26042002

Stationary average consensus protocol for a class of heterogeneous high-order multi-agent systems with application for aircraft

NASA Astrophysics Data System (ADS)

Rezaei, Mohammad Hadi; Menhaj, Mohammad Bagher

2018-01-01

This paper investigates the stationary average consensus problem for a class of heterogeneous-order multi-agent systems. The goal is to bring the positions of agents to the average of their initial positions while letting the other states converge to zero. To this end, three different consensus protocols are proposed. First, based on the auxiliary variables information among the agents under switching directed networks and state-feedback control, a protocol is proposed whereby all the agents achieve stationary average consensus. In the second and third protocols, by resorting to only measurements of relative positions of neighbouring agents under fixed balanced directed networks, two control frameworks are presented with two strategies based on state-feedback and output-feedback control. Finally, simulation results are given to illustrate the effectiveness of the proposed protocols.

System properties, feedback control and effector coordination of human temperature regulation.

PubMed

Werner, Jürgen

2010-05-01

The aim of human temperature regulation is to protect body processes by establishing a relative constancy of deep body temperature (regulated variable), in spite of external and internal influences on it. This is basically achieved by a distributed multi-sensor, multi-processor, multi-effector proportional feedback control system. The paper explains why proportional control implies inherent deviations of the regulated variable from the value in the thermoneutral zone. The concept of feedback of the thermal state of the body, conveniently represented by a high-weighted core temperature (T (c)) and low-weighted peripheral temperatures (T (s)) is equivalent to the control concept of "auxiliary feedback control", using a main (regulated) variable (T (c)), supported by an auxiliary variable (T (s)). This concept implies neither regulation of T (s) nor feedforward control. Steady-states result in the closed control-loop, when the open-loop properties of the (heat transfer) process are compatible with those of the thermoregulatory processors. They are called operating points or balance points and are achieved due to the inherent property of dynamical stability of the thermoregulatory feedback loop. No set-point and no comparison of signals (e.g. actual-set value) are necessary. Metabolic heat production and sweat production, though receiving the same information about the thermal state of the body, are independent effectors with different thresholds and gains. Coordination between one of these effectors and the vasomotor effector is achieved by the fact that changes in the (heat transfer) process evoked by vasomotor control are taken into account by the metabolic/sweat processor.

Multivariable control of the Space Shuttle Remote Manipulator System using linearization by state feedback

NASA Technical Reports Server (NTRS)

Gettman, Chang-Ching L.; Adams, Neil; Bedrossian, Nazareth; Valavani, Lena

1993-01-01

This paper demonstrates an approach to nonlinear control system design that uses linearization by state feedback to allow faster maneuvering of payloads by the Shuttle Remote Manipulator System (SRMS). A nonlinear feedback law is defined to cancel the nonlinear plant dynamics so that a linear controller can be designed for the SRMS. First a nonlinear design model was generated via SIMULINK. This design model included nonlinear arm dynamics derived from the Lagrangian approach, linearized servo model, and linearized gearbox model. The current SRMS position hold controller was implemented on this system. Next, a trajectory was defined using a rigid body kinematics SRMS tool, KRMS. The maneuver was simulated. Finally, higher bandwidth controllers were developed. Results of the new controllers were compared with the existing SRMS automatic control modes for the Space Station Freedom Mission Build 4 Payload extended on the SRMS.

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.

Output Feedback Distributed Containment Control for High-Order Nonlinear Multiagent Systems.

PubMed

Li, Yafeng; Hua, Changchun; Wu, Shuangshuang; Guan, Xinping

2017-01-31

In this paper, we study the problem of output feedback distributed containment control for a class of high-order nonlinear multiagent systems under a fixed undirected graph and a fixed directed graph, respectively. Only the output signals of the systems can be measured. The novel reduced order dynamic gain observer is constructed to estimate the unmeasured state variables of the system with the less conservative condition on nonlinear terms than traditional Lipschitz one. Via the backstepping method, output feedback distributed nonlinear controllers for the followers are designed. By means of the novel first virtual controllers, we separate the estimated state variables of different agents from each other. Consequently, the designed controllers show independence on the estimated state variables of neighbors except outputs information, and the dynamics of each agent can be greatly different, which make the design method have a wider class of applications. Finally, a numerical simulation is presented to illustrate the effectiveness of the proposed method.

Delay compensation in integrated communication and control systems. I - Conceptual development and analysis

NASA Technical Reports Server (NTRS)

Luck, Rogelio; Ray, Asok

1990-01-01

A procedure for compensating for the effects of distributed network-induced delays in integrated communication and control systems (ICCS) is proposed. The problem of analyzing systems with time-varying and possibly stochastic delays could be circumvented by use of a deterministic observer which is designed to perform under certain restrictive but realistic assumptions. The proposed delay-compensation algorithm is based on a deterministic state estimator and a linear state-variable-feedback control law. The deterministic observer can be replaced by a stochastic observer without any structural modifications of the delay compensation algorithm. However, if a feedforward-feedback control law is chosen instead of the state-variable feedback control law, the observer must be modified as a conventional nondelayed system would be. Under these circumstances, the delay compensation algorithm would be accordingly changed. The separation principle of the classical Luenberger observer holds true for the proposed delay compensator. The algorithm is suitable for ICCS in advanced aircraft, spacecraft, manufacturing automation, and chemical process applications.

Acceleration feedback improves balancing against reflex delay

PubMed Central

Insperger, Tamás; Milton, John; Stépán, Gábor

2013-01-01

A model for human postural balance is considered in which the time-delayed feedback depends on position, velocity and acceleration (proportional–derivative–acceleration (PDA) feedback). It is shown that a PDA controller is equivalent to a predictive controller, in which the prediction is based on the most recent information of the state, but the control input is not involved into the prediction. A PDA controller is superior to the corresponding proportional–derivative controller in the sense that the PDA controller can stabilize systems with approximately 40 per cent larger feedback delays. The addition of a sensory dead zone to account for the finite thresholds for detection by sensory receptors results in highly intermittent, complex oscillations that are a typical feature of human postural sway. PMID:23173196

On the stabilization of decentralized control systems.

NASA Technical Reports Server (NTRS)

Wang, S.-H.; Davison, E. J.

1973-01-01

This paper considers the problem of stabilizing a linear time-variant multivariable system by using several local feedback control laws. Each local feedback control law depends only on partial system outputs. A necessary and sufficient condition for the existence of local control laws with dynamic compensation to stabilize a given system is derived. This condition is stated in terms of a new notion, called fixed modes, which is a natural generalization of the well-known concept of uncontrollable modes and unobservable modes that occur in centralized control system problems. A procedure that constructs a set of stabilizing feedback control laws is given.

Output control using feedforward and cascade controllers

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

An open-loop solution to the output control problem in SISO (single-input, single-output) systems by means of feedforward and cascade controllers is investigated. A simple characterization of feedforward controllers, which achieve steady-state disturbance rejection, is given in a transfer-function setting. Cascade controllers which cause steady-state command tracking are characterized. Disturbance decoupling and command matching controllers are identified. Conditions for existence of feedforward and cascade controllers are given. For unstable systems, it is shown that a stabilizing feedback controller can be used without affecting the feedforward and cascade controllers used for output control; hence, the three controllers can be designed independently. Output control by a combination of feedforward and feedback is discussed.

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.

Stability analysis of dynamic collaboration model with control signals on two lanes

NASA Astrophysics Data System (ADS)

Li, Zhipeng; Zhang, Run; Xu, Shangzhi; Qian, Yeqing; Xu, Juan

2014-12-01

In this paper, the influence of control signals on the stability of two-lane traffic flow is mainly studied by applying control theory with lane changing behaviors. We present the two-lane dynamic collaboration model with lateral friction and the expressions of feedback control signals. What is more, utilizing the delayed feedback control theory to the two-lane dynamic collaboration model with control signals, we investigate the stability of traffic flow theoretically and the stability conditions for both lanes are derived with finding that the forward and lateral feedback signals can improve the stability of traffic flow while the backward feedback signals cannot achieve it. Besides, direct simulations are conducted to verify the results of theoretical analysis, which shows that the feedback signals have a significant effect on the running state of two vehicle groups, and the results are same with the theoretical analysis.

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.

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.

Integrated Flight/Structural Mode Control for Very Flexible Aircraft Using L1 Adaptive Output Feedback Controller

NASA Technical Reports Server (NTRS)

Che, Jiaxing; Cao, Chengyu; Gregory, Irene M.

2012-01-01

This paper explores application of adaptive control architecture to a light, high-aspect ratio, flexible aircraft configuration that exhibits strong rigid body/flexible mode coupling. Specifically, an L(sub 1) adaptive output feedback controller is developed for a semi-span wind tunnel model capable of motion. The wind tunnel mount allows the semi-span model to translate vertically and pitch at the wing root, resulting in better simulation of an aircraft s rigid body motion. The control objective is to design a pitch control with altitude hold while suppressing body freedom flutter. The controller is an output feedback nominal controller (LQG) augmented by an L(sub 1) adaptive loop. A modification to the L(sub 1) output feedback is proposed to make it more suitable for flexible structures. The new control law relaxes the required bounds on the unmatched uncertainty and allows dependence on the state as well as time, i.e. a more general unmatched nonlinearity. The paper presents controller development and simulated performance responses. Simulation is conducted by using full state flexible wing models derived from test data at 10 different dynamic pressure conditions. An L(sub 1) adaptive output feedback controller is designed for a single test point and is then applied to all the test cases. The simulation results show that the L(sub 1) augmented controller can stabilize and meet the performance requirements for all 10 test conditions ranging from 30 psf to 130 psf dynamic pressure.

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.

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

Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays.

PubMed

Wang, Min; Ge, Shuzhi Sam; Hong, Keum-Shik

2010-11-01

This paper presents adaptive neural tracking control for a class of non-affine pure-feedback systems with multiple unknown state time-varying delays. To overcome the design difficulty from non-affine structure of pure-feedback system, mean value theorem is exploited to deduce affine appearance of state variables x(i) as virtual controls α(i), and of the actual control u. The separation technique is introduced to decompose unknown functions of all time-varying delayed states into a series of continuous functions of each delayed state. The novel Lyapunov-Krasovskii functionals are employed to compensate for the unknown functions of current delayed state, which is effectively free from any restriction on unknown time-delay functions and overcomes the circular construction of controller caused by the neural approximation of a function of u and [Formula: see text] . Novel continuous functions are introduced to overcome the design difficulty deduced from the use of one adaptive parameter. To achieve uniformly ultimate boundedness of all the signals in the closed-loop system and tracking performance, control gains are effectively modified as a dynamic form with a class of even function, which makes stability analysis be carried out at the present of multiple time-varying delays. Simulation studies are provided to demonstrate the effectiveness of the proposed scheme.

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

NASA Technical Reports Server (NTRS)

Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.

2013-01-01

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

Robust back-stepping output feedback trajectory tracking for quadrotors via extended state observer and sigmoid tracking differentiator

NASA Astrophysics Data System (ADS)

Shao, Xingling; Liu, Jun; Wang, Honglun

2018-05-01

In this paper, a robust back-stepping output feedback trajectory tracking controller is proposed for quadrotors subject to parametric uncertainties and external disturbances. Based on the hierarchical control principle, the quadrotor dynamics is decomposed into translational and rotational subsystems to facilitate the back-stepping control design. With given model information incorporated into observer design, a high-order extended state observer (ESO) that relies only on position measurements is developed to estimate the remaining unmeasurable states and the lumped disturbances in rotational subsystem simultaneously. To overcome the problem of "explosion of complexity" in the back-stepping design, the sigmoid tracking differentiator (STD) is introduced to compute the derivative of virtual control laws. The advantage is that the proposed controller via output-feedback scheme not only can ensure good tracking performance using very limited information of quadrotors, but also has the ability of handling the undesired uncertainties. The stability analysis is established using the Lyapunov theory. Simulation results demonstrate the effectiveness of the proposed control scheme in achieving a guaranteed tracking performance with respect to an 8-shaped reference trajectory.

Adaptive Neural Output-Feedback Control for a Class of Nonlower Triangular Nonlinear Systems With Unmodeled Dynamics.

PubMed

Wang, Huanqing; Liu, Peter Xiaoping; Li, Shuai; Wang, Ding

2017-08-29

This paper presents the development of an adaptive neural controller for a class of nonlinear systems with unmodeled dynamics and immeasurable states. An observer is designed to estimate system states. The structure consistency of virtual control signals and the variable partition technique are combined to overcome the difficulties appearing in a nonlower triangular form. An adaptive neural output-feedback controller is developed based on the backstepping technique and the universal approximation property of the radial basis function (RBF) neural networks. By using the Lyapunov stability analysis, the semiglobally and uniformly ultimate boundedness of all signals within the closed-loop system is guaranteed. The simulation results show that the controlled system converges quickly, and all the signals are bounded. This paper is novel at least in the two aspects: 1) an output-feedback control strategy is developed for a class of nonlower triangular nonlinear systems with unmodeled dynamics and 2) the nonlinear disturbances and their bounds are the functions of all states, which is in a more general form than existing results.

Application of a passivity based control methodology for flexible joint robots to a simplified Space Shuttle RMS

NASA Technical Reports Server (NTRS)

Sicard, Pierre; Wen, John T.

1992-01-01

A passivity approach for the control design of flexible joint robots is applied to the rate control of a three-link arm modeled after the shoulder yaw joint of the Space Shuttle Remote Manipulator System (RMS). The system model includes friction and elastic joint couplings modeled as nonlinear springs. The basic structure of the proposed controller is the sum of a model-based feedforward and a model-independent feedback. A regulator approach with link state feedback is employed to define the desired motor state. Passivity theory is used to design a motor state-based controller to stabilize the error system formed by the feedforward. Simulation results show that greatly improved performance was obtained by using the proposed controller over the existing RMS controller.

Time-delayed feedback control of diffusion in random walkers.

PubMed

Ando, Hiroyasu; Takehara, Kohta; Kobayashi, Miki U

2017-07-01

Time delay in general leads to instability in some systems, while specific feedback with delay can control fluctuated motion in nonlinear deterministic systems to a stable state. In this paper, we consider a stochastic process, i.e., a random walk, and observe its diffusion phenomenon with time-delayed feedback. As a result, the diffusion coefficient decreases with increasing delay time. We analytically illustrate this suppression of diffusion by using stochastic delay differential equations and justify the feasibility of this suppression by applying time-delayed feedback to a molecular dynamics model.

Gust alleviation of highly flexible UAVs with artificial hair sensors

NASA Astrophysics Data System (ADS)

Su, Weihua; Reich, Gregory W.

2015-04-01

Artificial hair sensors (AHS) have been recently developed in Air Force Research Laboratory (AFRL) using carbon nanotube (CNT). The deformation of CNT in air flow causes voltage and current changes in the circuit, which can be used to quantify the dynamic pressure and aerodynamic load along the wing surface. AFRL has done a lot of essential work in design, manufacturing, and measurement of AHSs. The work in this paper is to bridge the current AFRL's work on AHSs and their feasible applications in flight dynamics and control (e.g., the gust alleviation) of highly flexible aircraft. A highly flexible vehicle is modeled using a strain-based geometrically nonlinear beam formulation, coupled with finite-state inflow aerodynamics. A feedback control algorithm for the rejection of gust perturbations will be developed. A simplified Linear Quadratic Regulator (LQR) controller will be implemented based on the state-space representation of the linearized system. All AHS measurements will be used as the control input, i.e., wing sectional aerodynamic loads will be defined as the control output for designing the feedback gain. Once the controller is designed, closed-loop aeroelastic simulations will be performed to evaluate the performance of different controllers with the force feedback and be compared to traditional controller designs with the state feedback. From the study, the feasibility of AHSs in flight control will be assessed. The whole study will facilitate in building a fly-by-feel simulation environment for autonomous vehicles.

Mode-selective control of thermal Brownian vibration of micro-resonator (Generation of a thermal no-equilibrium state by mechanical feedback control)

NASA Astrophysics Data System (ADS)

Kawamura, Y.; Kanegae, R.

2017-09-01

Recently, there have been various attempts to dampen the vibration amplitude of the Brownian motion of a microresonator below the thermal vibration amplitude, with the goal of reaching the quantum ground vibration level. To further develop the approach of reaching the quantum ground state, it is essential to clarify whether or not coupling exists between the different vibration modes of the resonator. In this paper, the mode-selective control of thermal Brownian vibration is shown. The first and the second vibration modes of a micro-cantilever moved by a random Brownian motion are cooled selectively and independently below the thermal vibration amplitude, as determined by the statistical thermodynamic theory, using a mechanical feedback control method. This experimental result shows that the thermal no-equilibrium condition was generated by mechanical feedback control.

Reduced state feedback gain computation. [optimization and control theory for aircraft control

NASA Technical Reports Server (NTRS)

Kaufman, H.

1976-01-01

Because application of conventional optimal linear regulator theory to flight controller design 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. Therefore, a stochastic linear model that was developed is presented which accounts for aircraft parameter and initial uncertainty, measurement noise, turbulence, pilot command and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was 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.

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.

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

Integrated optical sensor

DOEpatents

Watkins, Arthur D.; Smartt, Herschel B.; Taylor, Paul L.

1994-01-01

An integrated optical sensor for arc welding having multifunction feedback control. The sensor, comprising generally a CCD camera and diode laser, is positioned behind the arc torch for measuring weld pool position and width, standoff distance, and post-weld centerline cooling rate. Computer process information from this sensor is passed to a controlling computer for use in feedback control loops to aid in the control of the welding process. Weld pool position and width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint. Sensor standoff distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to determine the final metallurgical state of the weld bead and heat affected zone, thereby controlling post-weld mechanical properties.

Integrated optical sensor

DOEpatents

Watkins, A.D.; Smartt, H.B.; Taylor, P.L.

1994-01-04

An integrated optical sensor for arc welding having multifunction feedback control is described. The sensor, comprising generally a CCD camera and diode laser, is positioned behind the arc torch for measuring weld pool position and width, standoff distance, and post-weld centerline cooling rate. Computer process information from this sensor is passed to a controlling computer for use in feedback control loops to aid in the control of the welding process. Weld pool position and width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint. Sensor standoff distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to determine the final metallurgical state of the weld bead and heat affected zone, thereby controlling post-weld mechanical properties. 6 figures.

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.

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.

Comment on "Synchronization of chaotic systems with delay using intermittent linear state feedback" [Chaos 18, 033122 (2008)].

PubMed

Zhang, Yinping; Wang, Qing-Guo

2008-12-01

In the referenced paper, there is technical carelessness in the third lemma and in the main result. Hence, it is a possible failure when the result is used to design the intermittent linear state feedback controller for exponential synchronization of two chaotic delayed systems.

Adaptive Importance Sampling for Control and Inference

NASA Astrophysics Data System (ADS)

Kappen, H. J.; Ruiz, H. C.

2016-03-01

Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.

Modal space three-state feedback control for electro-hydraulic servo plane redundant driving mechanism with eccentric load decoupling.

PubMed

Zhao, Jinsong; Wang, Zhipeng; Zhang, Chuanbi; Yang, Chifu; Bai, Wenjie; Zhao, Zining

2018-06-01

The shaking table based on electro-hydraulic servo parallel mechanism has the advantage of strong carrying capacity. However, the strong coupling caused by the eccentric load not only affects the degree of freedom space control precision, but also brings trouble to the system control. A novel decoupling control strategy is proposed, which is based on modal space to solve the coupling problem for parallel mechanism with eccentric load. The phenomenon of strong dynamic coupling among degree of freedom space is described by experiments, and its influence on control design is discussed. Considering the particularity of plane motion, the dynamic model is built by Lagrangian method to avoid complex calculations. The dynamic equations of the coupling physical space are transformed into the dynamic equations of the decoupling modal space by using the weighted orthogonality of the modal main mode with respect to mass matrix and stiffness matrix. In the modal space, the adjustments of the modal channels are independent of each other. Moreover, the paper discusses identical closed-loop dynamic characteristics of modal channels, which will realize decoupling for degree of freedom space, thus a modal space three-state feedback control is proposed to expand the frequency bandwidth of each modal channel for ensuring their near-identical responses in a larger frequency range. Experimental results show that the concept of modal space three-state feedback control proposed in this paper can effectively reduce the strong coupling problem of degree of freedom space channels, which verify the effectiveness of the proposed model space state feedback control strategy for improving the control performance of the electro-hydraulic servo plane redundant driving mechanism. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Linear system theory

NASA Technical Reports Server (NTRS)

Callier, Frank M.; Desoer, Charles A.

1991-01-01

The aim of this book is to provide a systematic and rigorous access to the main topics of linear state-space system theory in both the continuous-time case and the discrete-time case; and the I/O description of linear systems. The main thrusts of the work are the analysis of system descriptions and derivations of their properties, LQ-optimal control, state feedback and state estimation, and MIMO unity-feedback systems.

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.

Finite-time stabilization of uncertain nonholonomic systems in feedforward-like form by output feedback.

PubMed

Gao, Fangzheng; Wu, Yuqiang; Zhang, Zhongcai

2015-11-01

This paper investigates the problem of finite-time stabilization by output feedback for a class of nonholonomic systems in chained form with uncertainties. Comparing with the existing relevant literature, a distinguishing feature of the systems under investigation is that the x-subsystem is a feedforward-like rather than feedback-like system. This renders the existing control methods inapplicable to the control problems of the systems. A constructive design procedure for output feedback control is given. The designed controller renders that the states of closed-loop system are regulated to zero in a finite time. Two simulation examples are provided to illustrate the effectiveness of the proposed approach. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Zero Power Non-Contact Suspension System with Permanent Magnet Motion Feedback

NASA Astrophysics Data System (ADS)

Sun, Feng; Oka, Koichi

This paper proposes a zero power control method for a permanent magnetic suspension system consisting mainly of a permanent magnet, an actuator, sensors, a suspended iron ball and a spring. A system using this zero power control method will consume quasi-zero power when the levitated object is suspended in an equilibrium state. To realize zero power control, a spring is installed in the magnetic suspension device to counterbalance the gravitational force on the actuator in the equilibrium position. In addition, an integral feedback loop in the controller affords zero actuator current when the device is in a balanced state. In this study, a model was set up for feasibility analysis, a prototype was manufactured for experimental confirmation, numerical simulations of zero power control with nonlinear attractive force were carried out based on the model, and experiments were completed to confirm the practicality of the prototype. The simulations and experiments were performed under varied conditions, such as without springs and without zero power control, with springs and without zero power control, with springs and with zero power control, using different springs and integral feedback gains. Some results are shown and analyzed in this paper. All results indicate that this zero power control method is feasible and effective for use in this suspension system with a permanent magnet motion feedback loop.

Automatic and controlled processing in the corticocerebellar system.

PubMed

Ramnani, Narender

2014-01-01

During learning, performance changes often involve a transition from controlled processing in which performance is flexible and responsive to ongoing error feedback, but effortful and slow, to a state in which processing becomes swift and automatic. In this state, performance is unencumbered by the requirement to process feedback, but its insensitivity to feedback reduces its flexibility. Many properties of automatic processing are similar to those that one would expect of forward models, and many have suggested that these may be instantiated in cerebellar circuitry. Since hierarchically organized frontal lobe areas can both send and receive commands, I discuss the possibility that they can act both as controllers and controlled objects and that their behaviors can be independently modeled by forward models in cerebellar circuits. Since areas of the prefrontal cortex contribute to this hierarchically organized system and send outputs to the cerebellar cortex, I suggest that the cerebellum is likely to contribute to the automation of cognitive skills, and to the formation of habitual behavior which is resistant to error feedback. An important prerequisite to these ideas is that cerebellar circuitry should have access to higher order error feedback that signals the success or failure of cognitive processing. I have discussed the pathways through which such feedback could arrive via the inferior olive and the dopamine system. Cerebellar outputs inhibit both the inferior olive and the dopamine system. It is possible that learned representations in the cerebellum use this as a mechanism to suppress the processing of feedback in other parts of the nervous system. Thus, cerebellar processes that control automatic performance may be completed without triggering the engagement of controlled processes by prefrontal mechanisms. © 2014 Elsevier B.V. All rights reserved.

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Design of integrated autopilot/autothrottle for NASA TSRV airplane using integral LQG methodology. [transport systems research vehicle

NASA Technical Reports Server (NTRS)

Kaminer, Isaac; Benson, Russell A.

1989-01-01

An integrated autopilot/autothrottle control system has been developed for the NASA transport system research vehicle using a two-degree-of-freedom approach. Based on this approach, the feedback regulator was designed using an integral linear quadratic regulator design technique, which offers a systematic approach to satisfy desired feedback performance requirements and guarantees stability margins in both control and sensor loops. The resulting feedback controller was discretized and implemented using a delta coordinate concept, which allows for transient free controller switching by initializing all controller states to zero and provides a simple solution for dealing with throttle limiting cases.

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions.

PubMed

Yu, Zhaoxu; Li, Shugang; Yu, Zhaosheng; Li, Fangfei

2018-04-01

This paper investigates the problem of output feedback adaptive stabilization for a class of nonstrict-feedback stochastic nonlinear systems with both unknown backlashlike hysteresis and unknown control directions. A new linear state transformation is applied to the original system, and then, control design for the new system becomes feasible. By combining the neural network's (NN's) parameterization, variable separation technique, and Nussbaum gain function method, an input-driven observer-based adaptive NN control scheme, which involves only one parameter to be updated, is developed for such systems. All closed-loop signals are bounded in probability and the error signals remain semiglobally bounded in the fourth moment (or mean square). Finally, the effectiveness and the applicability of the proposed control design are verified by two simulation examples.

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

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.

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.

Regional robust stabilisation and domain-of-attraction estimation for MIMO uncertain nonlinear systems with input saturation

NASA Astrophysics Data System (ADS)

Azizi, S.; Torres, L. A. B.; Palhares, R. M.

2018-01-01

The regional robust stabilisation by means of linear time-invariant state feedback control for a class of uncertain MIMO nonlinear systems with parametric uncertainties and control input saturation is investigated. The nonlinear systems are described in a differential algebraic representation and the regional stability is handled considering the largest ellipsoidal domain-of-attraction (DOA) inside a given polytopic region in the state space. A novel set of sufficient Linear Matrix Inequality (LMI) conditions with new auxiliary decision variables are developed aiming to design less conservative linear state feedback controllers with corresponding larger DOAs, by considering the polytopic description of the saturated inputs. A few examples are presented showing favourable comparisons with recently published similar control design methodologies.

Fuzzy Model-based Pitch Stabilization and Wing Vibration Suppression of Flexible Wing Aircraft.

NASA Technical Reports Server (NTRS)

Ayoubi, Mohammad A.; Swei, Sean Shan-Min; Nguyen, Nhan T.

2014-01-01

This paper presents a fuzzy nonlinear controller to regulate the longitudinal dynamics of an aircraft and suppress the bending and torsional vibrations of its flexible wings. The fuzzy controller utilizes full-state feedback with input constraint. First, the Takagi-Sugeno fuzzy linear model is developed which approximates the coupled aeroelastic aircraft model. Then, based on the fuzzy linear model, a fuzzy controller is developed to utilize a full-state feedback and stabilize the system while it satisfies the control input constraint. Linear matrix inequality (LMI) techniques are employed to solve the fuzzy control problem. Finally, the performance of the proposed controller is demonstrated on the NASA Generic Transport Model (GTM).

Decentralized control of large flexible structures by joint decoupling

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Juang, Jer-Nan

1992-01-01

A decentralized control design method is presented for large complex flexible structures by using the idea of joint decoupling. The derivation is based on a coupled substructure state-space model, which is obtained from enforcing conditions of interface compatibility and equilibrium to the substructure state-space models. It is shown that by restricting the control law to be localized state feedback and by setting the joint actuator input commands to decouple joint 'degrees of freedom' (dof) from interior dof, the global structure control design problem can be decomposed into several substructure control design problems. The substructure control gains and substructure observers are designed based on modified substructure state-space models. The controllers produced by the proposed method can operate successfully at the individual substructure level as well as at the global structure level. Therefore, not only control design but also control implementation is decentralized. Stability and performance requirement of the closed-loop system can be achieved by using any existing state feedback control design method. A two-component mass-spring damper system and a three-truss structure are used as examples to demonstrate the proposed method.

Spacecraft stability and control using new techniques for periodic and time-delayed systems

NASA Astrophysics Data System (ADS)

NAzari, Morad

This dissertation addresses various problems in spacecraft stability and control using specialized theoretical and numerical techniques for time-periodic and time-delayed systems. First, the effects of energy dissipation are considered in the dual-spin spacecraft, where the damper masses in the platform (?) and the rotor (?) cause energy loss in the system. Floquet theory is employed to obtain stability charts for different relative spin rates of the subsystem [special characters omitted] with respect to the subsystem [special characters omitted]. Further, the stability and bifurcation of delayed feedback spin stabilization of a rigid spacecraft is investigated. The spin is stabilized about the principal axis of the intermediate moment of inertia using a simple delayed feedback control law. In particular, linear stability is analyzed via the exponential-polynomial characteristic equations and then the method of multiple scales is used to obtain the normal form of the Hopf bifurcation. Next, the dynamics of a rigid spacecraft with nonlinear delayed multi-actuator feedback control are studied, where a nonlinear feedback controller using an inverse dynamics approach is sought for the controlled system to have the desired linear delayed closed-loop dynamics (CLD). Later, three linear state feedback control strategies based on Chebyshev spectral collocation and the Lyapunov Floquet transformation (LFT) are explored for regulation control of linear periodic time delayed systems. First , a delayed feedback control law with discrete delay is implemented and the stability of the closed-loop response is investigated in the parameter space of available control gains using infinite-dimensional Floquet theory. Second, the delay differential equation (DDE) is discretized into a large set of ordinary differential equations (ODEs) using the Chebyshev spectral continuous time approximation (CSCTA) and delayed feedback with distributed delay is applied. The third strategy involves use of both CSCTA and the reduced Lyapunov Floquet transformation (RLFT) in order to design a non-delayed feedback control law. The delayed Mathieu equation is used as an illustrative example in which the closed-loop response and control effort are compared for all three control strategies. Finally, three example applications of control of time-periodic astrodynamic systems, i.e. formation flying control for an elliptic Keplerian chief orbit, body-fixed hovering control over a tumbling asteroid, and stationkeeping in Earth-Moon L1 halo orbits, are shown using versions of the control strategies introduced above. These applications employ a mixture of feedforward and non-delayed periodic-gain state feedback for tracking control of natural and non-natural motions in these systems. A major conclusion is that control effort is minimized by employing periodic-gain (rather than constant-gain) feedback control in such systems.

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.

Precise computer controlled positioning of robot end effectors using force sensors

NASA Technical Reports Server (NTRS)

Shieh, L. S.; Mcinnis, B. C.; Wang, J. C.

1988-01-01

A thorough study of combined position/force control using sensory feedback for a one-dimensional manipulator model, which may count for the spacecraft docking problem or be extended to the multi-joint robot manipulator problem, was performed. The additional degree of freedom introduced by the compliant force sensor is included in the system dynamics in the design of precise position control. State feedback based on the pole placement method and with integral control is used to design the position controller. A simple constant gain force controller is used as an example to illustrate the dependence of the stability and steady-state accuracy of the overall position/force control upon the design of the inner position controller. Supportive simulation results are also provided.

Smart Braid Feedback for the Closed-Loop Control of Soft Robotic Systems.

PubMed

Felt, Wyatt; Chin, Khai Yi; Remy, C David

2017-09-01

This article experimentally investigates the potential of using flexible, inductance-based contraction sensors in the closed-loop motion control of soft robots. Accurate motion control remains a highly challenging task for soft robotic systems. Precise models of the actuation dynamics and environmental interactions are often unavailable. This renders open-loop control impossible, while closed-loop control suffers from a lack of suitable feedback. Conventional motion sensors, such as linear or rotary encoders, are difficult to adapt to robots that lack discrete mechanical joints. The rigid nature of these sensors runs contrary to the aspirational benefits of soft systems. As truly soft sensor solutions are still in their infancy, motion control of soft robots has so far relied on laboratory-based sensing systems such as motion capture, electromagnetic (EM) tracking, or Fiber Bragg Gratings. In this article, we used embedded flexible sensors known as Smart Braids to sense the contraction of McKibben muscles through changes in inductance. We evaluated closed-loop control on two systems: a revolute joint and a planar, one degree of freedom continuum manipulator. In the revolute joint, our proposed controller compensated for elasticity in the actuator connections. The Smart Braid feedback allowed motion control with a steady-state root-mean-square (RMS) error of [1.5]°. In the continuum manipulator, Smart Braid feedback enabled tracking of the desired tip angle with a steady-state RMS error of [1.25]°. This work demonstrates that Smart Braid sensors can provide accurate position feedback in closed-loop motion control suitable for field applications of soft robotic systems.

Closed-loop control of a fragile network: application to seizure-like dynamics of an epilepsy model

PubMed Central

Ehrens, Daniel; Sritharan, Duluxan; Sarma, Sridevi V.

2015-01-01

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Closed-loop therapy could therefore entail detecting when the network goes unstable, and then stimulating with an exogenous current to stabilize the network. In this study, a non-linear stochastic model of a neuronal network was used to simulate both seizure and non-seizure activity. In particular, synaptic weights between neurons were chosen such that the network's fixed point is stable during non-seizure periods, and a subset of these connections (the most fragile) were perturbed to make the same fixed point unstable to model seizure events; and, the model randomly transitions between these two modes. The goal of this study was to measure spike train observations from this epileptic network and then apply a feedback controller that (i) detects when the network goes unstable, and then (ii) applies a state-feedback gain control input to the network to stabilize it. The stability detector is based on a 2-state (stable, unstable) hidden Markov model (HMM) of the network, and detects the transition from the stable mode to the unstable mode from using the firing rate of the most fragile node in the network (which is the output of the HMM). When the unstable mode is detected, a state-feedback gain is applied to generate a control input to the fragile node bringing the network back to the stable mode. Finally, when the network is detected as stable again, the feedback control input is switched off. High performance was achieved for the stability detector, and feedback control suppressed seizures within 2 s after onset. PMID:25784851

Eigenspace techniques for active flutter suppression

NASA Technical Reports Server (NTRS)

Garrard, William L.; Liebst, Bradley S.; Farm, Jerome A.

1987-01-01

The use of eigenspace techniques for the design of an active flutter suppression system for a hypothetical research drone is discussed. One leading edge and two trailing edge aerodynamic control surfaces and four sensors (accelerometers) are available for each wing. Full state control laws are designed by selecting feedback gains which place closed loop eigenvalues and shape closed loop eigenvectors so as to stabilize wing flutter and reduce gust loads at the wing root while yielding accepatable robustness and satisfying constrains on rms control surface activity. These controllers are realized by state estimators designed using an eigenvalue placement/eigenvector shaping technique which results in recovery of the full state loop transfer characteristics. The resulting feedback compensators are shown to perform almost as well as the full state designs. They also exhibit acceptable performance in situations in which the failure of an actuator is simulated.

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.

Stability boundaries for command augmentation systems

NASA Technical Reports Server (NTRS)

Shrivastava, P. C.

1987-01-01

The Stability Augmentation System (SAS) is a special case of the Command Augmentation System (CAS). Control saturation imposes bounds on achievable commands. The state equilibrium depends only on the open loop dynamics and control deflection. The control magnitude to achieve a desired command equilibrium is independent of the feedback gain. A feedback controller provides the desired response, maintains the system equilibrium under disturbances, but it does not affect the equilibrium values of states and control. The saturation boundaries change with commands, but the location of the equilibrium points in the saturated region remains unchanged. Nonzero command vectors yield saturation boundaries that are asymmetric with respect to the state equilibrium. Except for the saddle point case with MCE control law, the stability boundaries change with commands. For the cases of saddle point and unstable nodes, the region of stability decreases with increasing command magnitudes.

? and ? nonquadratic stabilisation of discrete-time Takagi-Sugeno systems based on multi-instant fuzzy Lyapunov functions

NASA Astrophysics Data System (ADS)

Tognetti, Eduardo S.; Oliveira, Ricardo C. L. F.; Peres, Pedro L. D.

2015-01-01

The problem of state feedback control design for discrete-time Takagi-Sugeno (TS) (T-S) fuzzy systems is investigated in this paper. A Lyapunov function, which is quadratic in the state and presents a multi-polynomial dependence on the fuzzy weighting functions at the current and past instants of time, is proposed.This function contains, as particular cases, other previous Lyapunov functions already used in the literature, being able to provide less conservative conditions of control design for TS fuzzy systems. The structure of the proposed Lyapunov function also motivates the design of a new stabilising compensator for Takagi-Sugeno fuzzy systems. The main novelty of the proposed state feedback control law is that the gain is composed of matrices with multi-polynomial dependence on the fuzzy weighting functions at a set of past instants of time, including the current one. The conditions for the existence of a stabilising state feedback control law that minimises an upper bound to the ? or ? norms are given in terms of linear matrix inequalities. Numerical examples show that the approach can be less conservative and more efficient than other methods available in the literature.

Hardware Simulations of Spacecraft Attitude Synchronization Using Lyapunov-Based Controllers

NASA Astrophysics Data System (ADS)

Jung, Juno; Park, Sang-Young; Eun, Youngho; Kim, Sung-Woo; Park, Chandeok

2018-04-01

In the near future, space missions with multiple spacecraft are expected to replace traditional missions with a single large spacecraft. These spacecraft formation flying missions generally require precise knowledge of relative position and attitude between neighboring agents. In this study, among the several challenging issues, we focus on the technique to control spacecraft attitude synchronization in formation. We develop a number of nonlinear control schemes based on the Lyapunov stability theorem and considering special situations: full-state feedback control, full-state feedback control with unknown inertia parameters, and output feedback control without angular velocity measurements. All the proposed controllers offer absolute and relative control using reaction wheel assembly for both regulator and tracking problems. In addition to the numerical simulations, an air-bearing-based hardware-in-the-loop (HIL) system is used to verify the proposed control laws in real-time hardware environments. The pointing errors converge to 0.5{°} with numerical simulations and to 2{°} using the HIL system. Consequently, both numerical and hardware simulations confirm the performance of the spacecraft attitude synchronization algorithms developed in this study.

Improved methods in neural network-based adaptive output feedback control, with applications to flight control

NASA Astrophysics Data System (ADS)

Kim, Nakwan

Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

Opposing and following responses in sensorimotor speech control: Why responses go both ways.

PubMed

Franken, Matthias K; Acheson, Daniel J; McQueen, James M; Hagoort, Peter; Eisner, Frank

2018-06-04

When talking, speakers continuously monitor and use the auditory feedback of their own voice to control and inform speech production processes. When speakers are provided with auditory feedback that is perturbed in real time, most of them compensate for this by opposing the feedback perturbation. But some responses follow the perturbation. In the present study, we investigated whether the state of the speech production system at perturbation onset may determine what type of response (opposing or following) is made. The results suggest that whether a perturbation-related response is opposing or following depends on ongoing fluctuations of the production system: The system initially responds by doing the opposite of what it was doing. This effect and the nontrivial proportion of following responses suggest that current production models are inadequate: They need to account for why responses to unexpected sensory feedback depend on the production system's state at the time of perturbation.

Event-triggered output feedback control for distributed networked systems.

PubMed

Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

2016-01-01

This paper addresses the problem of output-feedback communication and control with event-triggered framework in the context of distributed networked control systems. The design problem of the event-triggered output-feedback control is proposed as a linear matrix inequality (LMI) feasibility problem. The scheme is developed for the distributed system where only partial states are available. In this scheme, a subsystem uses local observers and share its information to its neighbors only when the subsystem's local error exceeds a specified threshold. The developed method is illustrated by using a coupled cart example from the literature. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Method and apparatus for loss of control inhibitor systems

NASA Technical Reports Server (NTRS)

A'Harrah, Ralph C. (Inventor)

2007-01-01

Active and adaptive systems and methods to prevent loss of control incidents by providing tactile feedback to a vehicle operator are disclosed. According to the present invention, an operator gives a control input to an inceptor. An inceptor sensor measures an inceptor input value of the control input. The inceptor input is used as an input to a Steady-State Inceptor Input/Effector Output Model that models the vehicle control system design. A desired effector output from the inceptor input is generated from the model. The desired effector output is compared to an actual effector output to get a distortion metric. A feedback force is generated as a function of the distortion metric. The feedback force is used as an input to a feedback force generator which generates a loss of control inhibitor system (LOCIS) force back to the inceptor. The LOCIS force is felt by the operator through the inceptor.

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.

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

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.

Evaluating the performance of vehicular platoon control under different network topologies of initial states

NASA Astrophysics Data System (ADS)

Li, Yongfu; Li, Kezhi; Zheng, Taixiong; Hu, Xiangdong; Feng, Huizong; Li, Yinguo

2016-05-01

This study proposes a feedback-based platoon control protocol for connected autonomous vehicles (CAVs) under different network topologies of initial states. In particularly, algebraic graph theory is used to describe the network topology. Then, the leader-follower approach is used to model the interactions between CAVs. In addition, feedback-based protocol is designed to control the platoon considering the longitudinal and lateral gaps simultaneously as well as different network topologies. The stability and consensus of the vehicular platoon is analyzed using the Lyapunov technique. Effects of different network topologies of initial states on convergence time and robustness of platoon control are investigated. Results from numerical experiments demonstrate the effectiveness of the proposed protocol with respect to the position and velocity consensus in terms of the convergence time and robustness. Also, the findings of this study illustrate the convergence time of the control protocol is associated with the initial states, while the robustness is not affected by the initial states significantly.

Detecting and Correcting Errors in Rapid Aiming Movements: Effects of Movement Time, Distance, and Velocity

ERIC Educational Resources Information Center

Sherwood, David E.

2010-01-01

According to closed-loop accounts of motor control, movement errors are detected by comparing sensory feedback to an acquired reference state. Differences between the reference state and the movement-produced feedback results in an error signal that serves as a basis for a correction. The main question addressed in the current study was how…

Optimizing Dynamical Network Structure for Pinning Control

NASA Astrophysics Data System (ADS)

Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo

2016-04-01

Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.

Accessibility, stabilizability, and feedback control of continuous orbital transfer.

PubMed

Gurfil, Pini

2004-05-01

This paper investigates the problem of low-thrust orbital transfer using orbital element feedback from a control-theoretic standpoint, concepts of controllability, feedback stabilizability, and their interaction. The Gauss variational equations (GVEs) are used to model the state-space dynamics. First, the notion of accessibility, a weaker form of controllability, is presented. It is then shown that the GVEs are globally accessible. Based on the accessibility result, a nonlinear feedback controller is derived that asymptotically steers a vehicle from an initial elliptic Keplerian orbit to any given elliptic Keplerian orbit. The performance of the new controller is illustrated by simulating an orbital transfer between two geosynchronous Earth orbits. It is shown that the low-thrust controller requires less fuel than an impulsive maneuver for the same transfer time. Closed-form, analytic expressions for the new orbital transfer controller are given. Finally, it is proved, based on a topological nonlinear stabilizability test, that there does not exist a continuous closed-loop controller that can transfer a spacecraft to a parabolic escape trajectory.

Dynamics of nonlinear feedback control.

PubMed

Snippe, H P; van Hateren, J H

2007-05-01

Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. For input steps, the dynamics of gain and attenuation can be very different, depending on the mathematical form of the nonlinearity and the ordering of the nonlinearity and the filtering in the feedback loop. Further, the dynamics of feedback control can be strongly asymmetrical for increment versus decrement steps of the input. Nevertheless, for each of the models studied, the nonlinearity in the feedback loop can be chosen such that immediately after an input step, the dynamics of feedback control is symmetric with respect to increments versus decrements. Finally, we study the dynamics of the output of the control loops and find conditions under which overshoots and undershoots of the output relative to the steady-state output occur when the models are stimulated with low-pass filtered steps. For small steps at the input, overshoots and undershoots of the output do not occur when the filtering in the control path is faster than the low-pass filtering at the input. For large steps at the input, however, results depend on the model, and for some of the models, multiple overshoots and undershoots can occur even with a fast control path.

Bifurcation analysis of a delay reaction-diffusion malware propagation model with feedback control

NASA Astrophysics Data System (ADS)

Zhu, Linhe; Zhao, Hongyong; Wang, Xiaoming

2015-05-01

With the rapid development of network information technology, information networks security has become a very critical issue in our work and daily life. This paper attempts to develop a delay reaction-diffusion model with a state feedback controller to describe the process of malware propagation in mobile wireless sensor networks (MWSNs). By analyzing the stability and Hopf bifurcation, we show that the state feedback method can successfully be used to control unstable steady states or periodic oscillations. Moreover, formulas for determining the properties of the bifurcating periodic oscillations are derived by applying the normal form method and center manifold theorem. Finally, we conduct extensive simulations on large-scale MWSNs to evaluate the proposed model. Numerical evidences show that the linear term of the controller is enough to delay the onset of the Hopf bifurcation and the properties of the bifurcation can be regulated to achieve some desirable behaviors by choosing the appropriate higher terms of the controller. Furthermore, we obtain that the spatial-temporal dynamic characteristics of malware propagation are closely related to the rate constant for nodes leaving the infective class for recovered class and the mobile behavior of nodes.

Spacecraft Formation Flying near Sun-Earth L2 Lagrange Point: Trajectory Generation and Adaptive Full-State Feedback Control

NASA Technical Reports Server (NTRS)

Wong, Hong; Kapila, Vikram

2004-01-01

In this paper, we present a method for trajectory generation and adaptive full-state feedback control to facilitate spacecraft formation flying near the Sun-Earth L2 Lagrange point. Specifically, the dynamics of a spacecraft in the neighborhood of a Halo orbit reveals that there exist quasi-periodic orbits surrounding the Halo orbit. Thus, a spacecraft formation is created by placing a leader spacecraft on a desired Halo orbit and placing follower spacecraft on desired quasi-periodic orbits. To produce a formation maintenance controller, we first develop the nonlinear dynamics of a follower spacecraft relative to the leader spacecraft. We assume that the leader spacecraft is on a desired Halo orbit trajectory and the follower spacecraft is to track a desired quasi-periodic orbit surrounding the Halo orbit. Then, we design an adaptive, full-state feedback position tracking controller for the follower spacecraft providing an adaptive compensation for the unknown mass of the follower spacecraft. The proposed control law is simulated for the case of the leader and follower spacecraft pair and is shown to yield global, asymptotic convergence of the relative position tracking errors.

Biomimetic Hybrid Feedback Feedforward Neural-Network Learning Control.

PubMed

Pan, Yongping; Yu, Haoyong

2017-06-01

This brief presents a biomimetic hybrid feedback feedforward neural-network learning control (NNLC) strategy inspired by the human motor learning control mechanism for a class of uncertain nonlinear systems. The control structure includes a proportional-derivative controller acting as a feedback servo machine and a radial-basis-function (RBF) NN acting as a feedforward predictive machine. Under the sufficient constraints on control parameters, the closed-loop system achieves semiglobal practical exponential stability, such that an accurate NN approximation is guaranteed in a local region along recurrent reference trajectories. Compared with the existing NNLC methods, the novelties of the proposed method include: 1) the implementation of an adaptive NN control to guarantee plant states being recurrent is not needed, since recurrent reference signals rather than plant states are utilized as NN inputs, which greatly simplifies the analysis and synthesis of the NNLC and 2) the domain of NN approximation can be determined a priori by the given reference signals, which leads to an easy construction of the RBF-NNs. Simulation results have verified the effectiveness of this approach.

Design and hardware-in-loop implementation of collision avoidance algorithms for heavy commercial road vehicles

NASA Astrophysics Data System (ADS)

Rajaram, Vignesh; Subramanian, Shankar C.

2016-07-01

An important aspect from the perspective of operational safety of heavy road vehicles is the detection and avoidance of collisions, particularly at high speeds. The development of a collision avoidance system is the overall focus of the research presented in this paper. The collision avoidance algorithm was developed using a sliding mode controller (SMC) and compared to one developed using linear full state feedback in terms of performance and controller effort. Important dynamic characteristics such as load transfer during braking, tyre-road interaction, dynamic brake force distribution and pneumatic brake system response were considered. The effect of aerodynamic drag on the controller performance was also studied. The developed control algorithms have been implemented on a Hardware-in-Loop experimental set-up equipped with the vehicle dynamic simulation software, IPG/TruckMaker®. The evaluation has been performed for realistic traffic scenarios with different loading and road conditions. The Hardware-in-Loop experimental results showed that the SMC and full state feedback controller were able to prevent the collision. However, when the discrepancies in the form of parametric variations were included, the SMC provided better results in terms of reduced stopping distance and lower controller effort compared to the full state feedback controller.

A stage structure pest management model with impulsive state feedback control

NASA Astrophysics Data System (ADS)

Pang, Guoping; Chen, Lansun; Xu, Weijian; Fu, Gang

2015-06-01

A stage structure pest management model with impulsive state feedback control is investigated. We get the sufficient condition for the existence of the order-1 periodic solution by differential equation geometry theory and successor function. Further, we obtain a new judgement method for the stability of the order-1 periodic solution of the semi-continuous systems by referencing the stability analysis for limit cycles of continuous systems, which is different from the previous method of analog of Poincarè criterion. Finally, we analyze numerically the theoretical results obtained.

Control of the constrained planar simple inverted pendulum

NASA Technical Reports Server (NTRS)

Bavarian, B.; Wyman, B. F.; Hemami, H.

1983-01-01

Control of a constrained planar inverted pendulum by eigenstructure assignment is considered. Linear feedback is used to stabilize and decouple the system in such a way that specified subspaces of the state space are invariant for the closed-loop system. The effectiveness of the feedback law is tested by digital computer simulation. Pre-compensation by an inverse plant is used to improve performance.

Spacecraft nonlinear control

NASA Technical Reports Server (NTRS)

Sheen, Jyh-Jong; Bishop, Robert H.

1992-01-01

The feedback linearization technique is applied to the problem of spacecraft attitude control and momentum management with control moment gyros (CMGs). The feedback linearization consists of a coordinate transformation, which transforms the system to a companion form, and a nonlinear feedback control law to cancel the nonlinear dynamics resulting in a linear equivalent model. Pole placement techniques are then used to place the closed-loop poles. The coordinate transformation proposed here evolves from three output functions of relative degree four, three, and two, respectively. The nonlinear feedback control law is presented. Stability in a neighborhood of a controllable torque equilibrium attitude (TEA) is guaranteed and this fact is demonstrated by the simulation results. An investigation of the nonlinear control law shows that singularities exist in the state space outside the neighborhood of the controllable TEA. The nonlinear control law is simplified by a standard linearization technique and it is shown that the linearized nonlinear controller provides a natural way to select control gains for the multiple-input, multiple-output system. Simulation results using the linearized nonlinear controller show good performance relative to the nonlinear controller in the neighborhood of the TEA.

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.

Strong suppression of shot noise in a feedback-controlled single-electron transistor

NASA Astrophysics Data System (ADS)

Wagner, Timo; Strasberg, Philipp; Bayer, Johannes C.; Rugeramigabo, Eddy P.; Brandes, Tobias; Haug, Rolf J.

2017-03-01

Feedback control of quantum mechanical systems is rapidly attracting attention not only due to fundamental questions about quantum measurements, but also because of its novel applications in many fields in physics. Quantum control has been studied intensively in quantum optics but progress has recently been made in the control of solid-state qubits as well. In quantum transport only a few active and passive feedback experiments have been realized on the level of single electrons, although theoretical proposals exist. Here we demonstrate the suppression of shot noise in a single-electron transistor using an exclusively electronic closed-loop feedback to monitor and adjust the counting statistics. With increasing feedback response we observe a stronger suppression and faster freezing of charge current fluctuations. Our technique is analogous to the generation of squeezed light with in-loop photodetection as used in quantum optics. Sub-Poisson single-electron sources will pave the way for high-precision measurements in quantum transport similar to optical or optomechanical equivalents.

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.

Real-time control of hind limb functional electrical stimulation using feedback from dorsal root ganglia recordings

NASA Astrophysics Data System (ADS)

Bruns, Tim M.; Wagenaar, Joost B.; Bauman, Matthew J.; Gaunt, Robert A.; Weber, Douglas J.

2013-04-01

Objective. Functional electrical stimulation (FES) approaches often utilize an open-loop controller to drive state transitions. The addition of sensory feedback may allow for closed-loop control that can respond effectively to perturbations and muscle fatigue. Approach. We evaluated the use of natural sensory nerve signals obtained with penetrating microelectrode arrays in lumbar dorsal root ganglia (DRG) as real-time feedback for closed-loop control of FES-generated hind limb stepping in anesthetized cats. Main results. Leg position feedback was obtained in near real-time at 50 ms intervals by decoding the firing rates of more than 120 DRG neurons recorded simultaneously. Over 5 m of effective linear distance was traversed during closed-loop stepping trials in each of two cats. The controller compensated effectively for perturbations in the stepping path when DRG sensory feedback was provided. The presence of stimulation artifacts and the quality of DRG unit sorting did not significantly affect the accuracy of leg position feedback obtained from the linear decoding model as long as at least 20 DRG units were included in the model. Significance. This work demonstrates the feasibility and utility of closed-loop FES control based on natural neural sensors. Further work is needed to improve the controller and electrode technologies and to evaluate long-term viability.

Real-time control of hind limb functional electrical stimulation using feedback from dorsal root ganglia recordings

PubMed Central

Bruns, Tim M; Wagenaar, Joost B; Bauman, Matthew J; Gaunt, Robert A; Weber, Douglas J

2013-01-01

Objective Functional electrical stimulation (FES) approaches often utilize an open-loop controller to drive state transitions. The addition of sensory feedback may allow for closed-loop control that can respond effectively to perturbations and muscle fatigue. Approach We evaluated the use of natural sensory nerve signals obtained with penetrating microelectrode arrays in lumbar dorsal root ganglia (DRG) as real-time feedback for closed-loop control of FES-generated hind limb stepping in anesthetized cats. Main results Leg position feedback was obtained in near real-time at 50 ms intervals by decoding the firing rates of more than 120 DRG neurons recorded simultaneously. Over 5 m of effective linear distance was traversed during closed-loop stepping trials in each of two cats. The controller compensated effectively for perturbations in the stepping path when DRG sensory feedback was provided. The presence of stimulation artifacts and the quality of DRG unit sorting did not significantly affect the accuracy of leg position feedback obtained from the linear decoding model as long as at least 20 DRG units were included in the model. Significance This work demonstrates the feasibility and utility of closed-loop FES control based on natural neural sensors. Further work is needed to improve the controller and electrode technologies and to evaluate long-term viability. PMID:23503062

Control of flexible beams using a free-free active truss

NASA Technical Reports Server (NTRS)

Clark, W. W.; Kimiavi, B.; Robertshaw, H. H.

1989-01-01

An analytical and experimental study involving controlling flexible beams using a free-free active truss is presented. This work extends previous work in controlling flexible continua with active trusses which were configured with fixed-free boundary conditions. The following describes the Lagrangian approach used to derive the equations of motion for the active truss and the beams attached to it. A partial-state feedback control law is derived for this system based on a full-state feedback Linear Quadratic Regulator method. The analytical model is examined via numerical simulations and the results are compared to a similar experimental apparatus described herein. The results show that control of a flexible continua is possible with a free-free active truss.

State feedback control design for Boolean networks.

PubMed

Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang

2016-08-26

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.

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.

Adaptive output-feedback control for switched stochastic uncertain nonlinear systems with time-varying delay.

PubMed

Song, Zhibao; Zhai, Junyong

2018-04-01

This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Differential Flatness and Cooperative Tracking in the Lorenz System

NASA Technical Reports Server (NTRS)

Crespo, Luis G.

2002-01-01

In this paper the control of the Lorenz system for both stabilization and tracking problems is studied via feedback linearization and differential flatness. By using the Rayleigh number as the control, only variable physically tunable, a barrier in the controllability of the system is incidentally imposed. This is reflected in the appearance of a singularity in the state transformation. Composite controllers that overcome this difficulty are designed and evaluated. The transition through the manifold defined by such a singularity is achieved by inducing a chaotic response within a boundary layer that contains it. Outside this region, a conventional feedback nonlinear control is applied. In this fashion, the authority of the control is enlarged to the whole. state space and the need for high control efforts is mitigated. In addition, the differential parametrization of the problem is used to track nonlinear functions of one state variable (single tracking) as well as several state variables (cooperative tracking). Control tasks that lead to integrable and non-integrable differential equations for the nominal flat output in steady-state are considered. In particular, a novel numerical strategy to deal with the non-integrable case is proposed. Numerical results validate very well the control design.

Leader-Follower Formation Control of UUVs with Model Uncertainties, Current Disturbances, and Unstable Communication

PubMed Central

Yan, Zheping; Xu, Da; Chen, Tao; Zhang, Wei; Liu, Yibo

2018-01-01

Unmanned underwater vehicles (UUVs) have rapidly developed as mobile sensor networks recently in the investigation, survey, and exploration of the underwater environment. The goal of this paper is to develop a practical and efficient formation control method to improve work efficiency of multi-UUV sensor networks. Distributed leader-follower formation controllers are designed based on a state feedback and consensus algorithm. Considering that each vehicle is subject to model uncertainties and current disturbances, a second-order integral UUV model with a nonlinear function is established using the state feedback linearized method under current disturbances. For unstable communication among UUVs, communication failure and acoustic link noise interference are considered. Two-layer random switching communication topologies are proposed to solve the problem of communication failure. For acoustic link noise interference, accurate representation of valid communication information and noise stripping when designing controllers is necessary. Effective communication topology weights are designed to represent the validity of communication information interfered by noise. Utilizing state feedback and noise stripping, sufficient conditions for design formation controllers are proposed to ensure UUV formation achieves consensus under model uncertainties, current disturbances, and unstable communication. The stability of formation controllers is proven by the Lyapunov-Razumikhin theorem, and the validity is verified by simulation results. PMID:29473919

Large deviation analysis of a simple information engine

NASA Astrophysics Data System (ADS)

Maitland, Michael; Grosskinsky, Stefan; Harris, Rosemary J.

2015-11-01

Information thermodynamics provides a framework for studying the effect of feedback loops on entropy production. It has enabled the understanding of novel thermodynamic systems such as the information engine, which can be seen as a modern version of "Maxwell's Dæmon," whereby a feedback controller processes information gained by measurements in order to extract work. Here, we analyze a simple model of such an engine that uses feedback control based on measurements to obtain negative entropy production. We focus on the distribution and fluctuations of the information obtained by the feedback controller. Significantly, our model allows an analytic treatment for a two-state system with exact calculation of the large deviation rate function. These results suggest an approximate technique for larger systems, which is corroborated by simulation data.

Stabilisation of time-varying linear systems via Lyapunov differential equations

NASA Astrophysics Data System (ADS)

Zhou, Bin; Cai, Guang-Bin; Duan, Guang-Ren

2013-02-01

This article studies stabilisation problem for time-varying linear systems via state feedback. Two types of controllers are designed by utilising solutions to Lyapunov differential equations. The first type of feedback controllers involves the unique positive-definite solution to a parametric Lyapunov differential equation, which can be solved when either the state transition matrix of the open-loop system is exactly known, or the future information of the system matrices are accessible in advance. Different from the first class of controllers which may be difficult to implement in practice, the second type of controllers can be easily implemented by solving a state-dependent Lyapunov differential equation with a given positive-definite initial condition. In both cases, explicit conditions are obtained to guarantee the exponentially asymptotic stability of the associated closed-loop systems. Numerical examples show the effectiveness of the proposed approaches.

Linear Matrix Inequality Method for a Quadratic Performance Index Minimization Problem with a class of Bilinear Matrix Inequality Conditions

NASA Astrophysics Data System (ADS)

Tanemura, M.; Chida, Y.

2016-09-01

There are a lot of design problems of control system which are expressed as a performance index minimization under BMI conditions. However, a minimization problem expressed as LMIs can be easily solved because of the convex property of LMIs. Therefore, many researchers have been studying transforming a variety of control design problems into convex minimization problems expressed as LMIs. This paper proposes an LMI method for a quadratic performance index minimization problem with a class of BMI conditions. The minimization problem treated in this paper includes design problems of state-feedback gain for switched system and so on. The effectiveness of the proposed method is verified through a state-feedback gain design for switched systems and a numerical simulation using the designed feedback gains.

Use of digital control theory state space formalism for feedback at SLC

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

Himel, T.; Hendrickson, L.; Rouse, F.

The algorithms used in the database-driven SLC fast-feedback system are based on the state space formalism of digital control theory. These are implemented as a set of matrix equations which use a Kalman filter to estimate a vector of states from a vector of measurements, and then apply a gain matrix to determine the actuator settings from the state vector. The matrices used in the calculation are derived offline using Linear Quadratic Gaussian minimization. For a given noise spectrum, this procedure minimizes the rms of the states (e.g., the position or energy of the beam). The offline program also allowsmore » simulation of the loop's response to arbitrary inputs, and calculates its frequency response. 3 refs., 3 figs.« less

Steady-state bumpless transfer under controller uncertainty using the state/output feedback topology

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

Zheng, K.; Lee, A.H.; Bentsman, J.

2006-01-15

Linear quadratic (LQ) bumpless transfer design introduced recently by Turner and Walker gives a very convenient and straightforward computational procedure for the steady-state bumpless transfer operator synthesis. It is, however, found to be incapable of providing convergence of the output of the offline controller to that of the online controller in several industrial applications, producing bumps in the plant output in the wake of controller transfer. An examination of this phenomenon reveals that the applications in question are characterized by a significant mismatch, further referred to as controller uncertainty, between the dynamics of the implemented controllers and their models usedmore » in the transfer operator computation. To address this problem, while retaining the convenience of the Turner and Walker design, a novel state/output feedback bumpless transfer topology is introduced that employs the nominal state of the offline controller and, through the use of an additional controller/model mismatch compensator, also the offline controller output. A corresponding steady-state bumpless transfer design procedure along with the supporting theory is developed for a large class of systems. Due to these features, it is demonstrated to solve a long-standing problem of high-quality steady-state bumpless transfer from the industry standard low-order nonlinear multiloop PID-based controllers to the modern multiinput-multioutput (MIMO) robust controllers in the megawatt/throttle pressure control of a typical coal-fired boiler/turbine unit.« less

Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on polynomial-fuzzy-model-based control approach.

PubMed

Lam, H K

2012-02-01

This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.

Neural feedback for instantaneous spatiotemporal modulation of afferent pathways in bi-directional brain-machine interfaces.

PubMed

Liu, Jianbo; Khalil, Hassan K; Oweiss, Karim G

2011-10-01

In bi-directional brain-machine interfaces (BMIs), precisely controlling the delivery of microstimulation, both in space and in time, is critical to continuously modulate the neural activity patterns that carry information about the state of the brain-actuated device to sensory areas in the brain. In this paper, we investigate the use of neural feedback to control the spatiotemporal firing patterns of neural ensembles in a model of the thalamocortical pathway. Control of pyramidal (PY) cells in the primary somatosensory cortex (S1) is achieved based on microstimulation of thalamic relay cells through multiple-input multiple-output (MIMO) feedback controllers. This closed loop feedback control mechanism is achieved by simultaneously varying the stimulation parameters across multiple stimulation electrodes in the thalamic circuit based on continuous monitoring of the difference between reference patterns and the evoked responses of the cortical PY cells. We demonstrate that it is feasible to achieve a desired level of performance by controlling the firing activity pattern of a few "key" neural elements in the network. Our results suggest that neural feedback could be an effective method to facilitate the delivery of information to the cortex to substitute lost sensory inputs in cortically controlled BMIs.

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression.

PubMed

Agrawal, Deepak K; Tang, Xun; Westbrook, Alexandra; Marshall, Ryan; Maxwell, Colin S; Lucks, Julius; Noireaux, Vincent; Beisel, Chase L; Dunlop, Mary J; Franco, Elisa

2018-05-08

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.

Flatness-based adaptive fuzzy control of chaotic finance dynamics

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

2017-11-01

A flatness-based adaptive fuzzy control is applied to the problem of stabilization of the dynamics of a chaotic finance system, describing interaction between the interest rate, the investment demand and the price exponent. By proving that the system is differentially flat and by applying differential flatness diffeomorphisms, its transformation to the linear canonical (Brunovsky) is performed. For the latter description of the system, the design of a stabilizing state feedback controller becomes possible. A first problem in the design of such a controller is that the dynamic model of the finance system is unknown and thus it has to be identified with the use neurofuzzy approximators. The estimated dynamics provided by the approximators is used in the computation of the control input, thus establishing an indirect adaptive control scheme. The learning rate of the approximators is chosen from the requirement the system's Lyapunov function to have always a negative first-order derivative. Another problem that has to be dealt with is that the control loop is implemented only with the use of output feedback. To estimate the non-measurable state vector elements of the finance system, a state observer is implemented in the control loop. The computation of the feedback control signal requires the solution of two algebraic Riccati equations at each iteration of the control algorithm. Lyapunov stability analysis demonstrates first that an H-infinity tracking performance criterion is satisfied. This signifies elevated robustness against modelling errors and external perturbations. Moreover, the global asymptotic stability is proven for the control loop.

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

Global tracking for a class of uncertain nonlinear systems with unknown sign-switching control direction by output feedback

NASA Astrophysics Data System (ADS)

Roux Oliveira, Tiago; Jacoud Peixoto, Alessandro; Hsu, Liu

2015-09-01

This paper addresses the design of a sliding mode controller for a class of high-order uncertain nonlinear plants with unmatched state-dependent nonlinearities and unknown sign of the high frequency gain, i.e., the control direction is assumed unknown. Differently from most previous studies, the control direction is allowed to switch its sign. We show that it is possible to obtain global exact tracking using only output-feedback by coupling a relay periodic switching function with a norm state observer. One significant advantage of the new scheme is its robustness and improved transient response under arbitrary changes of the control direction which have been theoretically demonstrated for jump variations and successfully tested by simulations. The proposed controller is also evaluated with a DC motor control experiment.

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.

Decoupled and linear quadratic regulator control of a large, flexible space antenna with an observer in the control loop

NASA Technical Reports Server (NTRS)

Hamer, H. A.; Johnson, K. G.; Young, J. W.

1985-01-01

An analysis is performed to compare decoupled and linear quadratic regulator (LQR) procedures for the control of a large, flexible space antenna. Control objectives involve: (1) commanding changes in the rigid-body modes, (2) nulling initial disturbances in the rigid-body modes, or (3) nulling initial disturbances in the first three flexible modes. Control is achieved with two three-axis control-moment gyros located on the antenna column. Results are presented to illustrate various effects on control requirements for the two procedures. These effects include errors in the initial estimates of state variables, variations in the type, number, and location of sensors, and deletions of state-variable estimates for certain flexible modes after control activation. The advantages of incorporating a time lag in the control feedback are also illustrated. In addition, the effects of inoperative-control situations are analyzed with regard to control requirements and resultant modal responses. Comparisons are included which show the effects of perfect state feedback with no residual modes (ideal case). Time-history responses are presented to illustrate the various effects on the control procedures.

State reference design and saturated control of doubly-fed induction generators under voltage dips

NASA Astrophysics Data System (ADS)

Tilli, Andrea; Conficoni, Christian; Hashemi, Ahmad

2017-04-01

In this paper, the stator/rotor currents control problem of doubly-fed induction generator under faulty line voltage is carried out. Common grid faults cause a steep decline in the line voltage profile, commonly denoted as voltage dip. This point is critical for such kind of machines, having their stator windings directly connected to the grid. In this respect, solid methodological nonlinear control theory arguments are exploited and applied to design a novel controller, whose main goal is to improve the system behaviour during voltage dips, endowing it with low voltage ride through capability, a fundamental feature required by modern Grid Codes. The proposed solution exploits both feedforward and feedback actions. The feedforward part relies on suitable reference trajectories for the system internal dynamics, which are designed to prevent large oscillations in the rotor currents and command voltages, excited by line perturbations. The feedback part uses state measurements and is designed according to Linear Matrix Inequalities (LMI) based saturated control techniques to further reduce oscillations, while explicitly accounting for the system constraints. Numerical simulations verify the benefits of the internal dynamics trajectory planning, and the saturated state feedback action, in crucially improving the Doubly-Fed Induction Machine response under severe grid faults.

Integration of sensory force feedback is disturbed in CRPS-related dystonia.

PubMed

Mugge, Winfred; van der Helm, Frans C T; Schouten, Alfred C

2013-01-01

Complex regional pain syndrome (CRPS) is characterized by pain and disturbed blood flow, temperature regulation and motor control. Approximately 25% of cases develop fixed dystonia. The origin of this movement disorder is poorly understood, although recent insights suggest involvement of disturbed force feedback. Assessment of sensorimotor integration may provide insight into the pathophysiology of fixed dystonia. Sensory weighting is the process of integrating and weighting sensory feedback channels in the central nervous system to improve the state estimate. It was hypothesized that patients with CRPS-related dystonia bias sensory weighting of force and position toward position due to the unreliability of force feedback. The current study provides experimental evidence for dysfunctional sensory integration in fixed dystonia, showing that CRPS-patients with fixed dystonia weight force and position feedback differently than controls do. The study shows reduced force feedback weights in CRPS-patients with fixed dystonia, making it the first to demonstrate disturbed integration of force feedback in fixed dystonia, an important step towards understanding the pathophysiology of fixed dystonia.

Development of electrical feedback controlled heat pipes and the advanced thermal control flight experiment

NASA Technical Reports Server (NTRS)

Bienert, W. B.

1974-01-01

The development and characteristics of electrical feedback controlled heat pipes (FCHP) are discussed. An analytical model was produced to describe the performance of the FCHP under steady state and transient conditions. An advanced thermal control flight experiment was designed to demonstrate the performance of the thermal control component in a space environment. The thermal control equipment was evaluated on the ATS-F satellite to provide performance data for the components and to act as a thermal control system which can be used to provide temperature stability of spacecraft components in future applications.

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.

Phase I to II cross-induction of xenobiotic metabolizing enzymes: a feedforward control mechanism for potential hormetic responses.

PubMed

Zhang, Qiang; Pi, Jingbo; Woods, Courtney G; Andersen, Melvin E

2009-06-15

Hormetic responses to xenobiotic exposure likely occur as a result of overcompensation by the homeostatic control systems operating in biological organisms. However, the mechanisms underlying overcompensation that leads to hormesis are still unclear. A well-known homeostatic circuit in the cell is the gene induction network comprising phase I, II and III metabolizing enzymes, which are responsible for xenobiotic detoxification, and in many cases, bioactivation. By formulating a differential equation-based computational model, we investigated in this study whether hormesis can arise from the operation of this gene/enzyme network. The model consists of two feedback and one feedforward controls. With the phase I negative feedback control, xenobiotic X activates nuclear receptors to induce cytochrome P450 enzyme, which bioactivates X into a reactive metabolite X'. With the phase II negative feedback control, X' activates transcription factor Nrf2 to induce phase II enzymes such as glutathione S-transferase and glutamate cysteine ligase, etc., which participate in a set of reactions that lead to the metabolism of X' into a less toxic conjugate X''. The feedforward control involves phase I to II cross-induction, in which the parent chemical X can also induce phase II enzymes directly through the nuclear receptor and indirectly through transcriptionally upregulating Nrf2. As a result of the active feedforward control, a steady-state hormetic relationship readily arises between the concentrations of the reactive metabolite X' and the extracellular parent chemical X to which the cell is exposed. The shape of dose-response evolves over time from initially monotonically increasing to J-shaped at the final steady state-a temporal sequence consistent with adaptation-mediated hormesis. The magnitude of the hormetic response is enhanced by increases in the feedforward gain, but attenuated by increases in the bioactivation or phase II feedback loop gains. Our study suggests a possibly common mechanism for the hormetic responses observed with many mutagens/carcinogens whose activities require bioactivation by phase I enzymes. Feedforward control, often operating in combination with negative feedback regulation in a homeostatic system, may be a general control theme responsible for steady-state hormesis.

A nonlinear Kalman filtering approach to embedded control of turbocharged diesel engines

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Arsie, Ivan

2014-10-01

The development of efficient embedded control for turbocharged Diesel engines, requires the programming of elaborated nonlinear control and filtering methods. To this end, in this paper nonlinear control for turbocharged Diesel engines is developed with the use of Differential flatness theory and the Derivative-free nonlinear Kalman Filter. It is shown that the dynamic model of the turbocharged Diesel engine is differentially flat and admits dynamic feedback linearization. It is also shown that the dynamic model can be written in the linear Brunovsky canonical form for which a state feedback controller can be easily designed. To compensate for modeling errors and external disturbances the Derivative-free nonlinear Kalman Filter is used and redesigned as a disturbance observer. The filter consists of the Kalman Filter recursion on the linearized equivalent of the Diesel engine model and of an inverse transformation based on differential flatness theory which enables to obtain estimates for the state variables of the initial nonlinear model. Once the disturbances variables are identified it is possible to compensate them by including an additional control term in the feedback loop. The efficiency of the proposed control method is tested through simulation experiments.

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.

The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis.

PubMed

Markovic, Marko; Schweisfurth, Meike A; Engels, Leonard F; Bentz, Tashina; Wüstefeld, Daniela; Farina, Dario; Dosen, Strahinja

2018-03-27

To effectively replace the human hand, a prosthesis should seamlessly respond to user intentions but also convey sensory information back to the user. Restoration of sensory feedback is rated highly by the prosthesis users, and feedback is critical for grasping in able-bodied subjects. Nonetheless, the benefits of feedback in prosthetics are still debated. The lack of consensus is likely due to the complex nature of sensory feedback during prosthesis control, so that its effectiveness depends on multiple factors (e.g., task complexity, user learning). We evaluated the impact of these factors with a longitudinal assessment in six amputee subjects, using a clinical setup (socket, embedded control) and a range of tasks (box and blocks, block turn, clothespin and cups relocation). To provide feedback, we have proposed a novel vibrotactile stimulation scheme capable of transmitting multiple variables from a multifunction prosthesis. The subjects wore a bracelet with four by two uniformly placed vibro-tactors providing information on contact, prosthesis state (active function), and grasping force. The subjects also completed a questionnaire for the subjective evaluation of the feedback. The tests demonstrated that feedback was beneficial only in the complex tasks (block turn, clothespin and cups relocation), and that the training had an important, task-dependent impact. In the clothespin relocation and block turn tasks, training allowed the subjects to establish successful feedforward control, and therefore, the feedback became redundant. In the cups relocation task, however, the subjects needed some training to learn how to properly exploit the feedback. The subjective evaluation of the feedback was consistently positive, regardless of the objective benefits. These results underline the multifaceted nature of closed-loop prosthesis control as, depending on the context, the same feedback interface can have different impact on performance. Finally, even if the closed-loop control does not improve the performance, it could be beneficial as it seems to improve the subjective experience. Therefore, in this study we demonstrate, for the first time, the relevance of an advanced, multi-variable feedback interface for dexterous, multi-functional prosthesis control in a clinically relevant setting.

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.

System identification from closed-loop data with known output feedback dynamics

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Horta, Lucas G.; Longman, Richard W.

1992-01-01

This paper presents a procedure to identify the open loop systems when it is operating under closed loop conditions. First, closed loop excitation data are used to compute the system open loop and closed loop Markov parameters. The Markov parameters, which are the pulse response samples, are then used to compute a state space representation of the open loop system. Two closed loop configurations are considered in this paper. The closed loop system can have either a linear output feedback controller or a dynamic output feedback controller. Numerical examples are provided to illustrate the proposed closed loop identification method.

Dynamics of bow-tie shaped bursting: Forced pendulum with dynamic feedback.

PubMed

Hongray, Thotreithem; Balakrishnan, Janaki

2016-12-01

A detailed study is performed on the parameter space of the mechanical system of a driven pendulum with damping and constant torque under feedback control. We report an interesting bow-tie shaped bursting oscillatory behaviour, which is exhibited for small driving frequencies, in a certain parameter regime, which has not been reported earlier in this forced system with dynamic feedback. We show that the bursting oscillations are caused because of a transition of the quiescent state to the spiking state by a saddle-focus bifurcation, and because of another saddle-focus bifurcation, which leads to cessation of spiking, bringing the system back to the quiescent state. The resting period between two successive bursts (T rest ) is estimated analytically.

Electrocardiographic anxiety profiles improve speech anxiety.

PubMed

Kim, Pyoung Won; Kim, Seung Ae; Jung, Keun-Hwa

2012-12-01

The present study was to set out in efforts to determine the effect of electrocardiographic (ECG) feedback on the performance in speech anxiety. Forty-six high school students participated in a speech performance educational program. They were randomly divided into two groups, an experimental group with ECG feedback (N = 21) and a control group (N = 25). Feedback was given with video recording in the control, whereas in the experimental group, an additional ECG feedback was provided. Speech performance was evaluated by the Korean Broadcasting System (KBS) speech ability test, which determines the 10 different speaking categories. ECG was recorded during rest and speech, together with a video recording of the speech performance. Changes in R-R intervals were used to reflect anxiety profiles. Three trials were performed for 3-week program. Results showed that the subjects with ECG feedback revealed a significant improvement in speech performance and anxiety states, which compared to those in the control group. These findings suggest that visualization of the anxiety profile feedback with ECG can be a better cognitive therapeutic strategy in speech anxiety.

Identification of linear system models and state estimators for controls

NASA Technical Reports Server (NTRS)

Chen, Chung-Wen

1992-01-01

The following paper is presented in viewgraph format and covers topics including: (1) linear state feedback control system; (2) Kalman filter state estimation; (3) relation between residual and stochastic part of output; (4) obtaining Kalman filter gain; (5) state estimation under unknown system model and unknown noises; and (6) relationship between filter Markov parameters and system Markov parameters.

Further results on global state feedback stabilization of nonlinear high-order feedforward systems.

PubMed

Xie, Xue-Jun; Zhang, Xing-Hui

2014-03-01

In this paper, by introducing a combined method of sign function, homogeneous domination and adding a power integrator, and overcoming several troublesome obstacles in the design and analysis, the problem of state feedback control for a class of nonlinear high-order feedforward systems with the nonlinearity's order being relaxed to an interval rather than a fixed point is solved. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

PubMed

Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

2015-02-01

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

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.

Digital adaptive control of a VTOL aircraft

NASA Technical Reports Server (NTRS)

Reid, G. F.

1976-01-01

A technique has been developed for calculating feedback and feedforward gain matrices that stabilize a VTOL aircraft while enabling it to track input commands of forward and vertical velocity. Leverrier's algorithm is used in a procedure for determining a set of state variable, feedback gains that force the closed loop poles and zeroes of one pilot input transfer function to be at preselected positions in the s plane. This set of feedback gains is then used to calculate the feedback and feedforward gains for the velocity command controller. The method is computationally attractive since the gains are determined by solving systems of linear, simultaneous equations. Responses obtained using a digital simulation of the longitudinal dynamics of the CH-47 helicopter are presented.

Accountability Policies and Teachers' Acceptance and Usage of School Performance Feedback--A Comparative Study

ERIC Educational Resources Information Center

Maier, Uwe

2010-01-01

This paper implemented a comparative approach to investigate the relationships between test-based school accountability policies in 2 German states and teachers' acceptance and usage of feedback information. Thuringia implemented mandatory tests for secondary schools based on competency modeling and performance data controlled for socioeconomic…

Control-based continuation: Bifurcation and stability analysis for physical experiments

NASA Astrophysics Data System (ADS)

Barton, David A. W.

2017-02-01

Control-based continuation is technique for tracking the solutions and bifurcations of nonlinear experiments. The idea is to apply the method of numerical continuation to a feedback-controlled physical experiment such that the control becomes non-invasive. Since in an experiment it is not (generally) possible to set the state of the system directly, the control target becomes a proxy for the state. Control-based continuation enables the systematic investigation of the bifurcation structure of a physical system, much like if it was numerical model. However, stability information (and hence bifurcation detection and classification) is not readily available due to the presence of stabilising feedback control. This paper uses a periodic auto-regressive model with exogenous inputs (ARX) to approximate the time-varying linearisation of the experiment around a particular periodic orbit, thus providing the missing stability information. This method is demonstrated using a physical nonlinear tuned mass damper.

Active vibration control with model correction on a flexible laboratory grid structure

NASA Technical Reports Server (NTRS)

Schamel, George C., II; Haftka, Raphael T.

1991-01-01

This paper presents experimental and computational comparisons of three active damping control laws applied to a complex laboratory structure. Two reduced structural models were used with one model being corrected on the basis of measured mode shapes and frequencies. Three control laws were investigated, a time-invariant linear quadratic regulator with state estimation and two direct rate feedback control laws. Experimental results for all designs were obtained with digital implementation. It was found that model correction improved the agreement between analytical and experimental results. The best agreement was obtained with the simplest direct rate feedback control.

Reinforcement-learning-based dual-control methodology for complex nonlinear discrete-time systems with application to spark engine EGR operation.

PubMed

Shih, Peter; Kaul, Brian C; Jagannathan, S; Drallmeier, James A

2008-08-01

A novel reinforcement-learning-based dual-control methodology adaptive neural network (NN) controller is developed to deliver a desired tracking performance for a class of complex feedback nonlinear discrete-time systems, which consists of a second-order nonlinear discrete-time system in nonstrict feedback form and an affine nonlinear discrete-time system, in the presence of bounded and unknown disturbances. For example, the exhaust gas recirculation (EGR) operation of a spark ignition (SI) engine is modeled by using such a complex nonlinear discrete-time system. A dual-controller approach is undertaken where primary adaptive critic NN controller is designed for the nonstrict feedback nonlinear discrete-time system whereas the secondary one for the affine nonlinear discrete-time system but the controllers together offer the desired performance. The primary adaptive critic NN controller includes an NN observer for estimating the states and output, an NN critic, and two action NNs for generating virtual control and actual control inputs for the nonstrict feedback nonlinear discrete-time system, whereas an additional critic NN and an action NN are included for the affine nonlinear discrete-time system by assuming the state availability. All NN weights adapt online towards minimization of a certain performance index, utilizing gradient-descent-based rule. Using Lyapunov theory, the uniformly ultimate boundedness (UUB) of the closed-loop tracking error, weight estimates, and observer estimates are shown. The adaptive critic NN controller performance is evaluated on an SI engine operating with high EGR levels where the controller objective is to reduce cyclic dispersion in heat release while minimizing fuel intake. Simulation and experimental results indicate that engine out emissions drop significantly at 20% EGR due to reduction in dispersion in heat release thus verifying the dual-control approach.

Relative position finite-time coordinated tracking control of spacecraft formation without velocity measurements.

PubMed

Hu, Qinglei; Zhang, Jian

2015-01-01

This paper investigates finite-time relative position coordinated tracking problem by output feedback for spacecraft formation flying without velocity measurement. By employing homogeneous system theory, a finite-time relative position coordinated tracking controller by state feedback is firstly developed, where the desired time-varying trajectory given in advance can be tracked by the formation. Then, to address the problem of lack of velocity measurements, a finite-time output feedback controller is proposed by involving a novel filter to recover unknown velocity information in a finite time. Rigorous proof shows that the proposed control law ensures global stability and guarantees the position of spacecraft formation to track a time-varying reference in finite time. Finally, simulation results are presented to illustrate the performance of the proposed controller. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Flight control synthesis for flexible aircraft using Eigenspace assignment

NASA Technical Reports Server (NTRS)

Davidson, J. B.; Schmidt, D. K.

1986-01-01

The use of eigenspace assignment techniques to synthesize flight control systems for flexible aircraft is explored. Eigenspace assignment techniques are used to achieve a specified desired eigenspace, chosen to yield desirable system impulse residue magnitudes for selected system responses. Two of these are investigated. The first directly determines constant measurement feedback gains that will yield a close-loop system eigenspace close to a desired eigenspace. The second technique selects quadratic weighting matrices in a linear quadratic control synthesis that will asymptotically yield the close-loop achievable eigenspace. Finally, the possibility of using either of these techniques with state estimation is explored. Application of the methods to synthesize integrated flight-control and structural-mode-control laws for a large flexible aircraft is demonstrated and results discussed. Eigenspace selection criteria based on design goals are discussed, and for the study case it would appear that a desirable eigenspace can be obtained. In addition, the importance of state-space selection is noted along with problems with reduced-order measurement feedback. Since the full-state control laws may be implemented with dynamic compensation (state estimation), the use of reduced-order measurement feedback is less desirable. This is especially true since no change in the transient response from the pilot's input results if state estimation is used appropriately. The potential is also noted for high actuator bandwidth requirements if the linear quadratic synthesis approach is utilized. Even with the actuator pole location selected, a problem with unmodeled modes is noted due to high bandwidth. Some suggestions for future research include investigating how to choose an eigenspace that will achieve certain desired dynamics and stability robustness, determining how the choice of measurements effects synthesis results, and exploring how the phase relationships between desired eigenvector elements effects the synthesis results.

Improvement of time-delayed feedback control by periodic modulation: analytical theory of Floquet mode control scheme.

PubMed

Just, Wolfram; Popovich, Svitlana; Amann, Andreas; Baba, Nilüfer; Schöll, Eckehard

2003-02-01

We investigate time-delayed feedback control schemes which are based on the unstable modes of the target state, to stabilize unstable periodic orbits. The periodic time dependence of these modes introduces an external time scale in the control process. Phase shifts that develop between these modes and the controlled periodic orbit may lead to a huge increase of the control performance. We illustrate such a feature on a nonlinear reaction diffusion system with global coupling and give a detailed investigation for the Rössler model. In addition we provide the analytical explanation for the observed control features.

Multivariable control theory applied to hierarchial attitude control for planetary spacecraft

NASA Technical Reports Server (NTRS)

Boland, J. S., III; Russell, D. W.

1972-01-01

Multivariable control theory is applied to the design of a hierarchial attitude control system for the CARD space vehicle. The system selected uses reaction control jets (RCJ) and control moment gyros (CMG). The RCJ system uses linear signal mixing and a no-fire region similar to that used on the Skylab program; the y-axis and z-axis systems which are coupled use a sum and difference feedback scheme. The CMG system uses the optimum steering law and the same feedback signals as the RCJ system. When both systems are active the design is such that the torques from each system are never in opposition. A state-space analysis was made of the CMG system to determine the general structure of the input matrices (steering law) and feedback matrices that will decouple the axes. It is shown that the optimum steering law and proportional-plus-rate feedback are special cases. A derivation of the disturbing torques on the space vehicle due to the motion of the on-board television camera is presented. A procedure for computing an upper bound on these torques (given the system parameters) is included.

Mittag-Leffler synchronization of delayed fractional-order bidirectional associative memory neural networks with discontinuous activations: state feedback control and impulsive control schemes.

PubMed

Ding, Xiaoshuai; Cao, Jinde; Zhao, Xuan; Alsaadi, Fuad E

2017-08-01

This paper is concerned with the drive-response synchronization for a class of fractional-order bidirectional associative memory neural networks with time delays, as well as in the presence of discontinuous activation functions. The global existence of solution under the framework of Filippov for such networks is firstly obtained based on the fixed-point theorem for condensing map. Then the state feedback and impulsive controllers are, respectively, designed to ensure the Mittag-Leffler synchronization of these neural networks and two new synchronization criteria are obtained, which are expressed in terms of a fractional comparison principle and Razumikhin techniques. Numerical simulations are presented to validate the proposed methodologies.

Output feedback control for a class of nonlinear systems with actuator degradation and sensor noise.

PubMed

Ai, Weiqing; Lu, Zhenli; Li, Bin; Fei, Shumin

2016-11-01

This paper investigates the output feedback control problem of a class of nonlinear systems with sensor noise and actuator degradation. Firstly, by using the descriptor observer approach, the origin system is transformed into a descriptor system. On the basis of the descriptor system, a novel Proportional Derivative (PD) observer is developed to asymptotically estimate sensor noise and system state simultaneously. Then, by designing an adaptive law to estimate the effectiveness of actuator, an adaptive observer-based controller is constructed to ensure that system state can be regulated to the origin asymptotically. Finally, the design scheme is applied to address a flexible joint robot link problem. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Desynchronization in an ensemble of globally coupled chaotic bursting neuronal oscillators by dynamic delayed feedback control

NASA Astrophysics Data System (ADS)

Che, Yanqiu; Yang, Tingting; Li, Ruixue; Li, Huiyan; Han, Chunxiao; Wang, Jiang; Wei, Xile

2015-09-01

In this paper, we propose a dynamic delayed feedback control approach or desynchronization of chaotic-bursting synchronous activities in an ensemble of globally coupled neuronal oscillators. We demonstrate that the difference signal between an ensemble's mean field and its time delayed state, filtered and fed back to the ensemble, can suppress the self-synchronization in the ensemble. These individual units are decoupled and stabilized at the desired desynchronized states while the stimulation signal reduces to the noise level. The effectiveness of the method is illustrated by examples of two different populations of globally coupled chaotic-bursting neurons. The proposed method has potential for mild, effective and demand-controlled therapy of neurological diseases characterized by pathological synchronization.

Eigenvalue assignment by minimal state-feedback gain in LTI multivariable systems

NASA Astrophysics Data System (ADS)

Ataei, Mohammad; Enshaee, Ali

2011-12-01

In this article, an improved method for eigenvalue assignment via state feedback in the linear time-invariant multivariable systems is proposed. This method is based on elementary similarity operations, and involves mainly utilisation of vector companion forms, and thus is very simple and easy to implement on a digital computer. In addition to the controllable systems, the proposed method can be applied for the stabilisable ones and also systems with linearly dependent inputs. Moreover, two types of state-feedback gain matrices can be achieved by this method: (1) the numerical one, which is unique, and (2) the parametric one, in which its parameters are determined in order to achieve a gain matrix with minimum Frobenius norm. The numerical examples are presented to demonstrate the advantages of the proposed method.

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

Performance recovery of a class of uncertain non-affine systems with unmodelled dynamics: an indirect dynamic inversion method

NASA Astrophysics Data System (ADS)

Yi, Bowen; Lin, Shuyi; Yang, Bo; Zhang, Weidong

2018-02-01

This paper presents an output feedback indirect dynamic inversion (IDI) approach for a class of uncertain nonaffine systems with input unmodelled dynamics. Compared with previous approaches to achieve performance recovery, the proposed method aims at dealing with a broader class of nonaffine-in-control systems with triangular structure. An IDI state feedback law is designed first, in which less knowledge of the model plant is needed compared to earlier approximate dynamic inversion methods, thus yielding more robust performance. After that, an extended high-gain observer is designed to accomplish the task with output feedback. Finally, we prove that the designed IDI controller is equivalent to an adaptive proportional-integral (PI) controller, with respect to both time response equivalence and robustness equivalence. The conclusion implies that for the studied strict-feedback non-affine systems with unmodelled dynamics, there always exits a PI controller to stabilise the systems. The effectiveness and benefits of the designed approach are verified by three examples.

Controller design for a class of nonlinear MIMO coupled system using multiple models and second level adaptation.

PubMed

Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha

2017-07-01

In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Development of flank wear model of cutting tool by using adaptive feedback linear control system on machining AISI D2 steel and AISI 4340 steel

NASA Astrophysics Data System (ADS)

Orra, Kashfull; Choudhury, Sounak K.

2016-12-01

The purpose of this paper is to build an adaptive feedback linear control system to check the variation of cutting force signal to improve the tool life. The paper discusses the use of transfer function approach in improving the mathematical modelling and adaptively controlling the process dynamics of the turning operation. The experimental results shows to be in agreement with the simulation model and error obtained is less than 3%. The state space approach model used in this paper successfully check the adequacy of the control system through controllability and observability test matrix and can be transferred from one state to another by appropriate input control in a finite time. The proposed system can be implemented to other machining process under varying range of cutting conditions to improve the efficiency and observability of the system.

Frequency adaptation in controlled stochastic resonance utilizing delayed feedback method: two-pole approximation for response function.

PubMed

Tutu, Hiroki

2011-06-01

Stochastic resonance (SR) enhanced by time-delayed feedback control is studied. The system in the absence of control is described by a Langevin equation for a bistable system, and possesses a usual SR response. The control with the feedback loop, the delay time of which equals to one-half of the period (2π/Ω) of the input signal, gives rise to a noise-induced oscillatory switching cycle between two states in the output time series, while its average frequency is just smaller than Ω in a small noise regime. As the noise intensity D approaches an appropriate level, the noise constructively works to adapt the frequency of the switching cycle to Ω, and this changes the dynamics into a state wherein the phase of the output signal is entrained to that of the input signal from its phase slipped state. The behavior is characterized by power loss of the external signal or response function. This paper deals with the response function based on a dichotomic model. A method of delay-coordinate series expansion, which reduces a non-Markovian transition probability flux to a series of memory fluxes on a discrete delay-coordinate system, is proposed. Its primitive implementation suggests that the method can be a potential tool for a systematic analysis of SR phenomenon with delayed feedback loop. We show that a D-dependent behavior of poles of a finite Laplace transform of the response function qualitatively characterizes the structure of the power loss, and we also show analytical results for the correlation function and the power spectral density.

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.

Inducing Mind Sets in Self-Regulated Learning with Motivational Information

ERIC Educational Resources Information Center

Martens, R.; de Brabander, C.; Rozendaal, J.; Boekaerts, M.; van der Leeden, R.

2010-01-01

The way students perceive a learning climate (e.g. controlling or stimulating) is significantly influenced by feedback and assessment. However, at present much is unclear about the relation between feedback and motivational state. More specifically, the interplay with student characteristics is unclear. Since there is a strong increase of group…

Controls and Participation for Successful Information Systems.

ERIC Educational Resources Information Center

Donald, A. Wayne

1979-01-01

The major information systems at Virginia Polytechnic Institute and State University are described. The use of the feedback and feedforward controls in planning and projecting administrative functions is examined. (Author/BH)

Flatness-based embedded adaptive fuzzy control of turbocharged diesel engines

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Arsie, Ivan

2014-10-01

In this paper nonlinear embedded control for turbocharged Diesel engines is developed with the use of Differential flatness theory and adaptive fuzzy control. It is shown that the dynamic model of the turbocharged Diesel engine is differentially flat and admits dynamic feedback linearization. It is also shown that the dynamic model can be written in the linear Brunovsky canonical form for which a state feedback controller can be easily designed. To compensate for modeling errors and external disturbances an adaptive fuzzy control scheme is implemanted making use of the transformed dynamical system of the diesel engine that is obtained through the application of differential flatness theory. Since only the system's output is measurable the complete state vector has to be reconstructed with the use of a state observer. It is shown that a suitable learning law can be defined for neuro-fuzzy approximators, which are part of the controller, so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed observer-based adaptive fuzzy control scheme results in H∞ tracking performance.

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

Control of nonlinear systems with applications to constrained robots and spacecraft attitude stabilization

NASA Technical Reports Server (NTRS)

Krishnan, Hariharan

1993-01-01

This thesis is organized in two parts. In Part 1, control systems described by a class of nonlinear differential and algebraic equations are introduced. A procedure for local stabilization based on a local state realization is developed. An alternative approach to local stabilization is developed based on a classical linearization of the nonlinear differential-algebraic equations. A theoretical framework is established for solving a tracking problem associated with the differential-algebraic system. First, a simple procedure is developed for the design of a feedback control law which ensures, at least locally, that the tracking error in the closed loop system lies within any given bound if the reference inputs are sufficiently slowly varying. Next, by imposing additional assumptions, a procedure is developed for the design of a feedback control law which ensures that the tracking error in the closed loop system approaches zero exponentially for reference inputs which are not necessarily slowly varying. The control design methodologies are used for simultaneous force and position control in constrained robot systems. The differential-algebraic equations are shown to characterize the slow dynamics of a certain nonlinear control system in nonstandard singularly perturbed form. In Part 2, the attitude stabilization (reorientation) of a rigid spacecraft using only two control torques is considered. First, the case of momentum wheel actuators is considered. The complete spacecraft dynamics are not controllable. However, the spacecraft dynamics are small time locally controllable in a reduced sense. The reduced spacecraft dynamics cannot be asymptotically stabilized using continuous feedback, but a discontinuous feedback control strategy is constructed. Next, the case of gas jet actuators is considered. If the uncontrolled principal axis is not an axis of symmetry, the complete spacecraft dynamics are small time locally controllable. However, the spacecraft attitude cannot be asymptotically stabilized using continuous feedback, but a discontinuous stabilizing feedback control strategy is constructed. If the uncontrolled principal axis is an axis of symmetry, the complete spacecraft dynamics cannot be stabilized. However, the spacecraft dynamics are small time locally controllable in a reduced sense. The reduced spacecraft dynamics cannot be asymptotically stabilized using continuous feedback, but again a discontinuous feedback control strategy is constructed.

Biogeomorphic feedback between plant growth and flooding causes alternative stable states in an experimental floodplain

NASA Astrophysics Data System (ADS)

Wang, Chen; Wang, Qiao; Meire, Dieter; Ma, Wandong; Wu, Chuanqing; Meng, Zhen; Van de Koppel, Johan; Troch, Peter; Verhoeven, Ronny; De Mulder, Tom; Temmerman, Stijn

2016-07-01

It is important to understand the mechanisms of vegetation establishment on bare substrate in a disturbance-driven ecosystem because of many valuable ecosystem services. This study tested for empirical indications of local alternative stable states controlled by biogeomorphic feedbacks using flume experiments with alfalfa: (1) single flood experiments different in flood intensity and plant growth, (2) long-term evolution experiments with repeated flooding and seeding. We observed: (1) a combination of thresholds in plant growth and flooding magnitude for upgrowing seedlings to survive; (2) bimodality in vegetation biomass after floods indicating the existence of two alternative states, either densely vegetated or bare; (3) facilitation of vegetation establishment by the spatial pattern formation of channels and sand bars. In conclusion, empirical indicators were demonstrated for local alternative stable states in a disturbance-driven ecosystem associated with biogeomorphic feedbacks, which could contribute to the protection and restoration of vegetation in such ecosystems.

Approximation methods for control of acoustic/structure models with piezoceramic actuators

NASA Technical Reports Server (NTRS)

Banks, H. T.; Fang, W.; Silcox, R. J.; Smith, R. C.

1991-01-01

The active control of acoustic pressure in a 2-D cavity with a flexible boundary (a beam) is considered. Specifically, this control is implemented via piezoceramic patches on the beam which produces pure bending moments. The incorporation of the feedback control in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input term. Approximation methods in the context of linear quadratic regulator (LQR) state space control formulation are discussed and numerical results demonstrating the effectiveness of this approach in computing feedback controls for noise reduction are presented.

Globally linearized control on diabatic continuous stirred tank reactor: a case study.

PubMed

Jana, Amiya Kumar; Samanta, Amar Nath; Ganguly, Saibal

2005-07-01

This paper focuses on the promise of globally linearized control (GLC) structure in the realm of strongly nonlinear reactor system control. The proposed nonlinear control strategy is comprised of: (i) an input-output linearizing state feedback law (transformer), (ii) a state observer, and (iii) an external linear controller. The synthesis of discrete-time GLC controller for single-input single-output diabatic continuous stirred tank reactor (DCSTR) has been studied first, followed by the synthesis of feedforward/feedback controller for the same reactor having dead time in process as well as in disturbance. Subsequently, the multivariable GLC structure has been designed and then applied on multi-input multi-output DCSTR system. The simulation study shows high quality performance of the derived nonlinear controllers. The better-performed GLC in conjunction with reduced-order observer has been compared with the conventional proportional integral controller on the example reactor and superior performance has been achieved by the proposed GLC control scheme.

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

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1979-01-01

Results are given on the relationships between closed loop eigenstructures, state feedback gain matrices of the linear state feedback problem, and quadratic weights of the linear quadratic regulator. 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 for the first time to compute angles of approach. Equations are also derived to find the sensitivity of closed loop eigenvalues and the directional derivatives of closed loop eigenvectors (with respect to a scalar multiplying the feedback gain matrix or the quadratic control weight). An equivalence class of quadratic weights that produce the same asymptotic eigenstructure is defined, sufficient conditions to be in it are given, 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.

Project Management Using Modern Guidance, Navigation and Control Theory

NASA Technical Reports Server (NTRS)

Hill, Terry

2010-01-01

The idea of control theory and its application to project management is not new, however literature on the topic and real-world applications is not as readily available and comprehensive in how all the principals of Guidance, Navigation and Control (GN&C) apply. This paper will address how the fundamental principals of modern GN&C Theory have been applied to NASA's Constellation Space Suit project and the results in the ability to manage the project within cost, schedule and budget. A s with physical systems, projects can be modeled and managed with the same guiding principles of GN&C as if it were a complex vehicle, system or software with time-varying processes, at times non-linear responses, multiple data inputs of varying accuracy and a range of operating points. With such systems the classic approach could be applied to small and well-defined projects; however with larger, multi-year projects involving multiple organizational structures, external influences and a multitude of diverse resources, then modern control theory is required to model and control the project. The fundamental principals of G N&C stated that a system is comprised of these basic core concepts: State, Behavior, Control system, Navigation system, Guidance and Planning Logic, Feedback systems. The state of a system is a definition of the aspects of the dynamics of the system that can change, such as position, velocity, acceleration, coordinate-based attitude, temperature, etc. The behavior of the system is more of what changes are possible rather than what can change, which is captured in the state of the system. The behavior of a system is captured in the system modeling and if properly done, will aid in accurate system performance prediction in the future. The Control system understands the state and behavior of the system and feedback systems to adjust the control inputs into the system. The Navigation system takes the multiple data inputs and based upon a priori knowledge of the input, will develop a statistical-based weighting of the input to determine where the system currently is located. Guidance and Planning logic of the system with the understanding of where it is (provided by the navigation system) will in turn determine where it needs to be and how to get there. Lastly, the system Feedback system is the right arm of the control system to allow it to affect change in the overall system and therefore it is critical to not only correctly identify the system feedback inputs but also the system response to the feedback inputs. And with any systems project it is critical that the objective of the system be clearly defined for not only planning but to be used to measure performance and to aid in the guidance of the system or project.

Digital controller design: Analysis of the annular suspension pointing system. [analog controllers with feedback

NASA Technical Reports Server (NTRS)

Kuo, B. C.

1978-01-01

The analog controllers of the annular suspension pointing system are designed for control of the chi, phi sub 1, and phi sub 2 bandwidth dynamics through decoupling and pole placement. Since it is virtually impossible to find an equivalent bandwidth of the overall system and establish a general eigenvalue requirement for the system, the subsystem dynamics are decoupled through state feedback and the poles are placed simultaneously to realize the desired bandwidths for the three system components. Decoupling and pole placement are also used to design the closed-loop digital system through approximation.

An integrated optical sensor for GMAW feedback control

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

Taylor, P.L.; Watkins, A.D.; Larsen, E.D.

1992-08-01

The integrated optical sensor (IOS) is a multifunction feedback control sensor for arc welding, that is computer automated and independent of significant operator interaction. It is based on three major ``off-the-shelf`` components: a charged coupled device (CCD) camera, a diode laser, and a processing computer. The sensor head is compact and lightweight to avoid interference with weld head mobility, hardened to survive the harsh operating environment, and free of specialized cooling and power requirements. The sensor is positioned behind the GMAW torch and measures weld pool position and width, standoff distance, and postweld centerline cooling rate. Weld pool position andmore » width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint, thus allowing compensation for such phenomena as arc blow. Sensor stand off distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to infer the final metallurgical state of the weld bead and heat affected zone, thereby providing a means of controlling post weld mechanical properties.« less

An integrated optical sensor for GMAW feedback control

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

Taylor, P.L.; Watkins, A.D.; Larsen, E.D.

1992-01-01

The integrated optical sensor (IOS) is a multifunction feedback control sensor for arc welding, that is computer automated and independent of significant operator interaction. It is based on three major off-the-shelf'' components: a charged coupled device (CCD) camera, a diode laser, and a processing computer. The sensor head is compact and lightweight to avoid interference with weld head mobility, hardened to survive the harsh operating environment, and free of specialized cooling and power requirements. The sensor is positioned behind the GMAW torch and measures weld pool position and width, standoff distance, and postweld centerline cooling rate. Weld pool position andmore » width are used in a feedback loop, by the weld controller, to track the weld pool relative to the weld joint, thus allowing compensation for such phenomena as arc blow. Sensor stand off distance is used in a feedback loop to control the contact tip to base metal distance during the welding process. Cooling rate information is used to infer the final metallurgical state of the weld bead and heat affected zone, thereby providing a means of controlling post weld mechanical properties.« less

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

State deadbeat response and observability in multi-modal systems

NASA Technical Reports Server (NTRS)

Conner, L. T., Jr.; Stanford, D. P.

1984-01-01

Two aspects of multimodal systems are examined. It is shown that any completely controllable system with state dimension n not exceeding three allows a choice of feedback matrices resulting in a state deadbeat response. Some of the results presented here are valid for arbitrary n, and it is suggested that for all n the state deadbeat response can be obtained under the hypothesis of complete controllability. The controllability canonical form for a multimodal system is refined by introducing a notion of observability which is dual to controllability for these systems.

The neural representation of typical and atypical experiences of negative images: comparing fear, disgust and morbid fascination

PubMed Central

Lindquist, Kristen A.; Adebayo, Morenikeji; Barrett, Lisa Feldman

2016-01-01

Negative stimuli do not only evoke fear or disgust, but can also evoke a state of ‘morbid fascination’ which is an urge to approach and explore a negative stimulus. In the present neuroimaging study, we applied an innovative method to investigate the neural systems involved in typical and atypical conceptualizations of negative images. Participants received false feedback labeling their mental experience as fear, disgust or morbid fascination. This manipulation was successful; participants judged the false feedback correct for 70% of the trials on average. The neuroimaging results demonstrated differential activity within regions in the ‘neural reference space for discrete emotion’ depending on the type of feedback. We found robust differences in the ventrolateral prefrontal cortex, the dorsomedial prefrontal cortex and the lateral orbitofrontal cortex comparing morbid fascination to control feedback. More subtle differences in the dorsomedial prefrontal cortex and the lateral orbitofrontal cortex were also found between morbid fascination feedback and the other emotion feedback conditions. This study is the first to forward evidence about the neural representation of the experimentally unexplored state of morbid fascination. In line with a constructionist framework, our findings suggest that neural resources associated with the process of conceptualization contribute to the neural representation of this state. PMID:26180088

Adaptive Fuzzy Tracking Control for a Class of MIMO Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Lin, Chong; Liu, Xiaoping; Liu, Kefu

2015-12-01

This paper focuses on the problem of fuzzy adaptive control for a class of multiinput and multioutput (MIMO) nonlinear systems in nonstrict-feedback form, which contains the strict-feedback form as a special case. By the condition of variable partition, a new fuzzy adaptive backstepping is proposed for such a class of nonlinear MIMO systems. The suggested fuzzy adaptive controller guarantees that the proposed control scheme can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking errors eventually converge to a small neighborhood around the origin. The main advantage of this paper is that a control approach is systematically derived for nonlinear systems with strong interconnected terms which are the functions of all states of the whole system. Simulation results further illustrate the effectiveness of the suggested approach.

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.

Active control of convection

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

Bau, H.H.

Using stability theory, numerical simulations, and in some instances experiments, it is demonstrated that the critical Rayleigh number for the bifurcation (1) from the no-motion (conduction) state to the motion state and (2) from time-independent convection to time-dependent, oscillatory convection in the thermal convection loop and Rayleigh-Benard problems can be significantly increased or decreased. This is accomplished through the use of a feedback controller effectuating small perturbations in the boundary data. The controller consists of sensors which detect deviations in the fluid`s temperature from the motionless, conductive values and then direct actuators to respond to these deviations in such amore » way as to suppress the naturally occurring flow instabilities. Actuators which modify the boundary`s temperature/heat flux are considered. The feedback controller can also be used to control flow patterns and generate complex dynamic behavior at relatively low Rayleigh numbers.« less

Active chatter suppression with displacement-only measurement in turning process

NASA Astrophysics Data System (ADS)

Ma, Haifeng; Wu, Jianhua; Yang, Liuqing; Xiong, Zhenhua

2017-08-01

Regenerative chatter is a major hindrance for achieving high quality and high production rate in machining processes. Various active controllers have been proposed to mitigate chatter. However, most of existing controllers were developed on the basis of multi-states feedback of the system and state observers were usually needed. Moreover, model parameters of the machining process (mass, damping and stiffness) were required in existing active controllers. In this study, an active sliding mode controller, which employs a dynamic output feedback sliding surface for the unmatched condition and an adaptive law for disturbance estimation, is designed, analyzed, and validated for chatter suppression in turning process. Only displacement measurement is required by this approach. Other sensors and state observers are not needed. Moreover, it facilitates a rapid implementation since the designed controller is established without using model parameters of the turning process. Theoretical analysis, numerical simulations and experiments on a computer numerical control (CNC) lathe are presented. It shows that the chatter can be substantially attenuated and the chatter-free region can be significantly expanded with the presented method.

Deadbeat Predictive Controllers

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh

1997-01-01

Several new computational algorithms are presented to compute the deadbeat predictive control law. The first algorithm makes use of a multi-step-ahead output prediction to compute the control law without explicitly calculating the controllability matrix. The system identification must be performed first and then the predictive control law is designed. The second algorithm uses the input and output data directly to compute the feedback law. It combines the system identification and the predictive control law into one formulation. The third algorithm uses an observable-canonical form realization to design the predictive controller. The relationship between all three algorithms is established through the use of the state-space representation. All algorithms are applicable to multi-input, multi-output systems with disturbance inputs. In addition to the feedback terms, feed forward terms may also be added for disturbance inputs if they are measurable. Although the feedforward terms do not influence the stability of the closed-loop feedback law, they enhance the performance of the controlled system.

Feedback control laws for highly maneuverable aircraft

NASA Technical Reports Server (NTRS)

Garrard, William L.; Balas, Gary J.

1992-01-01

The results of a study of the application of H infinity and mu synthesis techniques to the design of feedback control laws for the longitudinal dynamics of the High Angle of Attack Research Vehicle (HARV) are presented. The objective of this study is to develop methods for the design of feedback control laws which cause the closed loop longitudinal dynamics of the HARV to meet handling quality specifications over the entire flight envelope. Control law designs are based on models of the HARV linearized at various flight conditions. The control laws are evaluated by both linear and nonlinear simulations of typical maneuvers. The fixed gain control laws resulting from both the H infinity and mu synthesis techniques result in excellent performance even when the aircraft performs maneuvers in which the system states vary significantly from their equilibrium design values. Both the H infinity and mu synthesis control laws result in performance which compares favorably with an existing baseline longitudinal control law.

Closed loop kinesthetic feedback for postural control rehabilitation.

PubMed

Vérité, Fabien; Bachta, Wael; Morel, Guillaume

2014-01-01

Postural control rehabilitation may benefit from the use of smart devices providing biofeedback. This approach consists of increasing the patients perception of their postural state. Namely, postural state is monitored and fed back in real time to the patients through one or more sensory channels. This allows implementing rehabilitation exercises where the patients control their posture with the help of additional sensory inputs. In this paper, a closed loop control of the Center-Of-Pressure (CoP) based on kinesthetic feedback is proposed as a new form of biofeedback. The motion of a one Degree of Freedom (DoF) translational device, lightly touched by the patient's forefinger, is servoed to the patient's CoP position extracted from the measurements of a force plate on which he/she stands. As a result, the patient's CoP can be controllably displaced. A first set of experiments is used to prove the feasibility of this closed-loop control under ideal conditions favoring the perception of the kinesthetic feedback, while the subject is totally unaware of the context. A second set of experiments is then proposed to evaluate the robustness of this approach under experimental conditions that are more realistic with regards to the clinical context of a rehabilitation program involving biofeedback-based exercises.

Feedback enhances feedforward figure-ground segmentation by changing firing mode.

PubMed

Supèr, Hans; Romeo, August

2011-01-01

In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.

Design Of Feedforward Controllers For Multivariable Plants

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

Controllers based on simple low-order transfer functions. Mathematical criteria derived for design of feedforward controllers for class of multiple-input/multiple-output linear plants. Represented by simple low-order transfer functions, obtained without reconstruction of states of commands and disturbances. Enables plant to track command while remaining unresponsive to disturbance in steady state. Feedback controller added independently to stabilize plant or to make control system less susceptible to variations in parameters of plant.

A nonlinear controller design for permanent magnet motors using a synchronization-based technique inspired from the Lorenz system.

PubMed

Zaher, Ashraf A

2008-03-01

The dynamic behavior of a permanent magnet synchronous machine (PMSM) is analyzed. Nominal and special operating conditions are explored to show that the PMSM can experience chaos. A nonlinear controller is introduced to control these unwanted chaotic oscillations and to bring the PMSM to a stable steady state. The designed controller uses a pole-placement approach to force the closed-loop system to follow the performance of a simple first-order linear system with zero steady-state error to a desired set point. The similarity between the mathematical model of the PMSM and the famous chaotic Lorenz system is utilized to design a synchronization-based state observer using only the angular speed for feedback. Simulation results verify the effectiveness of the proposed controller in eliminating the chaotic oscillations while using a single feedback signal. The superiority of the proposed controller is further demonstrated by comparing it with a conventional PID controller. Finally, a laboratory-based experiment was conducted using the MCK2812 C Pro-MS(BL) motion control kit to confirm the theoretical results and to verify both the causality and versatility of the proposed controller.

Robust Feedback Control of Flow Induced Structural Radiation of Sound

NASA Technical Reports Server (NTRS)

Heatwole, Craig M.; Bernhard, Robert J.; Franchek, Matthew A.

1997-01-01

A significant component of the interior noise of aircraft and automobiles is a result of turbulent boundary layer excitation of the vehicular structure. In this work, active robust feedback control of the noise due to this non-predictable excitation is investigated. Both an analytical model and experimental investigations are used to determine the characteristics of the flow induced structural sound radiation problem. The problem is shown to be broadband in nature with large system uncertainties associated with the various operating conditions. Furthermore the delay associated with sound propagation is shown to restrict the use of microphone feedback. The state of the art control methodologies, IL synthesis and adaptive feedback control, are evaluated and shown to have limited success for solving this problem. A robust frequency domain controller design methodology is developed for the problem of sound radiated from turbulent flow driven plates. The control design methodology uses frequency domain sequential loop shaping techniques. System uncertainty, sound pressure level reduction performance, and actuator constraints are included in the design process. Using this design method, phase lag was added using non-minimum phase zeros such that the beneficial plant dynamics could be used. This general control approach has application to lightly damped vibration and sound radiation problems where there are high bandwidth control objectives requiring a low controller DC gain and controller order.

Cardiac and electro-cortical concomitants of social feedback processing in women

PubMed Central

van der Molen, Melle J. W.; Gunther Moor, Bregtje; van der Veen, Frederik M.; van der Molen, Maurits W.

2015-01-01

This study provides a joint analysis of the cardiac and electro-cortical—early and late P3 and feedback-related negativity (FRN)—responses to social acceptance and rejection feedback. Twenty-five female participants performed on a social- and age-judgment control task, in which they received feedback with respect to their liking and age judgments, respectively. Consistent with previous reports, results revealed transient cardiac slowing to be selectively prolonged to unexpected social rejection feedback. Late P3 amplitude was more pronounced to unexpected relative to expected feedback. Both early and late P3 amplitudes were shown to be context dependent, in that they were more pronounced to social as compared with non-social feedback. FRN amplitudes were more pronounced to unexpected relative to expected feedback, irrespective of context and feedback valence. This pattern of findings indicates that social acceptance and rejection feedback have widespread effects on bodily state and brain function, which are modulated by prior expectancies. PMID:25870439

Periodic-disturbance accommodating control of the space station for asymptotic momentum management

NASA Technical Reports Server (NTRS)

Warren, Wayne; Wie, Bong

1989-01-01

Periodic maneuvering control is developed for asymptotic momentum management of control gyros used as primary actuating devices for the Space Station. The proposed controller utilizes the concepts of quaternion feedback control and periodic-disturbance accommodation to achieve oscillations about the constant torque equilibrium attitude, while minimizing the control effort required. Three-axis coupled equations of motion, written in terms of quaternions, are derived for roll/yaw controller design and stability analysis. It is shown that the quaternion feedback controller is very robust for a wide range of pitch angles. It is also shown that the proposed controller tunes the open-loop unstable vehicle to a stable oscillatory motion which minimizes the control effort needed for steady-state operations.

New numerical methods for open-loop and feedback solutions to dynamic optimization problems

NASA Astrophysics Data System (ADS)

Ghosh, Pradipto

The topic of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each particle in the swarm uses its own memory as well as the knowledge accumulated by the entire swarm to iteratively converge on an optimal or near-optimal solution. It is relatively straightforward to implement and unlike gradient-based solvers, does not require an initial guess or continuity in the problem definition. Although particle swarm optimization has been successfully employed in solving static optimization problems, its application in dynamic optimization, as posed in optimal control theory, is still relatively new. In the first half of this thesis particle swarm optimization is used to generate near-optimal solutions to several nontrivial trajectory optimization problems including thrust programming for minimum fuel, multi-burn spacecraft orbit transfer, and computing minimum-time rest-to-rest trajectories for a robotic manipulator. A distinct feature of the particle swarm optimization implementation in this work is the runtime selection of the optimal solution structure. Optimal trajectories are generated by solving instances of constrained nonlinear mixed-integer programming problems with the swarming technique. For each solved optimal programming problem, the particle swarm optimization result is compared with a nearly exact solution found via a direct method using nonlinear programming. Numerical experiments indicate that swarm search can locate solutions to very great accuracy. The second half of this research develops a new extremal-field approach for synthesizing nearly optimal feedback controllers for optimal control and two-player pursuit-evasion games described by general nonlinear differential equations. A notable revelation from this development is that the resulting control law has an algebraic closed-form structure. The proposed method uses an optimal spatial statistical predictor called universal kriging to construct the surrogate model of a feedback controller, which is capable of quickly predicting an optimal control estimate based on current state (and time) information. With universal kriging, an approximation to the optimal feedback map is computed by conceptualizing a set of state-control samples from pre-computed extremals to be a particular realization of a jointly Gaussian spatial process. Feedback policies are computed for a variety of example dynamic optimization problems in order to evaluate the effectiveness of this methodology. This feedback synthesis approach is found to combine good numerical accuracy with low computational overhead, making it a suitable candidate for real-time applications. Particle swarm and universal kriging are combined for a capstone example, a near optimal, near-admissible, full-state feedback control law is computed and tested for the heat-load-limited atmospheric-turn guidance of an aeroassisted transfer vehicle. The performance of this explicit guidance scheme is found to be very promising; initial errors in atmospheric entry due to simulated thruster misfirings are found to be accurately corrected while closely respecting the algebraic state-inequality constraint.

Design of robust adaptive controller and feedback error learning for rehabilitation in Parkinson's disease: a simulation study.

PubMed

Rouhollahi, Korosh; Emadi Andani, Mehran; Karbassi, Seyed Mahdi; Izadi, Iman

2017-02-01

Deep brain stimulation (DBS) is an efficient therapy to control movement disorders of Parkinson's tremor. Stimulation of one area of basal ganglia (BG) by DBS with no feedback is the prevalent opinion. Reduction of additional stimulatory signal delivered to the brain is the advantage of using feedback. This results in reduction of side effects caused by the excessive stimulation intensity. In fact, the stimulatory intensity of controllers is decreased proportional to reduction of hand tremor. The objective of this study is to design a new controller structure to decrease three indicators: (i) the hand tremor; (ii) the level of delivered stimulation in disease condition; and (iii) the ratio of the level of delivered stimulation in health condition to disease condition. For this purpose, the authors offer a new closed-loop control structure to stimulate two areas of BG simultaneously. One area (STN: subthalamic nucleus) is stimulated by an adaptive controller with feedback error learning. The other area (GPi: globus pallidus internal) is stimulated by a partial state feedback (PSF) controller. Considering the three indicators, the results show that, stimulating two areas simultaneously leads to better performance compared with stimulating one area only. It is shown that both PSF and adaptive controllers are robust regarding system parameter uncertainties. In addition, a method is proposed to update the parameters of the BG model in real time. As a result, the parameters of the controllers can be updated based on the new parameters of the BG model.

Stabilising falling liquid film flows using feedback control

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

Thompson, Alice B., E-mail: alice.thompson1@imperial.ac.uk; Gomes, Susana N.; Pavliotis, Grigorios A.

2016-01-15

Falling liquid films become unstable due to inertial effects when the fluid layer is sufficiently thick or the slope sufficiently steep. This free surface flow of a single fluid layer has industrial applications including coating and heat transfer, which benefit from smooth and wavy interfaces, respectively. Here, we discuss how the dynamics of the system are altered by feedback controls based on observations of the interface height, and supplied to the system via the perpendicular injection and suction of fluid through the wall. In this study, we model the system using both Benney and weighted-residual models that account for themore » fluid injection through the wall. We find that feedback using injection and suction is a remarkably effective control mechanism: the controls can be used to drive the system towards arbitrary steady states and travelling waves, and the qualitative effects are independent of the details of the flow modelling. Furthermore, we show that the system can still be successfully controlled when the feedback is applied via a set of localised actuators and only a small number of system observations are available, and that this is possible using both static (where the controls are based on only the most recent set of observations) and dynamic (where the controls are based on an approximation of the system which evolves over time) control schemes. This study thus provides a solid theoretical foundation for future experimental realisations of the active feedback control of falling liquid films.« less

Smart environment architecture for emotion detection and regulation.

PubMed

Fernández-Caballero, Antonio; Martínez-Rodrigo, Arturo; Pastor, José Manuel; Castillo, José Carlos; Lozano-Monasor, Elena; López, María T; Zangróniz, Roberto; Latorre, José Miguel; Fernández-Sotos, Alicia

2016-12-01

This paper introduces an architecture as a proof-of-concept for emotion detection and regulation in smart health environments. The aim of the proposal is to detect the patient's emotional state by analysing his/her physiological signals, facial expression and behaviour. Then, the system provides the best-tailored actions in the environment to regulate these emotions towards a positive mood when possible. The current state-of-the-art in emotion regulation through music and colour/light is implemented with the final goal of enhancing the quality of life and care of the subject. The paper describes the three main parts of the architecture, namely "Emotion Detection", "Emotion Regulation" and "Emotion Feedback Control". "Emotion Detection" works with the data captured from the patient, whereas "Emotion Regulation" offers him/her different musical pieces and colour/light settings. "Emotion Feedback Control" performs as a feedback control loop to assess the effect of emotion regulation over emotion detection. We are currently testing the overall architecture and the intervention in real environments to achieve our final goal. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

General, database-driven fast-feedback system for the Stanford Linear Collider

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

Rouse, F.; Allison, S.; Castillo, S.

A new feedback system has been developed for stabilizing the SLC beams at many locations. The feedback loops are designed to sample and correct at the 60 Hz repetition rate of the accelerator. Each loop can be distributed across several of the standard 80386 microprocessors which control the SLC hardware. A new communications system, KISNet, has been implemented to pass signals between the microprocessors at this rate. The software is written in a general fashion using the state space formalism of digital control theory. This allows a new loop to be implemented by just setting up the online database andmore » perhaps installing a communications link. 3 refs., 4 figs.« less

Application of Physiological Self-Regulation and Adaptive Task Allocation Techniques for Controlling Operator Hazardous States of Awareness

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Pope, Alan T.; Freeman, Frederick G.

2001-01-01

Prinzel, Hadley, Freeman, and Mikulka found that adaptive task allocation significantly enhanced performance only when used at the endpoints of the task workload continuum (i.e., very low or high workload), but that the technique degraded performance if invoked during other levels of task demand. These researchers suggested that other techniques should be used in conjunction with adaptive automation to help minimize the onset of hazardous states of awareness (HSA) and keep the operator 'in-the-loop.' The paper reports on such a technique that uses psychophysiological self-regulation to modulate the level of task engagement. Eighteen participants were assigned to three groups (self-regulation, false feedback, and control) and performed a compensatory tracking task that was cycled between three levels of task difficulty on the basis of the electroencephalogram (EEG) record. Those participants who had received self-regulation training performed significantly better and reported lower NASA-TLX scores than participants in the false feedback and control groups. Furthermore, the false feedback and control groups had significantly more task allocations resulting in return-to-manual performance decrements and higher EEG difference scores. Theoretical and practical implications of these results for adaptive automation are discussed.

GASICA: generic automated stress induction and control application design of an application for controlling the stress state.

PubMed

van der Vijgh, Benny; Beun, Robbert J; van Rood, Maarten; Werkhoven, Peter

2014-01-01

In a multitude of research and therapy paradigms it is relevant to know, and desirably to control, the stress state of a patient or participant. Examples include research paradigms in which the stress state is the dependent or independent variable, or therapy paradigms where this state indicates the boundaries of the therapy. To our knowledge, no application currently exists that focuses specifically on the automated control of the stress state while at the same time being generic enough to be used in various therapy and research purposes. Therefore, we introduce GASICA, an application aimed at the automated control of the stress state in a multitude of therapy and research paradigms. The application consists of three components: a digital stressor game, a set of measurement devices, and a feedback model. These three components form a closed loop (called a biocybernetic loop by Pope et al. (1995) and Fairclough (2009) that continuously presents an acute psychological stressor, measures several physiological responses to this stressor, and adjusts the stressor intensity based on these measurements by means of the feedback model, hereby aiming to control the stress state. In this manner GASICA presents multidimensional and ecological valid stressors, whilst continuously in control of the form and intensity of the presented stressors, aiming at the automated control of the stress state. Furthermore, the application is designed as a modular open-source application to easily implement different therapy and research tasks using a high-level programming interface and configuration file, and allows for the addition of (existing) measurement equipment, making it usable for various paradigms.

GASICA: generic automated stress induction and control application design of an application for controlling the stress state

PubMed Central

van der Vijgh, Benny; Beun, Robbert J.; van Rood, Maarten; Werkhoven, Peter

2014-01-01

In a multitude of research and therapy paradigms it is relevant to know, and desirably to control, the stress state of a patient or participant. Examples include research paradigms in which the stress state is the dependent or independent variable, or therapy paradigms where this state indicates the boundaries of the therapy. To our knowledge, no application currently exists that focuses specifically on the automated control of the stress state while at the same time being generic enough to be used in various therapy and research purposes. Therefore, we introduce GASICA, an application aimed at the automated control of the stress state in a multitude of therapy and research paradigms. The application consists of three components: a digital stressor game, a set of measurement devices, and a feedback model. These three components form a closed loop (called a biocybernetic loop by Pope et al. (1995) and Fairclough (2009) that continuously presents an acute psychological stressor, measures several physiological responses to this stressor, and adjusts the stressor intensity based on these measurements by means of the feedback model, hereby aiming to control the stress state. In this manner GASICA presents multidimensional and ecological valid stressors, whilst continuously in control of the form and intensity of the presented stressors, aiming at the automated control of the stress state. Furthermore, the application is designed as a modular open-source application to easily implement different therapy and research tasks using a high-level programming interface and configuration file, and allows for the addition of (existing) measurement equipment, making it usable for various paradigms. PMID:25538554

Foot placement relies on state estimation during visually guided walking.

PubMed

Maeda, Rodrigo S; O'Connor, Shawn M; Donelan, J Maxwell; Marigold, Daniel S

2017-02-01

As we walk, we must accurately place our feet to stabilize our motion and to navigate our environment. We must also achieve this accuracy despite imperfect sensory feedback and unexpected disturbances. In this study we tested whether the nervous system uses state estimation to beneficially combine sensory feedback with forward model predictions to compensate for these challenges. Specifically, subjects wore prism lenses during a visually guided walking task, and we used trial-by-trial variation in prism lenses to add uncertainty to visual feedback and induce a reweighting of this input. To expose altered weighting, we added a consistent prism shift that required subjects to adapt their estimate of the visuomotor mapping relationship between a perceived target location and the motor command necessary to step to that position. With added prism noise, subjects responded to the consistent prism shift with smaller initial foot placement error but took longer to adapt, compatible with our mathematical model of the walking task that leverages state estimation to compensate for noise. Much like when we perform voluntary and discrete movements with our arms, it appears our nervous systems uses state estimation during walking to accurately reach our foot to the ground. Accurate foot placement is essential for safe walking. We used computational models and human walking experiments to test how our nervous system achieves this accuracy. We find that our control of foot placement beneficially combines sensory feedback with internal forward model predictions to accurately estimate the body's state. Our results match recent computational neuroscience findings for reaching movements, suggesting that state estimation is a general mechanism of human motor control. Copyright © 2017 the American Physiological Society.

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

Control logic to track the outputs of a command generator or randomly forced target

NASA Technical Reports Server (NTRS)

Trankle, T. L.; Bryson, A. E., Jr.

1977-01-01

A procedure is presented for synthesizing time-invariant control logic to cause the outputs of a linear plant to track the outputs of an unforced (or randomly forced) linear dynamic system. The control logic uses feed-forward of the reference system state variables and feedback of the plant state variables. The feed-forward gains are obtained from the solution of a linear algebraic matrix equation of the Liapunov type. The feedback gains are the usual regulator gains, determined to stabilize (or augment the stability of) the plant, possibly including integral control. The method is applied here to the design of control logic for a second-order servomechanism to follow a linearly increasing (ramp) signal, an unstable third-order system with two controls to track two separate ramp signals, and a sixth-order system with two controls to track a constant signal and an exponentially decreasing signal (aircraft landing-flare or glide-slope-capture with constant velocity).

Modelling and control of a rotor supported by magnetic bearings

NASA Technical Reports Server (NTRS)

Gurumoorthy, R.; Pradeep, A. K.

1994-01-01

In this paper we develop a dynamical model of a rotor and the active magnetic bearings used to support the rotor. We use this model to develop a stable state feedback control of the magnetic bearing system. We present the development of a rigid body model of the rotor, utilizing both Rotation Matrices (Euler Angles) and Euler Parameters (Quaternions). In the latter half of the paper we develop a stable state feedback control of the actively controlled magnetic bearing to control the rotor position under inbalances. The control law developed takes into account the variation of the model with rotational speed. We show stability over the whole operating range of speeds for the magnetic bearing system. Simulation results are presented to demonstrate the closed loop system performance. We develop the model of the magnetic bearing, and present two schemes for the excitation of the poles of the actively controlled magnetic bearing. We also present a scheme for averaging multiple sensor measurements and splitting the actuation forces amongst redundant actuators.

Approximation methods for control of structural acoustics models with piezoceramic actuators

NASA Astrophysics Data System (ADS)

Banks, H. T.; Fang, W.; Silcox, R. J.; Smith, R. C.

1993-01-01

The active control of acoustic pressure in a 2-D cavity with a flexible boundary (a beam) is considered. Specifically, this control is implemented via piezoceramic patches on the beam which produces pure bending moments. The incorporation of the feedback control in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input term. Approximation methods in this manner leads to a system with an unbounded input team. Approximation methods in the context of linear quadratic regulator (LQR) state space control formulation are discussed and numerical results demonstrating the effectiveness of this approach in computing feedback controls for noise reduction are presented.

Modeling, Control and Simulation of Three-Dimensional Robotic Systems with Applications to Biped Locomotion.

NASA Astrophysics Data System (ADS)

Zheng, Yuan-Fang

A three-dimensional, five link biped system is established. Newton-Euler state space formulation is employed to derive the equations of the system. The constraint forces involved in the equations can be eliminated by projection onto a smaller state space system for deriving advanced control laws. A model-referenced adaptive control scheme is developed to control the system. Digital computer simulations of point to point movement are carried out to show that the model-referenced adaptive control increases the dynamic range and speeds up the response of the system in comparison with linear and nonlinear feedback control. Further, the implementation of the controller is simpler. Impact effects of biped contact with the environment are modeled and studied. The instant velocity change at the moment of impact is derived as a function of the biped state and contact speed. The effects of impact on the state, as well as constraints are studied in biped landing on heels and toes simultaneously or on toes first. Rate and nonlinear position feedback are employed for stability of the biped after the impact. The complex structure of the foot is properly modeled. A spring and dashpot pair is suggested to represent the action of plantar fascia during the impact. This action prevents the arch of the foot from collapsing. A mathematical model of the skeletal muscle is discussed. A direct relationship between the stimulus rate and the active state is established. A piecewise linear relation between the length of the contractile element and the isometric force is considered. Hill's characteristic equation is maintained for determining the actual output force during different shortening velocities. A physical threshold model is proposed for recruitment which encompasses the size principle, its manifestations and exceptions to the size principle. Finally the role of spindle feedback in stability of the model is demonstrated by study of a pair of muscles.

State observers and Kalman filtering for high performance vibration isolation systems.

PubMed

Beker, M G; Bertolini, A; van den Brand, J F J; Bulten, H J; Hennes, E; Rabeling, D S

2014-03-01

There is a strong scientific case for the study of gravitational waves at or below the lower end of current detection bands. To take advantage of this scientific benefit, future generations of ground based gravitational wave detectors will need to expand the limit of their detection bands towards lower frequencies. Seismic motion presents a major challenge at these frequencies and vibration isolation systems will play a crucial role in achieving the desired low-frequency sensitivity. A compact vibration isolation system designed to isolate in-vacuum optical benches for Advanced Virgo will be introduced and measurements on this system are used to present its performance. All high performance isolation systems employ an active feedback control system to reduce the residual motion of their suspended payloads. The development of novel control schemes is needed to improve the performance beyond what is currently feasible. Here, we present a multi-channel feedback approach that is novel to the field. It utilizes a linear quadratic regulator in combination with a Kalman state observer and is shown to provide effective suppression of residual motion of the suspended payload. The application of state observer based feedback control for vibration isolation will be demonstrated with measurement results from the Advanced Virgo optical bench suspension system.

Children's feedback preferences in response to an experimentally manipulated peer evaluation outcome: the role of depressive symptoms.

PubMed

Reijntjes, Albert; Dekovic, Maja; Vermande, Marjolijn; Telch, Michael J

2007-06-01

The present study examined the linkage between pre-adolescent children's depressive symptoms and their preferences for receiving positive vs. negative feedback subsequent to being faced with an experimentally manipulated peer evaluation outcome in real time. Participants (n = 142) ages 10 to 13, played a computer contest based on the television show Survivor and were randomized to either a peer rejection (i.e., receiving the lowest total 'likeability' score from a group of peer-judges), a peer success (i.e., receiving the highest score), or a control peer evaluation condition. Children's self-reported feedback preferences were then assessed. Results revealed that participants assigned to the negative evaluation outcome, relative to either the success or the control outcome, showed a significantly higher subsequent preference for negatively tuned feedback. Contrary to previous work and predictions derived from self-verification theory, children higher in depressive symptoms were only more likely to prefer negative feedback in response to the negative peer evaluation outcome. These effects for depression were not accounted for by either state mood at baseline or mood change in response to the feedback manipulation.

Effect of density feedback on the two-route traffic scenario with bottleneck

NASA Astrophysics Data System (ADS)

Sun, Xiao-Yan; Ding, Zhong-Jun; Huang, Guo-Hua

2016-12-01

In this paper, we investigate the effect of density feedback on the two-route scenario with a bottleneck. The simulation and theory analysis shows that there exist two critical vehicle entry probabilities αc1 and αc2. When vehicle entry probability α≤αc1, four different states, i.e. free flow state, transition state, maximum current state and congestion state are identified in the system, which correspond to three critical reference densities. However, in the interval αc1<α<αc2, the free flow and transition state disappear, and there is only congestion state when α≥αc2. According to the results, traffic control center can adjust the reference density so that the system is in maximum current state. In this case, the capacity of the traffic system reaches maximum so that drivers can make full use of the roads. We hope that the study results can provide good advice for alleviating traffic jam and be useful to traffic control center for designing advanced traveller information systems.

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.

Energy management and attitude control for spacecraft

NASA Astrophysics Data System (ADS)

Costic, Bret Thomas

2001-07-01

This PhD dissertation describes the design and implementation of various control strategies centered around spacecraft applications: (i) an attitude control system for spacecraft, (ii) flywheels used for combined attitude and energy tracking, and (iii) an adaptive autobalancing control algorithm. The theory found in each of these sections is demonstrated through simulation or experimental results. An introduction to each of these three primary chapters can be found in chapter one. The main problem addressed in the second chapter is the quaternion-based, attitude tracking control of rigid spacecraft without angular velocity measurements and in the presence of an unknown inertia matrix. As a stepping-stone, an adaptive, full-state feedback controller that compensates for parametric uncertainty while ensuring asymptotic attitude tracking errors is designed. The adaptive, full-state feedback controller is then redesigned such that the need for angular velocity measurements is eliminated. The proposed adaptive, output feedback controller ensures asymptotic attitude tracking. This work uses a four-parameter representation of the spacecraft attitude that does not exhibit singular orientations as in the case of the previous three-parameter representation-based results. To the best of my knowledge, this represents the first solution to the adaptive, output feedback, attitude tracking control problem for the quaternion representation. Simulation results are included to illustrate the performance of the proposed output feedback control strategy. The third chapter is devoted to the use of multiple flywheels that integrate the energy storage and attitude control functions in space vehicles. This concept, which is referred to as an Integrated Energy Management and Attitude Control (IEMAC) system, reduces the space vehicle bus mass, volume, cost, and maintenance requirements while maintaining or improving the space vehicle performance. To this end, two nonlinear IEMAC strategies (model-based and adaptive) that simultaneously track a desired attitude trajectory and desired energy/power profile are presented. Both strategies ensure asymptotic tracking while the adaptive controller compensates for uncertain spacecraft inertia. In the final chapter, a control strategy is designed for a rotating, unbalanced disk. The control strategy, which is composed of a control torque and two control forces, regulates the disk displacement and ensures angular velocity tracking. The controller uses a desired compensation adaptation law and a gain adjusted forgetting factor to achieve exponential stability despite the lack of knowledge of the imbalance-related parameters, provided a mild persistency of excitation condition is satisfied.

Plasma Equilibrium Control in Nuclear Fusion Devices 2. Plasma Control in Magnetic Confinement Devices 2.1 Plasma Control in Tokamaks

NASA Astrophysics Data System (ADS)

Fukuda, Takeshi

The plasma control technique for use in large tokamak devices has made great developmental strides in the last decade, concomitantly with progress in the understanding of tokamak physics and in part facilitated by the substantial advancement in the computing environment. Equilibrium control procedures have thereby been established, and it has been pervasively recognized in recent years that the real-time feedback control of physical quantities is indispensable for the improvement and sustainment of plasma performance in a quasi-steady-state. Further development is presently undertaken to realize the “advanced plasma control” concept, where integrated fusion performance is achieved by the simultaneous feedback control of multiple physical quantities, combined with equilibrium control.

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.

Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations.

PubMed

Sarhadi, Pouria; Noei, Abolfazl Ranjbar; Khosravi, Alireza

2016-11-01

Input saturations and uncertain dynamics are among the practical challenges in control of autonomous vehicles. Adaptive control is known as a proper method to deal with the uncertain dynamics of these systems. Therefore, incorporating the ability to confront with input saturation in adaptive controllers can be valuable. In this paper, an adaptive autopilot is presented for the pitch and yaw channels of an autonomous underwater vehicle (AUV) in the presence of input saturations. This will be performed by combination of a model reference adaptive control (MRAC) with integral state feedback with a modern anti-windup (AW) compensator. MRAC with integral state feedback is commonly used in autonomous vehicles. However, some proper modifications need to be taken into account in order to cope with the saturation problem. To this end, a Riccati-based anti-windup (AW) compensator is employed. The presented technique is applied to the non-linear six degrees of freedom (DOF) model of an AUV and the obtained results are compared with that of its baseline method. Several simulation scenarios are executed in the pitch and yaw channels to evaluate the controller performance. Moreover, effectiveness of proposed adaptive controller is comprehensively investigated by implementing Monte Carlo simulations. The obtained results verify the performance of proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Observer-Based Adaptive Fault-Tolerant Tracking Control of Nonlinear Nonstrict-Feedback Systems.

PubMed

Wu, Chengwei; Liu, Jianxing; Xiong, Yongyang; Wu, Ligang

2017-06-28

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of ''explosion of complexity''. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper.

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.

Reducing model uncertainty effects in flexible manipulators through the addition of passive damping

NASA Technical Reports Server (NTRS)

Alberts, T. E.

1987-01-01

An important issue in the control of practical systems is the effect of model uncertainty on closed loop performance. This is of particular concern when flexible structures are to be controlled, due to the fact that states associated with higher frequency vibration modes are truncated in order to make the control problem tractable. Digital simulations of a single-link manipulator system are employed to demonstrate that passive damping added to the flexible member reduces adverse effects associated with model uncertainty. A controller was designed based on a model including only one flexible mode. This controller was applied to larger order systems to evaluate the effects of modal truncation. Simulations using a Linear Quadratic Regulator (LQR) design assuming full state feedback illustrate the effect of control spillover. Simulations of a system using output feedback illustrate the destabilizing effect of observation spillover. The simulations reveal that the system with passive damping is less susceptible to these effects than the untreated case.

Adaptive Neural Networks Prescribed Performance Control Design for Switched Interconnected Uncertain Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-06-28

In this paper, an adaptive neural networks (NNs)-based decentralized control scheme with the prescribed performance is proposed for uncertain switched nonstrict-feedback interconnected nonlinear systems. It is assumed that nonlinear interconnected terms and nonlinear functions of the concerned systems are unknown, and also the switching signals are unknown and arbitrary. A linear state estimator is constructed to solve the problem of unmeasured states. The NNs are employed to approximate unknown interconnected terms and nonlinear functions. A new output feedback decentralized control scheme is developed by using the adaptive backstepping design technique. The control design problem of nonlinear interconnected switched systems with unknown switching signals can be solved by the proposed scheme, and only a tuning parameter is needed for each subsystem. The proposed scheme can ensure that all variables of the control systems are semi-globally uniformly ultimately bounded and the tracking errors converge to a small residual set with the prescribed performance bound. The effectiveness of the proposed control approach is verified by some simulation results.

Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?

NASA Astrophysics Data System (ADS)

Fels, Meike; Bauer, Robert; Gharabaghi, Alireza

2015-08-01

Objective. Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns. Approach. We assessed the perceived workload with the NASA Task Load Index in twenty-one subjects who were exposed to two different feedback tasks in a cross-over design: (i) brain-robot interface (BRI) with haptic/proprioceptive feedback of sensorimotor oscillations related to motor imagery, and (ii) control of neuromuscular activity with feedback of the electromyography (EMG) of the same hand. We also used electroencephalography to examine the cortical activation patterns beforehand in resting state and during the training session of each task. Main results. The workload profile of BRI feedback differed from EMG feedback and was particularly characterized by the experience of frustration. The frustration level was highly correlated across tasks, suggesting subject-related relevance of this workload component. Those subjects who were specifically challenged by the respective tasks could be detected by an interhemispheric alpha-band network in resting state before the training and by their sensorimotor theta-band activation pattern during the exercise. Significance. Neurophysiological profiles in resting state and during the exercise may provide task-independent workload markers for monitoring and matching participants’ ability and task difficulty of neurofeedback interventions.

Dependable control systems with Internet of Things.

PubMed

Tran, Tri; Ha, Q P

2015-11-01

This paper presents an Internet of Things (IoT)-enabled dependable control system (DepCS) for continuous processes. In a DepCS, an actuator and a transmitter form a regulatory control loop. Each processor inside such actuator and transmitter is designed as a computational platform implementing the feedback control algorithm. The connections between actuators and transmitters via IoT create a reliable backbone for a DepCS. The centralized input-output marshaling system is not required in DepCSs. A state feedback control synthesis method for DepCS applying the self-recovery constraint is presented in the second part of the paper. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

On the Effect of Feedback Control on Benard Convection in a Boussinesq Fluid

NASA Technical Reports Server (NTRS)

Shortis, Trudi A.; Hall, Philip

1996-01-01

The effect of nonlinear feedback control strategies on the platform of convection in a Boussinesq fluid heated from below is investigated. In the absence of the control, given that non-Boussinesq effects may be neglected, it is well known that convection begins in the form of a supercritical bifurcation to rolls. Non-Boussinesq behaviour destroys the symmetry of the basic state, and through a subcritical bifurcation leads to the formation of hexagonal cells. Here we discuss the influence of regulation of the lower surface temperature by means of a control mechanism, made up of a combination of a proportional linear and nonlinear controller, on the stability of the hexagonal cell pattern.

Stabilization of exact nonlinear Timoshenko beams in space by boundary feedback

NASA Astrophysics Data System (ADS)

Do, K. D.

2018-05-01

Boundary feedback controllers are designed to stabilize Timoshenko beams with large translational and rotational motions in space under external disturbances. The exact nonlinear partial differential equations governing motion of the beams are derived and used in the control design. The designed controllers guarantee globally practically asymptotically (and locally practically exponentially) stability of the beam motions at the reference state. The control design, well-posedness and stability analysis are based on various relationships between the earth-fixed and body-fixed coordinates, Sobolev embeddings, and a Lyapunov-type theorem developed to study well-posedness and stability for a class of evolution systems in Hilbert space. Simulation results are included to illustrate the effectiveness of the proposed control design.

Anti-windup adaptive PID control design for a class of uncertain chaotic systems with input saturation.

PubMed

Tahoun, A H

2017-01-01

In this paper, the stabilization problem of actuators saturation in uncertain chaotic systems is investigated via an adaptive PID control method. The PID control parameters are auto-tuned adaptively via adaptive control laws. A multi-level augmented error is designed to account for the extra terms appearing due to the use of PID and saturation. The proposed control technique uses both the state-feedback and the output-feedback methodologies. Based on Lyapunov׳s stability theory, new anti-windup adaptive controllers are proposed. Demonstrative examples with MATLAB simulations are studied. The simulation results show the efficiency of the proposed adaptive PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

Next-generation audit and feedback for inpatient quality improvement using electronic health record data: a cluster randomised controlled trial.

PubMed

Patel, Sajan; Rajkomar, Alvin; Harrison, James D; Prasad, Priya A; Valencia, Victoria; Ranji, Sumant R; Mourad, Michelle

2018-03-05

Audit and feedback improves clinical care by highlighting the gap between current and ideal practice. We combined best practices of audit and feedback with continuously generated electronic health record data to improve performance on quality metrics in an inpatient setting. We conducted a cluster randomised control trial comparing intensive audit and feedback with usual audit and feedback from February 2016 to June 2016. The study subjects were internal medicine teams on the teaching service at an urban tertiary care hospital. Teams in the intensive feedback arm received access to a daily-updated team-based data dashboard as well as weekly inperson review of performance data ('STAT rounds'). The usual feedback arm received ongoing twice-monthly emails with graphical depictions of team performance on selected quality metrics. The primary outcome was performance on a composite discharge metric (Discharge Mix Index, 'DMI'). A washout period occurred at the end of the trial (from May through June 2016) during which STAT rounds were removed from the intensive feedback arm. A total of 40 medicine teams participated in the trial. During the intervention period, the primary outcome of completion of the DMI was achieved on 79.3% (426/537) of patients in the intervention group compared with 63.2% (326/516) in the control group (P<0.0001). During the washout period, there was no significant difference in performance between the intensive and usual feedback groups. Intensive audit and feedback using timely data and STAT rounds significantly increased performance on a composite discharge metric compared with usual feedback. With the cessation of STAT rounds, performance between the intensive and usual feedback groups did not differ significantly, highlighting the importance of feedback delivery on effecting change. The trial was registered with ClinicalTrials.gov (NCT02593253). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Feedback control of an interacting Bose-Einstein condensate using phase-contrast imaging

NASA Astrophysics Data System (ADS)

Szigeti, S. S.; Hush, M. R.; Carvalho, A. R. R.; Hope, J. J.

2010-10-01

The linewidth of an atom laser is limited by density fluctuations in the Bose-Einstein condensate (BEC) from which the atom laser beam is outcoupled. In this paper we show that a stable spatial mode for an interacting BEC can be generated using a realistic control scheme that includes the effects of the measurement backaction. This model extends the feedback theory, based on a phase-contrast imaging setup, presented by Szigeti, Hush, Carvalho, and Hope [Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.80.013614 80, 013614 (2009)]. In particular, it is applicable to a BEC with large interatomic interactions and solves the problem of inadequacy of the mean-field (coherent state) approximation by utilizing a fixed number state approximation. Our numerical analysis shows the control to be more effective for a condensate with a large nonlinearity.

Feedback control of an interacting Bose-Einstein condensate using phase-contrast imaging

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

Szigeti, S. S.; Hush, M. R.; Carvalho, A. R. R.

2010-10-15

The linewidth of an atom laser is limited by density fluctuations in the Bose-Einstein condensate (BEC) from which the atom laser beam is outcoupled. In this paper we show that a stable spatial mode for an interacting BEC can be generated using a realistic control scheme that includes the effects of the measurement backaction. This model extends the feedback theory, based on a phase-contrast imaging setup, presented by Szigeti, Hush, Carvalho, and Hope [Phys. Rev. A 80, 013614 (2009)]. In particular, it is applicable to a BEC with large interatomic interactions and solves the problem of inadequacy of the mean-fieldmore » (coherent state) approximation by utilizing a fixed number state approximation. Our numerical analysis shows the control to be more effective for a condensate with a large nonlinearity.« less

Robustness of linear quadratic state feedback designs in the presence of system uncertainty. [application to Augmentor Wing Jet STOL Research Aircraft flare control autopilot design

NASA Technical Reports Server (NTRS)

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

1977-01-01

The paper deals with the problem of expressing the robustness (stability) property of a linear quadratic state feedback (LQSF) design quantitatively in terms of bounds on the perturbations (modeling errors or parameter variations) in the system matrices so that the closed-loop system remains stable. Nonlinear time-varying and linear time-invariant perturbations are considered. The only computation required in obtaining a measure of the robustness of an LQSF design is to determine the eigenvalues of two symmetric matrices determined when solving the algebraic Riccati equation corresponding to the LQSF design problem. Results are applied to a complex dynamic system consisting of the flare control of a STOL aircraft. The design of the flare control is formulated as an LQSF tracking problem.

Periodic-disturbance accommodating control of the space station for asymptotic momentum management

NASA Technical Reports Server (NTRS)

Warren, Wayne; Wie, Bong; Geller, David

1989-01-01

Periodic-disturbance accommodating control is investigated for asymptotic momentum management of control moment gyros used as primary actuating devices for the Space Station. The proposed controller utilizes the concepts of quaternion feedback control and periodic-disturbance accommodation to achieve oscillations about the constant torque equilibrium attitude, while minimizing the control effort required. Three-axis coupled equations of motion, written in terms of quaternions, are derived for roll/yaw controller design and stability analysis. The quaternion feedback controller designed using the linear-quadratic regulator synthesis technique is shown to be robust for a wide range of pitch angles. It is also shown that the proposed controller tunes the open-loop unstable vehicle to a stable oscillatory motion which minimizes the control effort needed for steady-state operations.

SDRE control strategy applied to a nonlinear robotic including drive motor

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

Lima, Jeferson J. de, E-mail: jefersonjl82@gmail.com, E-mail: tusset@utfpr.edu.br, E-mail: fcjanzen@utfpr.edu.br, E-mail: piccirillo@utfpr.edu.br, E-mail: claudinor@utfpr.edu.br; Tusset, Angelo M., E-mail: jefersonjl82@gmail.com, E-mail: tusset@utfpr.edu.br, E-mail: fcjanzen@utfpr.edu.br, E-mail: piccirillo@utfpr.edu.br, E-mail: claudinor@utfpr.edu.br; Janzen, Frederic C., E-mail: jefersonjl82@gmail.com, E-mail: tusset@utfpr.edu.br, E-mail: fcjanzen@utfpr.edu.br, E-mail: piccirillo@utfpr.edu.br, E-mail: claudinor@utfpr.edu.br

A robotic control design considering all the inherent nonlinearities of the robot-engine configuration is developed. The interactions between the robot and joint motor drive mechanism are considered. The proposed control combines two strategies, one feedforward control in order to maintain the system in the desired coordinate, and feedback control system to take the system into a desired coordinate. The feedback control is obtained using State-Dependent Riccati Equation (SDRE). For link positioning two cases are considered. Case I: For control positioning, it is only used motor voltage; Case II: For control positioning, it is used both motor voltage and torque betweenmore » the links. Simulation results, including parametric uncertainties in control shows the feasibility of the proposed control for the considered system.« less

Ignorance is bliss: general and robust cancellation of decoherence via no-knowledge quantum feedback.

PubMed

Szigeti, Stuart S; Carvalho, Andre R R; Morley, James G; Hush, Michael R

2014-07-11

A "no-knowledge" measurement of an open quantum system yields no information about any system observable; it only returns noise input from the environment. Surprisingly, performing such a no-knowledge measurement can be advantageous. We prove that a system undergoing no-knowledge monitoring has reversible noise, which can be canceled by directly feeding back the measurement signal. We show how no-knowledge feedback control can be used to cancel decoherence in an arbitrary quantum system coupled to a Markovian reservoir that is being monitored. Since no-knowledge feedback does not depend on the system state or Hamiltonian, such decoherence cancellation is guaranteed to be general and robust, and can operate in conjunction with any other quantum control protocol. As an application, we show that no-knowledge feedback could be used to improve the performance of dissipative quantum computers subjected to local loss.

Comparing the Degree of Land-Atmosphere Interaction in Four Atmospheric General Circulation Models

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Dirmeyer, Paul A.; Hahmann, Andrea N.; Ijpelaar, Ruben; Tyahla, Lori; Cox, Peter; Suarez, Max J.; Houser, Paul R. (Technical Monitor)

2001-01-01

Land-atmosphere feedback, by which (for example) precipitation-induced moisture anomalies at the land surface affect the overlying atmosphere and thereby the subsequent generation of precipitation, has been examined and quantified with many atmospheric general circulation models (AGCMs). Generally missing from such studies, however, is an indication of the extent to which the simulated feedback strength is model dependent. Four modeling groups have recently performed a highly controlled numerical experiment that allows an objective inter-model comparison of land-atmosphere feedback strength. The experiment essentially consists of an ensemble of simulations in which each member simulation artificially maintains the same time series of surface prognostic variables. Differences in atmospheric behavior between the ensemble members then indicates the degree to which the state of the land surface controls atmospheric processes in that model. A comparison of the four sets of experimental results shows that feedback strength does indeed vary significantly between the AGCMs.

Robust consensus control with guaranteed rate of convergence using second-order Hurwitz polynomials

NASA Astrophysics Data System (ADS)

Fruhnert, Michael; Corless, Martin

2017-10-01

This paper considers homogeneous networks of general, linear time-invariant, second-order systems. We consider linear feedback controllers and require that the directed graph associated with the network contains a spanning tree and systems are stabilisable. We show that consensus with a guaranteed rate of convergence can always be achieved using linear state feedback. To achieve this, we provide a new and simple derivation of the conditions for a second-order polynomial with complex coefficients to be Hurwitz. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. Based on the conditions found, methods to compute feedback gains are proposed. We show that gains can be chosen such that consensus is achieved robustly over a variety of communication structures and system dynamics. We also consider the use of static output feedback.

Design of a feedback-feedforward steering controller for accurate path tracking and stability at the limits of handling

NASA Astrophysics Data System (ADS)

Kapania, Nitin R.; Gerdes, J. Christian

2015-12-01

This paper presents a feedback-feedforward steering controller that simultaneously maintains vehicle stability at the limits of handling while minimising lateral path tracking deviation. The design begins by considering the performance of a baseline controller with a lookahead feedback scheme and a feedforward algorithm based on a nonlinear vehicle handling diagram. While this initial design exhibits desirable stability properties at the limits of handling, the steady-state path deviation increases significantly at highway speeds. Results from both linear and nonlinear analyses indicate that lateral path tracking deviations are minimised when vehicle sideslip is held tangent to the desired path at all times. Analytical results show that directly incorporating this sideslip tangency condition into the steering feedback dramatically improves lateral path tracking, but at the expense of poor closed-loop stability margins. However, incorporating the desired sideslip behaviour into the feedforward loop creates a robust steering controller capable of accurate path tracking and oversteer correction at the physical limits of tyre friction. Experimental data collected from an Audi TTS test vehicle driving at the handling limits on a full length race circuit demonstrates the improved performance of the final controller design.

Afferent Neural Feedback Overrides the Modulating Effects of Arousal, Hypercapnia and Hypoxemia on Neonatal Cardio-respiratory Control.

PubMed

Lumb, Kathleen J; Schneider, Jennifer M; Ibrahim, Thowfique; Rigaux, Anita; Hasan, Shabih U

2018-04-20

Evidence at whole animal, organ-system, and cellular and molecular levels suggests that afferent volume feedback is critical for establishment of adequate ventilation at birth. Due to the irreversible nature of vagal ablation studies to date, it was difficult to quantify the roles of afferent volume input, arousal and changes in blood gas tensions on neonatal respiratory control. During reversible perineural vagal block, profound apneas, and hypoxemia and hypercarbia were observed necessitating termination of perineural blockade. Respiratory depression and apneas were independent of the sleep states. We demonstrate that profound apneas and life-threatening respiratory failure in vagally denervated animals do not result from lack of arousal or hypoxemia. Change in sleep state and concomitant respiratory depression result from lack of afferent volume feedback, which appears to be critical for the maintenance of normal breathing patterns and adequate gas exchange during the early postnatal period. Afferent volume feedback plays a vital role in neonatal respiratory control. Mechanisms for the profound respiratory depression and life-threatening apneas observed in vagally denervated neonatal animals remain unclear. We investigated the roles of sleep states, hypoxic-hypercapnia and afferent volume feedback on respiratory depression using reversible perineural vagal block during early postnatal period. Seven lambs were instrumented during the first 48h of life to record/analyze sleep states, diaphragmatic electromyograph, arterial blood gas tensions, systemic arterial blood pressure and rectal temperature. Perineural cuffs were placed around the vagi to attain reversible blockade. Post-operatively, during the awake state, both vagi were blocked using 2% xylocaine for up to 30 minutes. Compared with baseline values, pHa, PaO 2 and SaO 2 decreased and PaCO 2 increased during perineural blockade (P < 0.05). Four of seven animals exhibited apneas of ≥20 sec requiring immediate termination of perineural blockade. Breathing rates decreased from the baseline value of 53 ± 12 to 24 ± 20 breaths/min during blockade despite an increased PaCO 2 (P < 0.001). Following blockade, breathing patterns returned to baseline values despite marked hypocapnia (PaCO 2 33 ± 3 torr; P = 0.03). Respiratory depression and apneas were independent of sleep states. This study provides the much needed physiologic evidence that profound apneas and life-threatening respiratory failure in vagally denervated animals do not result from lack of arousal or hypoxemia. Rather, change in sleep state and concomitant respiratory depression result from lack of afferent volume feedback, which appears to be critical for the maintenance of normal breathing patterns and adequate gas exchange during the early postnatal period. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Force Modeling, Identification, and Feedback Control of Robot-Assisted Needle Insertion: A Survey of the Literature

PubMed Central

Xie, Yu; Liu, Shuang; Sun, Dong

2018-01-01

Robot-assisted surgery is of growing interest in the surgical and engineering communities. The use of robots allows surgery to be performed with precision using smaller instruments and incisions, resulting in shorter healing times. However, using current technology, an operator cannot directly feel the operation because the surgeon-instrument and instrument-tissue interaction force feedbacks are lost during needle insertion. Advancements in force feedback and control not only help reduce tissue deformation and needle deflection but also provide the surgeon with better control over the surgical instruments. The goal of this review is to summarize the key components surrounding the force feedback and control during robot-assisted needle insertion. The literature search was conducted during the middle months of 2017 using mainstream academic search engines with a combination of keywords relevant to the field. In total, 166 articles with valuable contents were analyzed and grouped into five related topics. This survey systemically summarizes the state-of-the-art force control technologies for robot-assisted needle insertion, such as force modeling, measurement, the factors that influence the interaction force, parameter identification, and force control algorithms. All studies show force control is still at its initial stage. The influence factors, needle deflection or planning remain open for investigation in future. PMID:29439539

Force Modeling, Identification, and Feedback Control of Robot-Assisted Needle Insertion: A Survey of the Literature.

PubMed

Yang, Chongjun; Xie, Yu; Liu, Shuang; Sun, Dong

2018-02-12

Robot-assisted surgery is of growing interest in the surgical and engineering communities. The use of robots allows surgery to be performed with precision using smaller instruments and incisions, resulting in shorter healing times. However, using current technology, an operator cannot directly feel the operation because the surgeon-instrument and instrument-tissue interaction force feedbacks are lost during needle insertion. Advancements in force feedback and control not only help reduce tissue deformation and needle deflection but also provide the surgeon with better control over the surgical instruments. The goal of this review is to summarize the key components surrounding the force feedback and control during robot-assisted needle insertion. The literature search was conducted during the middle months of 2017 using mainstream academic search engines with a combination of keywords relevant to the field. In total, 166 articles with valuable contents were analyzed and grouped into five related topics. This survey systemically summarizes the state-of-the-art force control technologies for robot-assisted needle insertion, such as force modeling, measurement, the factors that influence the interaction force, parameter identification, and force control algorithms. All studies show force control is still at its initial stage. The influence factors, needle deflection or planning remain open for investigation in future.

The Dependence of Cloud-SST Feedback on Circulation Regime and Timescale

NASA Astrophysics Data System (ADS)

Middlemas, E.; Clement, A. C.; Medeiros, B.

2017-12-01

Studies suggest cloud radiative feedback amplifies internal variability of Pacific sea surface temperature (SST) on interannual-and-longer timescales, though only a few modeling studies have tested the quantitative importance of this feedback (Bellomo et al. 2014b, Brown et al. 2016, Radel et al. 2016 Burgman et al. 2017). We prescribe clouds from a previous control run in the radiation module in Community Atmospheric Model (CAM5-slab), a method called "cloud-locking". By comparing this run to a control run, in which cloud radiative forcing can feedback on the climate system, we isolate the effect of cloud radiative forcing on SST variability. Cloud-locking prevents clouds from radiatively interacting with atmospheric circulation, water vapor, and SST, while maintaining a similar mean state to the control. On all timescales, cloud radiative forcing's influence on SST variance is modulated by the circulation regime. Cloud radiative forcing amplifies SST variance in subsiding regimes and dampens SST variance in convecting regimes. In this particular model, a tug of war between latent heat flux and cloud radiative forcing determines the variance of SST, and the winner depends on the timescale. On decadal-and-longer timescales, cloud radiative forcing plays a relatively larger role than on interannual-and-shorter timescales, while latent heat flux plays a smaller role. On longer timescales, the absence of cloud radiative feedback changes SST variance in a zonally asymmetric pattern in the Pacific Ocean that resembles an IPO-like pattern. We also present an analysis of cloud feedback's role on Pacific SST variability among preindustrial control CMIP5 models to test the model robustness of our results. Our results suggest that circulation plays a crucial role in cloud-SST feedbacks across the globe and cloud radiative feedbacks cannot be ignored when studying SST variability on decadal-and-longer timescales.

Control of constraint forces and trajectories in a rich sensory and actuation environment.

PubMed

Hemami, Hooshang; Dariush, Behzad

2010-12-01

A simple control strategy is proposed and applied to a class of non-linear systems that have abundant sensory and actuation channels as in living systems. The main objective is the independent control of constrained trajectories of motion, and control of the corresponding constraint forces. The peripheral controller is a proportional, derivative and integral (PID) controller. A central controller produces, via pattern generators, reference signals that are the desired constrained position and velocity trajectories, and the desired constraint forces. The basic tenet of the this hybrid control strategy is the use of two mechanisms: 1. linear state and force feedback, and 2. non-linear constraint velocity feedback - sliding mode feedback. The first mechanism can be envisioned as a high gain feedback systems. The high gain attribute imitates the agonist-antagonist co-activation in natural systems. The strategy is applied to the control of the force and trajectory of a two-segment thigh-leg planar biped leg with a mass-less foot cranking a pedal that is analogous to a bicycle pedal. Five computational experiments are presented to show the effectiveness of the strategy and the performance of the controller. The findings of this paper are applicable to the design of orthoses and prostheses to supplement functional electrical stimulation for support purposes in the spinally injured cases. Copyright © 2010 Elsevier Inc. All rights reserved.

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.

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.

Robust Control Algorithm for a Two Cart System and an Inverted Pendulum

NASA Technical Reports Server (NTRS)

Wilson, Chris L.; Capo-Lugo, Pedro

2011-01-01

The Rectilinear Control System can be used to simulate a launch vehicle during liftoff. Several control schemes have been developed that can control different dynamic models of the rectilinear plant. A robust control algorithm was developed that can control a pendulum to maintain an inverted position. A fluid slosh tank will be attached to the pendulum in order to test robustness in the presence of unknown slosh characteristics. The rectilinear plant consists of a DC motor and three carts mounted in series. Each cart s weight can be adjusted with brass masses and the carts can be coupled with springs. The pendulum is mounted on the first cart and an adjustable air damper can be attached to the third cart if desired. Each cart and the pendulum have a quadrature encoder to determine position. Full state feedback was implemented in order to develop the control algorithm along with a state estimator to determine the velocity states of the system. A MATLAB program was used to convert the state space matrices from continuous time to discrete time. This program also used a desired phase margin and damping ratio to determine the feedback gain matrix that would be used in the LabVIEW program. This experiment will allow engineers to gain a better understanding of liquid propellant slosh dynamics, therefore enabling them to develop more robust control algorithms for launch vehicle systems

Fault tolerant control laws

NASA Technical Reports Server (NTRS)

Ly, U. L.; Ho, J. K.

1986-01-01

A systematic procedure for the synthesis of fault tolerant control laws to actuator failure has been presented. Two design methods were used to synthesize fault tolerant controllers: the conventional LQ design method and a direct feedback controller design method SANDY. The latter method is used primarily to streamline the full-state Q feedback design into a practical implementable output feedback controller structure. To achieve robustness to control actuator failure, the redundant surfaces are properly balanced according to their control effectiveness. A simple gain schedule based on the landing gear up/down logic involving only three gains was developed to handle three design flight conditions: Mach .25 and Mach .60 at 5000 ft and Mach .90 at 20,000 ft. The fault tolerant control law developed in this study provides good stability augmentation and performance for the relaxed static stability aircraft. The augmented aircraft responses are found to be invariant to the presence of a failure. Furthermore, single-loop stability margins of +6 dB in gain and +30 deg in phase were achieved along with -40 dB/decade rolloff at high frequency.

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.

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.

The Stability Region for Feedback Control of the Wake Behind Twin Oscillating Cylinders

NASA Astrophysics Data System (ADS)

Borggaard, Jeff; Gugercin, Serkan; Zietsman, Lizette

2016-11-01

Linear feedback control has the ability to stabilize vortex shedding behind twin cylinders where cylinder rotation is the actuation mechanism. Complete elimination of the wake is only possible for certain Reynolds numbers and cylinder spacing. This is related to the presence of asymmetric unstable modes in the linearized system. We investigate this region of parameter space using a number of closed-loop simulations that bound this region. We then consider the practical issue of designing feedback controls based on limited state measurements by building a nonlinear compensator using linear robust control theory with and incorporating the nonlinear terms in the compensator (e.g., using the extended Kalman filter). Interpolatory model reduction methods are applied to the large discretized, linearized Navier-Stokes system and used for computing the control laws and compensators. Preliminary closed-loop simulations of a three-dimensional version of this problem will also be presented. Supported in part by the National Science Foundation.

Conic Sector Analysis of Hybrid Control Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1982-01-01

A hybrid control system contains an analog plant and a hybrid (or sampled-data) compensator. In this thesis a new conic sector is determined which is constructive and can be used to: (1) determine closed loop stability, (2) analyze robustness with respect to modelling uncertainties, (3) analyze steady state response to commands, and (4) select the sample rate. The use of conic sectors allows the designer to treat hybrid control systems as though they were analog control systems. The center of the conic sector can be used as a rigorous linear time invariant approximation of the hybrid control system, and the radius places a bound on the errors of this approximation. The hybrid feedback system can be multivariable, and the sampler is assumed to be synchronous. Algorithms to compute the conic sector are presented. Several examples demonstrate how the conic sector analysis techniques are applied. Extensions to single loop multirate hybrid feedback systems are presented. Further extensions are proposed for multiloop multirate hybrid feedback system and for single rate systems with asynchronous sampling.

Effects of computer-based immediate feedback on foreign language listening comprehension and test-associated anxiety.

PubMed

Lee, Shu-Ping; Su, Hui-Kai; Lee, Shin-Da

2012-06-01

This study investigated the effects of immediate feedback on computer-based foreign language listening comprehension tests and on intrapersonal test-associated anxiety in 72 English major college students at a Taiwanese University. Foreign language listening comprehension of computer-based tests designed by MOODLE, a dynamic e-learning environment, with or without immediate feedback together with the state-trait anxiety inventory (STAI) were tested and repeated after one week. The analysis indicated that immediate feedback during testing caused significantly higher anxiety and resulted in significantly higher listening scores than in the control group, which had no feedback. However, repeated feedback did not affect the test anxiety and listening scores. Computer-based immediate feedback did not lower debilitating effects of anxiety but enhanced students' intrapersonal eustress-like anxiety and probably improved their attention during listening tests. Computer-based tests with immediate feedback might help foreign language learners to increase attention in foreign language listening comprehension.

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.

Stabilizing detached Bridgman melt crystal growth: Proportional-integral feedback control

NASA Astrophysics Data System (ADS)

Yeckel, Andrew; Daoutidis, Prodromos; Derby, Jeffrey J.

2012-10-01

The dynamics, operability limits, and tuning of a proportional-integral feedback controller to stabilize detached vertical Bridgman crystal growth are analyzed using a capillary model of shape stability. The manipulated variable is the pressure difference between upper and lower vapor spaces, and the controlled variable is the gap width at the triple-phase line. Open and closed loop dynamics of step changes in these state variables are analyzed under both shape stable and shape unstable growth conditions. Effects of step changes in static contact angle and growth angle are also studied. Proportional and proportional-integral control can stabilize unstable growth, but only within tight operability limits imposed by the narrow range of allowed meniscus shapes. These limits are used to establish safe operating ranges of controller gain. Strong nonlinearity of the capillary model restricts the range of perturbations that can be stabilized, and under some circumstances, stabilizes a spurious operating state far from the set point. Stabilizing detachment at low growth angle proves difficult and becomes impossible at zero growth angle.

Robust iterative learning control for multi-phase batch processes: an average dwell-time method with 2D convergence indexes

NASA Astrophysics Data System (ADS)

Wang, Limin; Shen, Yiteng; Yu, Jingxian; Li, Ping; Zhang, Ridong; Gao, Furong

2018-01-01

In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini-Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy.

Delayed-feedback chimera states: Forced multiclusters and stochastic resonance

NASA Astrophysics Data System (ADS)

Semenov, V.; Zakharova, A.; Maistrenko, Y.; Schöll, E.

2016-07-01

A nonlinear oscillator model with negative time-delayed feedback is studied numerically under external deterministic and stochastic forcing. It is found that in the unforced system complex partial synchronization patterns like chimera states as well as salt-and-pepper-like solitary states arise on the route from regular dynamics to spatio-temporal chaos. The control of the dynamics by external periodic forcing is demonstrated by numerical simulations. It is shown that one-cluster and multi-cluster chimeras can be achieved by adjusting the external forcing frequency to appropriate resonance conditions. If a stochastic component is superimposed to the deterministic external forcing, chimera states can be induced in a way similar to stochastic resonance, they appear, therefore, in regimes where they do not exist without noise.

Controlling Mackey-Glass chaos.

PubMed

Kiss, Gábor; Röst, Gergely

2017-11-01

The Mackey-Glass equation is the representative example of delay induced chaotic behavior. Here, we propose various control mechanisms so that otherwise erratic solutions are forced to converge to the positive equilibrium or to a periodic orbit oscillating around that equilibrium. We take advantage of some recent results of the delay differential literature, when a sufficiently large domain of the phase space has been shown to be attractive and invariant, where the system is governed by monotone delayed feedback and chaos is not possible due to some Poincaré-Bendixson type results. We systematically investigate what control mechanisms are suitable to drive the system into such a situation and prove that constant perturbation, proportional feedback control, Pyragas control, and state dependent delay control can all be efficient to control Mackey-Glass chaos with properly chosen control parameters.

Controlling Mackey-Glass chaos

NASA Astrophysics Data System (ADS)

Kiss, Gábor; Röst, Gergely

2017-11-01

The Mackey-Glass equation is the representative example of delay induced chaotic behavior. Here, we propose various control mechanisms so that otherwise erratic solutions are forced to converge to the positive equilibrium or to a periodic orbit oscillating around that equilibrium. We take advantage of some recent results of the delay differential literature, when a sufficiently large domain of the phase space has been shown to be attractive and invariant, where the system is governed by monotone delayed feedback and chaos is not possible due to some Poincaré-Bendixson type results. We systematically investigate what control mechanisms are suitable to drive the system into such a situation and prove that constant perturbation, proportional feedback control, Pyragas control, and state dependent delay control can all be efficient to control Mackey-Glass chaos with properly chosen control parameters.

Measurement-based control of a mechanical oscillator at its thermal decoherence rate.

PubMed

Wilson, D J; Sudhir, V; Piro, N; Schilling, R; Ghadimi, A; Kippenberg, T J

2015-08-20

In real-time quantum feedback protocols, the record of a continuous measurement is used to stabilize a desired quantum state. Recent years have seen successful applications of these protocols in a variety of well-isolated micro-systems, including microwave photons and superconducting qubits. However, stabilizing the quantum state of a tangibly massive object, such as a mechanical oscillator, remains very challenging: the main obstacle is environmental decoherence, which places stringent requirements on the timescale in which the state must be measured. Here we describe a position sensor that is capable of resolving the zero-point motion of a solid-state, 4.3-megahertz nanomechanical oscillator in the timescale of its thermal decoherence, a basic requirement for real-time (Markovian) quantum feedback control tasks, such as ground-state preparation. The sensor is based on evanescent optomechanical coupling to a high-Q microcavity, and achieves an imprecision four orders of magnitude below that at the standard quantum limit for a weak continuous position measurement--a 100-fold improvement over previous reports--while maintaining an imprecision-back-action product that is within a factor of five of the Heisenberg uncertainty limit. As a demonstration of its utility, we use the measurement as an error signal with which to feedback cool the oscillator. Using radiation pressure as an actuator, the oscillator is cold damped with high efficiency: from a cryogenic-bath temperature of 4.4 kelvin to an effective value of 1.1 ± 0.1 millikelvin, corresponding to a mean phonon number of 5.3 ± 0.6 (that is, a ground-state probability of 16 per cent). Our results set a new benchmark for the performance of a linear position sensor, and signal the emergence of mechanical oscillators as practical subjects for measurement-based quantum control.

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.

Digital current regulator for proportional electro-hydraulic valves with unknown disturbance rejection.

PubMed

Canuto, Enrico; Acuña-Bravo, Wilber; Agostani, Marco; Bonadei, Marco

2014-07-01

Solenoid current regulation is well-known and standard in any proportional electro-hydraulic valve. The goal is to provide a wide-band transfer function from the reference to the measured current, thus making the solenoid a fast and ideal force actuator within the limits of the power supplier. The power supplier is usually a Pulse Width Modulation (PWM) amplifier fixing the voltage bound and the Nyquist frequency of the regulator. Typical analog regulators include three main terms: a feedforward channel, a proportional feedback channel and the electromotive force compensation. The latter compensation may be accomplished by integrative feedback. Here the problem is faced through a model-based design (Embedded Model Control), on the basis of a wide-band embedded model of the solenoid which includes the effect of eddy currents. To this end model parameters must be identified. The embedded model includes a stochastic disturbance dynamics capable of estimating and correcting the electromotive contribution together with parametric uncertainty, variability and state dependence. The embedded model which is fed by the measured current and the supplied voltage becomes a state predictor of the controllable and disturbance dynamics. The control law combines reference generator, state feedback and disturbance rejection to dispatch the PWM amplifier with the appropriate duty cycle. Modeling, identification and control design are outlined together with experimental result. Comparison with an existing analog regulator is also provided. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

On the control canonical structure of a class of scalar input systems

NASA Technical Reports Server (NTRS)

Teglas, R.

1983-01-01

A discrete finite dimensional system, nonharmonic Fourier series and controllability, reduction to canonical form, and spectral synthesis are considered. The extent to which the eigenvalue associated with a controllable pair of a certain type may be modified via continuous linear state feedback is demonstrated.

Towards autonomous neuroprosthetic control using Hebbian reinforcement learning.

PubMed

Mahmoudi, Babak; Pohlmeyer, Eric A; Prins, Noeline W; Geng, Shijia; Sanchez, Justin C

2013-12-01

Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability/undesirability of performance. Hebbian reinforcement learning (HRL) in a connectionist network was used for the design of the adaptive controller. The method combines the efficiency of supervised learning with the generality of reinforcement learning. The convergence properties of this approach were studied using both closed-loop control simulations and open-loop simulations that used primate neural data from robot-assisted reaching tasks. The HRL controller was able to perform classification and regression tasks using its episodic and sequential learning modes, respectively. In our experiments, the HRL controller quickly achieved convergence to an effective control policy, followed by robust performance. The controller also automatically stopped adapting the parameters after converging to a satisfactory control policy. Additionally, when the input neural vector was reorganized, the controller resumed adaptation to maintain performance. By estimating an evaluative feedback directly from the user, the HRL control algorithm may provide an efficient method for autonomous adaptation of neuroprosthetic systems. This method may enable the user to teach the controller the desired behavior using only a simple feedback signal.

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

Beker, M. G., E-mail: M.Beker@Nikhef.nl; Bertolini, A.; Hennes, E.

There is a strong scientific case for the study of gravitational waves at or below the lower end of current detection bands. To take advantage of this scientific benefit, future generations of ground based gravitational wave detectors will need to expand the limit of their detection bands towards lower frequencies. Seismic motion presents a major challenge at these frequencies and vibration isolation systems will play a crucial role in achieving the desired low-frequency sensitivity. A compact vibration isolation system designed to isolate in-vacuum optical benches for Advanced Virgo will be introduced and measurements on this system are used to presentmore » its performance. All high performance isolation systems employ an active feedback control system to reduce the residual motion of their suspended payloads. The development of novel control schemes is needed to improve the performance beyond what is currently feasible. Here, we present a multi-channel feedback approach that is novel to the field. It utilizes a linear quadratic regulator in combination with a Kalman state observer and is shown to provide effective suppression of residual motion of the suspended payload. The application of state observer based feedback control for vibration isolation will be demonstrated with measurement results from the Advanced Virgo optical bench suspension system.« less

Non-linear feedback control of the p53 protein-mdm2 inhibitor system using the derivative-free non-linear Kalman filter.

PubMed

Rigatos, Gerasimos G

2016-06-01

It is proven that the model of the p53-mdm2 protein synthesis loop is a differentially flat one and using a diffeomorphism (change of state variables) that is proposed by differential flatness theory it is shown that the protein synthesis model can be transformed into the canonical (Brunovsky) form. This enables the design of a feedback control law that maintains the concentration of the p53 protein at the desirable levels. To estimate the non-measurable elements of the state vector describing the p53-mdm2 system dynamics, the derivative-free non-linear Kalman filter is used. Moreover, to compensate for modelling uncertainties and external disturbances that affect the p53-mdm2 system, the derivative-free non-linear Kalman filter is re-designed as a disturbance observer. The derivative-free non-linear Kalman filter consists of the Kalman filter recursion applied on the linearised equivalent of the protein synthesis model together with an inverse transformation based on differential flatness theory that enables to retrieve estimates for the state variables of the initial non-linear model. The proposed non-linear feedback control and perturbations compensation method for the p53-mdm2 system can result in more efficient chemotherapy schemes where the infusion of medication will be better administered.

Unsteady steady-states: Central causes of unintentional force drift

PubMed Central

Ambike, Satyajit; Mattos, Daniela; Zatsiorsky, Vladimir M.; Latash, Mark L.

2016-01-01

We applied the theory of synergies to analyze the processes that lead to unintentional decline in isometric fingertip force when visual feedback of the produced force is removed. We tracked the changes in hypothetical control variables involved in single fingertip force production based on the equilibrium-point hypothesis, namely, the fingertip referent coordinate (RFT) and its apparent stiffness (CFT). The system's state is defined by a point in the {RFT; CFT} space. We tested the hypothesis that, after visual feedback removal, this point (1) moves along directions leading to drop in the output fingertip force, and (2) has even greater motion along directions that leaves the force unchanged. Subjects produced a prescribed fingertip force using visual feedback, and attempted to maintain this force for 15 s after the feedback was removed. We used the “inverse piano” apparatus to apply small and smooth positional perturbations to fingers at various times after visual feedback removal. The time courses of RFT and CFT showed that force drop was mostly due to a drift in RFT towards the actual fingertip position. Three analysis techniques, namely, hyperbolic regression, surrogate data analysis, and computation of motor-equivalent and non-motor-equivalent motions, suggested strong co-variation in RFT and CFT stabilizing the force magnitude. Finally, the changes in the two hypothetical control variables {RFT; CFT} relative to their average trends also displayed covariation. On the whole the findings suggest that unintentional force drop is associated with (a) a slow drift of the referent coordinate that pulls the system towards a low-energy state, and (b) a faster synergic motion of RFT and CFT that tends to stabilize the output fingertip force about the slowly-drifting equilibrium point. PMID:27540726

Unsteady steady-states: central causes of unintentional force drift.

PubMed

Ambike, Satyajit; Mattos, Daniela; Zatsiorsky, Vladimir M; Latash, Mark L

2016-12-01

We applied the theory of synergies to analyze the processes that lead to unintentional decline in isometric fingertip force when visual feedback of the produced force is removed. We tracked the changes in hypothetical control variables involved in single fingertip force production based on the equilibrium-point hypothesis, namely the fingertip referent coordinate (R FT ) and its apparent stiffness (C FT ). The system's state is defined by a point in the {R FT ; C FT } space. We tested the hypothesis that, after visual feedback removal, this point (1) moves along directions leading to drop in the output fingertip force, and (2) has even greater motion along directions that leaves the force unchanged. Subjects produced a prescribed fingertip force using visual feedback and attempted to maintain this force for 15 s after the feedback was removed. We used the "inverse piano" apparatus to apply small and smooth positional perturbations to fingers at various times after visual feedback removal. The time courses of R FT and C FT showed that force drop was mostly due to a drift in R FT toward the actual fingertip position. Three analysis techniques, namely hyperbolic regression, surrogate data analysis, and computation of motor-equivalent and non-motor-equivalent motions, suggested strong covariation in R FT and C FT stabilizing the force magnitude. Finally, the changes in the two hypothetical control variables {R FT ; C FT } relative to their average trends also displayed covariation. On the whole, the findings suggest that unintentional force drop is associated with (a) a slow drift of the referent coordinate that pulls the system toward a low-energy state and (b) a faster synergic motion of R FT and C FT that tends to stabilize the output fingertip force about the slowly drifting equilibrium point.

An experimental study of the correlates and consequences of perceiving oneself to be the target of gender discrimination.

PubMed

Brown, Christia Spears; Bigler, Rebecca S; Chu, Hui

2010-10-01

An experimental methodology was used to test hypotheses concerning the effects of contextual, cognitive-developmental, and individual difference factors on children's views of whether they have been the target of gender discrimination and the possible consequent effect of such views on two forms of state self-esteem: performance and social acceptance. Children (N=108, 5-11 years of age) completed theory of mind and gender attitude measures and a drawing task. Next, children received feedback that was designed to appear either gender biased (discrimination condition) or nonbiased (control condition). Children's attributions for the feedback and state self-esteem were assessed. As expected, children reported having been the target of gender discrimination more often in the discrimination condition than in the control condition. Older and more cognitively advanced children made fewer attributions to discrimination than their peers. Perceptions of discrimination were associated with higher performance state self-esteem and, among egalitarian children, lower social state self-esteem. Copyright 2010 Elsevier Inc. All rights reserved.

Children’s Feedback Preferences in Response to an Experimentally Manipulated Peer Evaluation Outcome: The Role of Depressive Symptoms

PubMed Central

Dekovic, Maja; Vermande, Marjolijn; Telch, Michael J.

2007-01-01

The present study examined the linkage between pre-adolescent children’s depressive symptoms and their preferences for receiving positive vs. negative feedback subsequent to being faced with an experimentally manipulated peer evaluation outcome in real time. Participants (n = 142) ages 10 to 13, played a computer contest based on the television show Survivor and were randomized to either a peer rejection (i.e., receiving the lowest total ‘likeability’ score from a group of peer-judges), a peer success (i.e., receiving the highest score), or a control peer evaluation condition. Children’s self-reported feedback preferences were then assessed. Results revealed that participants assigned to the negative evaluation outcome, relative to either the success or the control outcome, showed a significantly higher subsequent preference for negatively tuned feedback. Contrary to previous work and predictions derived from self-verification theory, children higher in depressive symptoms were only more likely to prefer negative feedback in response to the negative peer evaluation outcome. These effects for depression were not accounted for by either state mood at baseline or mood change in response to the feedback manipulation. PMID:17279340

Development of adaptive control applied to chaotic systems

NASA Astrophysics Data System (ADS)

Rhode, Martin Andreas

1997-12-01

Continuous-time derivative control and adaptive map-based recursive feedback control techniques are used to control chaos in a variety of systems and in situations that are of practical interest. The theoretical part of the research includes the review of fundamental concept of control theory in the context of its applications to deterministic chaotic systems, the development of a new adaptive algorithm to identify the linear system properties necessary for control, and the extension of the recursive proportional feedback control technique, RPF, to high dimensional systems. Chaos control was applied to models of a thermal pulsed combustor, electro-chemical dissolution and the hyperchaotic Rossler system. Important implications for combustion engineering were suggested by successful control of the model of the thermal pulsed combustor. The system was automatically tracked while maintaining control into regions of parameter and state space where no stable attractors exist. In a simulation of the electrochemical dissolution system, application of derivative control to stabilize a steady state, and adaptive RPF to stabilize a period one orbit, was demonstrated. The high dimensional adaptive control algorithm was applied in a simulation using the Rossler hyperchaotic system, where a period-two orbit with two unstable directions was stabilized and tracked over a wide range of a system parameter. In the experimental part, the electrochemical system was studied in parameter space, by scanning the applied potential and the frequency of the rotating copper disk. The automated control algorithm is demonstrated to be effective when applied to stabilize a period-one orbit in the experiment. We show the necessity of small random perturbations applied to the system in order to both learn the dynamics and control the system at the same time. The simultaneous learning and control capability is shown to be an important part of the active feedback control.

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

Decoupling suspension controller based on magnetic flux feedback.

PubMed

Zhang, Wenqing; Li, Jie; Zhang, Kun; Cui, Peng

2013-01-01

The suspension module control system model has been established based on MIMO (multiple input and multiple output) state feedback linearization. We have completed decoupling between double suspension points, and the new decoupling method has been applied to CMS04 magnetic suspension vehicle in national mid-low-speed maglev experiment field of Tangshan city in China. Double suspension system model is very accurate for investigating stability property of maglev control system. When magnetic flux signal is taken back to the suspension control system, the suspension module's antijamming capacity for resisting suspension load variety has been proved. Also, the external force interference has been enhanced. As a result, the robustness and stability properties of double-electromagnet suspension control system have been enhanced.

Decoupling Suspension Controller Based on Magnetic Flux Feedback

PubMed Central

Zhang, Wenqing; Li, Jie; Zhang, Kun; Cui, Peng

2013-01-01

The suspension module control system model has been established based on MIMO (multiple input and multiple output) state feedback linearization. We have completed decoupling between double suspension points, and the new decoupling method has been applied to CMS04 magnetic suspension vehicle in national mid-low-speed maglev experiment field of Tangshan city in China. Double suspension system model is very accurate for investigating stability property of maglev control system. When magnetic flux signal is taken back to the suspension control system, the suspension module's antijamming capacity for resisting suspension load variety has been proved. Also, the external force interference has been enhanced. As a result, the robustness and stability properties of double-electromagnet suspension control system have been enhanced. PMID:23844415

Resistive wall mode feedback control in EXTRAP T2R with improved steady-state error and transient response

NASA Astrophysics Data System (ADS)

Brunsell, P. R.; Olofsson, K. E. J.; Frassinetti, L.; Drake, J. R.

2007-10-01

Experiments in the EXTRAP T2R reversed field pinch [P. R. Brunsell, H. Bergsåker, M. Cecconello et al., Plasma Phys. Control. Fusion 43, 1457 (2001)] on feedback control of m =1 resistive wall modes (RWMs) are compared with simulations using the cylindrical linear magnetohydrodynamic model, including the dynamics of the active coils and power amplifiers. Stabilization of the main RWMs (n=-11,-10,-9,-8,+5,+6) is shown using modest loop gains of the order G ˜1. However, other marginally unstable RWMs (n=-2,-1,+1,+2) driven by external field errors are only partially canceled at these gains. The experimental system stability limit is confirmed by simulations showing that the latency of the digital controller ˜50μs is degrading the system gain margin. The transient response is improved with a proportional-plus-derivative controller, and steady-state error is improved with a proportional-plus-integral controller. Suppression of all modes is obtained at high gain G ˜10 using a proportional-plus-integral-plus-derivative controller.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1984-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The full state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system rmain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1985-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The fulll state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system remain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

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.

TEAMBLOCKS: HYBRID ABSTRACTIONS FOR PROVABLE MULTI-AGENT AUTONOMY

DTIC Science & Technology

2017-07-28

Raspberry Pi 23 can easily satisfy control loop periods on the order of 10−3s. Thus, we assume that the time to execute a piece of control code, ∆t...Release; Distribution Unlimited. 23 State Space The state space of the aircraft is X = R3 × SO(3) × R3 × R3; states consist of • pI ∈ R3, the...the tbdemo_ghaexecution script uses this operation to make feedback system out of the product of the linear system and PI controller. tbread

An approach to multivariable control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

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.

Quantifying the Relative Contributions of Divisive and Subtractive Feedback to Rhythm Generation

PubMed Central

Tabak, Joël; Rinzel, John; Bertram, Richard

2011-01-01

Biological systems are characterized by a high number of interacting components. Determining the role of each component is difficult, addressed here in the context of biological oscillations. Rhythmic behavior can result from the interplay of positive feedback that promotes bistability between high and low activity, and slow negative feedback that switches the system between the high and low activity states. Many biological oscillators include two types of negative feedback processes: divisive (decreases the gain of the positive feedback loop) and subtractive (increases the input threshold) that both contribute to slowly move the system between the high- and low-activity states. Can we determine the relative contribution of each type of negative feedback process to the rhythmic activity? Does one dominate? Do they control the active and silent phase equally? To answer these questions we use a neural network model with excitatory coupling, regulated by synaptic depression (divisive) and cellular adaptation (subtractive feedback). We first attempt to apply standard experimental methodologies: either passive observation to correlate the variations of a variable of interest to system behavior, or deletion of a component to establish whether a component is critical for the system. We find that these two strategies can lead to contradictory conclusions, and at best their interpretive power is limited. We instead develop a computational measure of the contribution of a process, by evaluating the sensitivity of the active (high activity) and silent (low activity) phase durations to the time constant of the process. The measure shows that both processes control the active phase, in proportion to their speed and relative weight. However, only the subtractive process plays a major role in setting the duration of the silent phase. This computational method can be used to analyze the role of negative feedback processes in a wide range of biological rhythms. PMID:21533065

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.).

Differential flatness properties and multivariable adaptive control of ovarian system dynamics

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos

2016-12-01

The ovarian system exhibits nonlinear dynamics which is modeled by a set of coupled nonlinear differential equations. The paper proposes adaptive fuzzy control based on differential flatness theory for the complex dynamics of the ovarian system. It is proven that the dynamic model of the ovarian system, having as state variables the LH and the FSH hormones and their derivatives, is a differentially flat one. This means that all its state variables and its control inputs can be described as differential functions of the flat output. By exploiting differential flatness properties the system's dynamic model is written in the multivariable linear canonical (Brunovsky) form, for which the design of a state feedback controller becomes possible. After this transformation, the new control inputs of the system contain unknown nonlinear parts, which are identified with the use of neurofuzzy approximators. The learning procedure for these estimators is determined by the requirement the first derivative of the closed-loop's Lyapunov function to be a negative one. Moreover, Lyapunov stability analysis shows that H-infinity tracking performance is succeeded for the feedback control loop and this assures improved robustness to the aforementioned model uncertainty as well as to external perturbations. The efficiency of the proposed adaptive fuzzy control scheme is confirmed through simulation experiments.

Better Bet-Hedging with coupled positive and negative feedback loops

NASA Astrophysics Data System (ADS)

Narula, Jatin; Igoshin, Oleg

2011-03-01

Bacteria use the phenotypic heterogeneity associated with bistable switches to distribute the risk of activating stress response strategies like sporulation and persistence. However bistable switches offer little control over the timing of phenotype switching and first passage times (FPT) for individual cells are found to be exponentially distributed. We show that a genetic circuit consisting of interlinked positive and negative feedback loops allows cells to control the timing of phenotypic switching. Using a mathematical model we find that in this system a stable high expression state and stable low expression limit cycle coexist and the FPT distribution for stochastic transitions between them shows multiple peaks at regular intervals. A multimodal FPT distribution allows cells to detect the persistence of stress and control the rate of phenotype transition of the population. We further show that extracellular signals from cell-cell communication that change the strength of the feedback loops can modulate the FPT distribution and allow cells even greater control in a bet-hedging strategy.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Real-time control of walking using recordings from dorsal root ganglia.

PubMed

Holinski, B J; Everaert, D G; Mushahwar, V K; Stein, R B

2013-10-01

The goal of this study was to decode sensory information from the dorsal root ganglia (DRG) in real time, and to use this information to adapt the control of unilateral stepping with a state-based control algorithm consisting of both feed-forward and feedback components. In five anesthetized cats, hind limb stepping on a walkway or treadmill was produced by patterned electrical stimulation of the spinal cord through implanted microwire arrays, while neuronal activity was recorded from the DRG. Different parameters, including distance and tilt of the vector between hip and limb endpoint, integrated gyroscope and ground reaction force were modelled from recorded neural firing rates. These models were then used for closed-loop feedback. Overall, firing-rate-based predictions of kinematic sensors (limb endpoint, integrated gyroscope) were the most accurate with variance accounted for >60% on average. Force prediction had the lowest prediction accuracy (48 ± 13%) but produced the greatest percentage of successful rule activations (96.3%) for stepping under closed-loop feedback control. The prediction of all sensor modalities degraded over time, with the exception of tilt. Sensory feedback from moving limbs would be a desirable component of any neuroprosthetic device designed to restore walking in people after a spinal cord injury. This study provides a proof-of-principle that real-time feedback from the DRG is possible and could form part of a fully implantable neuroprosthetic device with further development.

Nonlinear Control Systems

DTIC Science & Technology

2007-03-01

Finite -dimensional regulators for a class of infinite dimensional systems ,” Systems and Control Letters, 3 (1983), 7-12. [11] B...semiglobal stabilizability by encoded state feedback,” to appear in Systems and Control Letters. 22 29. C. De Persis, A. Isidori, “Global stabilization of...nonequilibrium setting, for both finite and infinite dimensional control systems . Our objectives for distributed parameter systems included

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.

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.

A new decentralised controller design method for a class of strongly interconnected systems

NASA Astrophysics Data System (ADS)

Duan, Zhisheng; Jiang, Zhong-Ping; Huang, Lin

2017-02-01

In this paper, two interconnected structures are first discussed, under which some closed-loop subsystems must be unstable to make the whole interconnected system stable, which can be viewed as a kind of strongly interconnected systems. Then, comparisons with small gain theorem are discussed and large gain interconnected characteristics are shown. A new approach for the design of decentralised controllers is presented by determining the Lyapunov function structure previously, which allows the existence of unstable subsystems. By fully utilising the orthogonal space information of input matrix, some new understandings are presented for the construction of Lyapunov matrix. This new method can deal with decentralised state feedback, static output feedback and dynamic output feedback controllers in a unified framework. Furthermore, in order to reduce the design conservativeness and deal with robustness, a new robust decentralised controller design method is given by combining with the parameter-dependent Lyapunov function method. Some basic rules are provided for the choice of initial variables in Lyapunov matrix or new introduced slack matrices. As byproducts, some linear matrix inequality based sufficient conditions are established for centralised static output feedback stabilisation. Effects of unstable subsystems in nonlinear Lur'e systems are further discussed. The corresponding decentralised controller design method is presented for absolute stability. The examples illustrate that the new method is significantly effective.

Robust output feedback stabilization for a flexible marine riser system.

PubMed

Zhao, Zhijia; Liu, Yu; Guo, Fang

2017-12-06

The aim of this paper is to develop a boundary control for the vibration reduction of a flexible marine riser system in the presence of parametric uncertainties and system states obtained inaccurately. To this end, an adaptive output feedback boundary control is proposed to suppress the riser's vibration fusing with observer-based backstepping, high-gain observers and robust adaptive control theory. In addition, the parameter adaptive laws are designed to compensate for the system parametric uncertainties, and the disturbance observer is introduced to mitigate the effects of external environmental disturbance. The uniformly bounded stability of the closed-loop system is achieved through rigorous Lyapunov analysis without any discretisation or simplification of the dynamics in the time and space, and the state observer error is ensured to exponentially converge to zero as time grows to infinity. In the end, the simulation and comparison studies are carried out to illustrate the performance of the proposed control under the proper choice of the design parameters. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Active vibration control of thin-plate structures with partial SCLD treatment

NASA Astrophysics Data System (ADS)

Lu, Jun; Wang, Pan; Zhan, Zhenfei

2017-02-01

To effectively suppress the low-frequency vibration of a thin-plate, the strategy adopted is to develop a model-based approach to the investigation on the active vibration control of a clamped-clamped plate with partial SCLD treatment. Firstly, a finite element model is developed based on the constitutive equations of elastic, piezoelectric and viscoelastic materials. The characteristics of viscoelastic materials varying with temperature and frequency are described by GHM damping model. A low-dimensional real modal control model which can be used as the basis for active vibration control is then obtained from the combined reduction. The emphasis is placed on the feedback control system to attenuate the vibration of plates with SCLD treatments. A modal controller in conjunction with modal state estimator is designed to solve the problem of full state feedback, making it much more feasible to real-time control. Finally, the theoretical model is verified by modal test, and an active vibration control is validated by hardware-in-the-loop experiment under different external excitations. The numerical and experimental study demonstrate how the piezoelectric actuators actively control the lower modes (first bending and torsional modes) using modal controller, while the higher frequency vibration attenuated by viscoelastic passive damping layer.

Predicted torque equilibrium attitude utilization for Space Station attitude control

NASA Technical Reports Server (NTRS)

Kumar, Renjith R.; Heck, Michael L.; Robertson, Brent P.

1990-01-01

An approximate knowledge of the torque equilibrium attitude (TEA) is shown to improve the performance of a control moment gyroscope (CMG) momentum management/attitude control law for Space Station Freedom. The linearized equations of motion are used in conjunction with a state transformation to obtain a control law which uses full state feedback and the predicted TEA to minimize both attitude excursions and CMG peak and secular momentum. The TEA can be computationally determined either by observing the steady state attitude of a 'controlled' spacecraft using arbitrary initial attitude, or by simulating a fixed attitude spacecraft flying in desired orbit subject to realistic environmental disturbance models.

Alternator control for battery charging

DOEpatents

Brunstetter, Craig A.; Jaye, John R.; Tallarek, Glen E.; Adams, Joseph B.

2015-07-14

In accordance with an aspect of the present disclosure, an electrical system for an automotive vehicle has an electrical generating machine and a battery. A set point voltage, which sets an output voltage of the electrical generating machine, is set by an electronic control unit (ECU). The ECU selects one of a plurality of control modes for controlling the alternator based on an operating state of the vehicle as determined from vehicle operating parameters. The ECU selects a range for the set point voltage based on the selected control mode and then sets the set point voltage within the range based on feedback parameters for that control mode. In an aspect, the control modes include a trickle charge mode and battery charge current is the feedback parameter and the ECU controls the set point voltage within the range to maintain a predetermined battery charge current.

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.

Feedback control in planarian stem cell systems.

PubMed

Mangel, Marc; Bonsall, Michael B; Aboobaker, Aziz

2016-02-13

In planarian flatworms, the mechanisms underlying the activity of collectively pluripotent adult stem cells (neoblasts) and their descendants can now be studied from the level of the individual gene to the entire animal. Flatworms maintain startling developmental plasticity and regenerative capacity in response to variable nutrient conditions or injury. We develop a model for cell dynamics in such animals, assuming that fully differentiated cells exert feedback control on neoblast activity. Our model predicts a number of whole organism level and general cell biological and behaviours, some of which have been empirically observed or inferred in planarians and others that have not. As previously observed empirically we find: 1) a curvilinear relationship between external food and planarian steady state size; 2) the fraction of neoblasts in the steady state is constant regardless of planarian size; 3) a burst of controlled apoptosis during regeneration after amputation as the number of differentiated cells are adjusted towards their homeostatic/steady state level. In addition our model describes the following properties that can inform and be tested by future experiments: 4) the strength of feedback control from differentiated cells to neoblasts (i.e. the activity of the signalling system) and from neoblasts on themselves in relation to absolute number depends upon the level of food in the environment; 5) planarians adjust size when food level reduces initially through increased apoptosis and then through a reduction in neoblast self-renewal activity; 6) following wounding or excision of differentiated cells, different time scales characterize both recovery of size and the two feedback functions; 7) the temporal pattern of feedback controls differs noticeably during recovery from a removal or neoblasts or a removal of differentiated cells; 8) the signaling strength for apoptosis of differentiated cells depends upon both the absolute and relative deviations of the number of differentiated cells from their homeostatic level; and 9) planaria prioritize resource use for cell divisions. We offer the first analytical framework for organizing experiments on planarian flatworm stem cell dynamics in a form that allows models to be compared with quantitative cell data based on underlying molecular mechanisms and thus facilitate the interplay between empirical studies and modeling. This framework is the foundation for studying cell migration during wound repair, the determination of homeostatic levels of differentiated cells by natural selection, and stochastic effects.

Modulating resonance behaviors by noise recycling in bistable systems with time delay

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

Sun, Zhongkui, E-mail: sunzk2008@gmail.com; Xu, Wei; Yang, Xiaoli

In this paper, the impact of noise recycling on resonance behaviors is studied theoretically and numerically in a prototypical bistable system with delayed feedback. According to the interior cooperating and interacting activity of noise recycling, a theory has been proposed by reducing the non-Markovian problem into a two-state model, wherein both the master equation and the transition rates depend on not only the current state but also the earlier two states due to the recycling lag and the feedback delay. By virtue of this theory, the formulae of the power spectrum density and the linear response function have been foundmore » analytically. And the theoretical results are well verified by numerical simulations. It has been demonstrated that both the recycling lag and the feedback delay play a crucial role in the resonance behaviors. In addition, the results also suggest an alternative scheme to modulate or control the coherence or stochastic resonance in bistable systems with time delay.« less

Large-angle slewing maneuvers for flexible spacecraft

NASA Technical Reports Server (NTRS)

Chun, Hon M.; Turner, James D.

1988-01-01

A new class of closed-form solutions for finite-time linear-quadratic optimal control problems is presented. The solutions involve Potter's solution for the differential matrix Riccati equation, which assumes the form of a steady-state plus transient term. Illustrative examples are presented which show that the new solutions are more computationally efficient than alternative solutions based on the state transition matrix. As an application of the closed-form solutions, the neighboring extremal path problem is presented for a spacecraft retargeting maneuver where a perturbed plant with off-nominal boundary conditions now follows a neighboring optimal trajectory. The perturbation feedback approach is further applied to three-dimensional slewing maneuvers of large flexible spacecraft. For this problem, the nominal solution is the optimal three-dimensional rigid body slew. The perturbation feedback then limits the deviations from this nominal solution due to the flexible body effects. The use of frequency shaping in both the nominal and perturbation feedback formulations reduces the excitation of high-frequency unmodeled modes. A modified Kalman filter is presented for estimating the plant states.

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

Practical scheme for error control using feedback

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

Sarovar, Mohan; Milburn, Gerard J.; Ahn, Charlene

2004-05-01

We describe a scheme for quantum-error correction that employs feedback and weak measurement rather than the standard tools of projective measurement and fast controlled unitary gates. The advantage of this scheme over previous protocols [for example, Ahn et al. Phys. Rev. A 65, 042301 (2001)], is that it requires little side processing while remaining robust to measurement inefficiency, and is therefore considerably more practical. We evaluate the performance of our scheme by simulating the correction of bit flips. We also consider implementation in a solid-state quantum-computation architecture and estimate the maximal error rate that could be corrected with current technology.

Output Control Using Feedforward And Cascade Controllers

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1990-01-01

Report presents theoretical study of open-loop control elements in single-input, single-output linear system. Focus on output-control (servomechanism) problem, in which objective is to find control scheme that causes output to track certain command inputs and to reject certain disturbance inputs in steady state. Report closes with brief discussion of characteristics and relative merits of feedforward, cascade, and feedback controllers and combinations thereof.

Programming generality into a performance feedback writing intervention: A randomized controlled trial.

PubMed

Hier, Bridget O; Eckert, Tanya L

2016-06-01

Substantial numbers of students in the United States are performing below grade-level expectations in core academic areas, and these deficits are most pronounced in the area of writing. Although performance feedback procedures have been shown to produce promising short-term improvements in elementary-aged students' writing skills, evidence of maintenance and generalization of these intervention effects is limited. The purpose of this study was to examine the immediate, generalized, and sustained effects of incorporating multiple exemplar training into the performance feedback procedures of a writing intervention using a randomized controlled trial (RCT). Results indicated that although the addition of multiple exemplar training did not improve students' writing performance on measures of stimulus and response generalization, it did result in greater maintenance of intervention effects in comparison to students who received performance feedback without generality programming and students who engaged in weekly writing practice alone. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

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.

Parallels between control PDE's (Partial Differential Equations) and systems of ODE's (Ordinary Differential Equations)

NASA Technical Reports Server (NTRS)

Hunt, L. R.; Villarreal, Ramiro

1987-01-01

System theorists understand that the same mathematical objects which determine controllability for nonlinear control systems of ordinary differential equations (ODEs) also determine hypoellipticity for linear partial differentail equations (PDEs). Moreover, almost any study of ODE systems begins with linear systems. It is remarkable that Hormander's paper on hypoellipticity of second order linear p.d.e.'s starts with equations due to Kolmogorov, which are shown to be analogous to the linear PDEs. Eigenvalue placement by state feedback for a controllable linear system can be paralleled for a Kolmogorov equation if an appropriate type of feedback is introduced. Results concerning transformations of nonlinear systems to linear systems are similar to results for transforming a linear PDE to a Kolmogorov equation.

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.

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.

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.

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).

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.

Biofeedback for Developing Self-Control of Tension and Stress in One's Hierarchy of Psychological States.

ERIC Educational Resources Information Center

Cassel, Russell

1985-01-01

Describes six stage hierarchial patterns in the development of self-control through biofeedback. The stages include Skeletal and Striated Muscle Tension; Visceral Involvement-Anxiety Neuroses; Chronic Physiological Dysfunctioning; Decision Making Competency; Twilight Learning-Permissive Concentration; and Autogenic Feedback Training. (BL)

Oscillation control system for electric motor drive

DOEpatents

Slicker, James M.; Sereshteh, Ahmad

1988-01-01

A feedback system for controlling mechanical oscillations in the torsionally complaint drive train of an electric or other vehicle. Motor speed is converted in a processor to estimate state signals in which a plant model which are used to electronically modify thetorque commands applied to the motor.

Functional characteristics of a double positive feedback loop coupled with autorepression

NASA Astrophysics Data System (ADS)

Banerjee, Subhasis; Bose, Indrani

2008-12-01

We study the functional characteristics of a two-gene motif consisting of a double positive feedback loop and an autoregulatory negative feedback loop. The motif appears in the gene regulatory network controlling the functional activity of pancreatic β-cells. The model exhibits bistability and hysteresis in appropriate parameter regions. The two stable steady states correspond to low (OFF state) and high (ON state) protein levels, respectively. Using a deterministic approach, we show that the region of bistability increases in extent when the copy number of one of the genes is reduced from 2 to 1. The negative feedback loop has the effect of reducing the size of the bistable region. Loss of a gene copy, brought about by mutations, hampers the normal functioning of the β-cells giving rise to the genetic disorder, maturity-onset diabetes of the young (MODY). The diabetic phenotype makes its appearance when a sizable fraction of the β-cells is in the OFF state. Using stochastic simulation techniques we show that, on reduction of the gene copy number, there is a transition from the monostable ON to the ON state in the bistable region of the parameter space. Fluctuations in the protein levels, arising due to the stochastic nature of gene expression, can give rise to transitions between the ON and OFF states. We show that as the strength of autorepression increases, the ON → OFF state transitions become less probable whereas the reverse transitions are more probable. The implications of the results in the context of the occurrence of MODY are pointed out.

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.

A technique for pole-zero placement for dual-input control systems. [computer simulation of CH-47 helicopter longitudinal dynamics

NASA Technical Reports Server (NTRS)

Reid, G. F.

1976-01-01

A technique is presented for determining state variable feedback gains that will place both the poles and zeros of a selected transfer function of a dual-input control system at pre-determined locations in the s-plane. Leverrier's algorithm is used to determine the numerator and denominator coefficients of the closed-loop transfer function as functions of the feedback gains. The values of gain that match these coefficients to those of a pre-selected model are found by solving two systems of linear simultaneous equations. The algorithm has been used in a computer simulation of the CH-47 helicopter to control longitudinal dynamics.

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.

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.

LPV H-infinity Control for the Longitudinal Dynamics of a Flexible Air-Breathing Hypersonic Vehicle

NASA Astrophysics Data System (ADS)

Hughes, Hunter Douglas

This dissertation establishes the method needed to synthesize and simulate an Hinfinity Linear Parameter-Varying (LPV) controller for a flexible air-breathing hypersonic vehicle model. A study was conducted to gain the understanding of the elastic effects on the open loop system. It was determined that three modes of vibration would be suitable for the hypersonic vehicle model. It was also discovered from the open loop study that there is strong coupling in the hypersonic vehicle states, especially between the angle of attack, pitch rate, pitch attitude, and the exible modes of the vehicle. This dissertation outlines the procedure for synthesizing a full state feedback Hinfinity LPV controller for the hypersonic vehicle. The full state feedback study looked at both velocity and altitude tracking for the exible vehicle. A parametric study was conducted on each of these controllers to see the effects of changing the number of gridding points in the parameter space and changing the parameter variation rate limits in the system on the robust performance of the controller. As a result of the parametric study, a 7 x 7 grid ranging from Mach 7 to Mach 9 in velocity and from 70,000 feet to 90,000 feet in altitude, and a parameter variation rate limit of [.5 200]T was used for both the velocity tracking and altitude tracking cases. The resulting Hinfinity robust performances were gamma = 2.2224 for the velocity tracking case and = 1:7582 for the altitude tracking case. A linear analysis was then conducted on five different selected trim points from the Hinfinity LPV controller. This was conducted for the velocity tracking and altitude tracking cases. The results of linear analysis show that there is a slight difference in the response of the Hinfinity LPV controller and the fixed point H infinity controller. For the tracking task, the Hinfinity controller responds more quickly, and has a lower Hinfinity performance value. Next, the H infinity LPV controller was simulated using the nonlinear flexible hypersonic model for both the velocity tracking and altitude tracking cases. Both of these cases were subject to a ramp input and a multi-step input both with and without perturbation in the model. The results of the simulation show that the tracking state follows the command signal successfully though the perturbed system does show some higher frequency characteristics in the non-tracking states. It was discovered that there is an issue with integral windup when switching takes place in the controller, so an algorithm was implemented to reset the integration of the error on the tracking state when the switch takes place. It was also seen that there was a decline in altitude when tracking velocity, and a large change in velocity that occurred during altitude tracking. These results lead to the decision to include a unity gain regulation state on velocity for the altitude tracking and the altitude for the velocity tracking during the output feedback control synthesis. The procedure for synthesizing an output feedback H infinity LPV controller for the hypersonic vehicle is also discussed in this dissertation. The output feedback design looked at velocity tracking and altitude tracking with rigid body motion variables for both the exible and rigid body hypersonic vehicle models. As with the full state feedback controller, a parametric study was conducted on each of these controllers to determine the number of gridding points in the parameter space and the parameter variation rate limits in the system. The parametric study reveals a 7x7 grid ranging from Mach 7 to Mach 9 in velocity and from 70,000 feet to 90,000 feet in altitude, and a parameter variation rate limit of [.1 200]T is preferable for both the velocity tracking and altitude tracking cases with both the exible and rigid body assumptions. The resulting Hinfinity robust performances were gamma = 113:2146 for the exible body velocity tracking case, gamma = 83.6931 for the rigid body velocity tracking case, gamma = 107:2043 for the exible body altitude tracking case, and gamma = 97:7403 for the rigid body altitude tracking case. A linear analysis was then conducted on five different selected trim points from the Hinfinity LPV controller. The results of this analysis show that there is a larger difference in the response of the Hinfinity LPV controller and the Hinfinity controller. For the tracking task, the Hinfinity controller responds more quickly, and has a lower Hinfinity performance value. Next, the Hinfinity LPV controller was applied to the exible nonlinear plant model. The rigid body controllers were applied to the exible plant model to see if the exible nature of the vehicle could be treated as a perturbation to the system. Additionally, there were simulations run both with and without sensor noise and parametric uncertainty. The results of simulation show that the rigid body controller is able to successfully apply to the exible body model for the velocity tracking case, but is unable to stabilize the altitude tracking case. It was also seen that the system is able to track the command signal while minimizing the variations seen in the altitude for the velocity tracking case and in the velocity during the altitude tracking case. Additionally, there was no obvious effect of perturbations in the system on the tracking state or secondary regulation state. There were high frequency responses associated with the other perturbed states.

Nonlinear fractional order proportion-integral-derivative active disturbance rejection control method design for hypersonic vehicle attitude control

NASA Astrophysics Data System (ADS)

Song, Jia; Wang, Lun; Cai, Guobiao; Qi, Xiaoqiang

2015-06-01

Near space hypersonic vehicle model is nonlinear, multivariable and couples in the reentry process, which are challenging for the controller design. In this paper, a nonlinear fractional order proportion integral derivative (NFOPIλDμ) active disturbance rejection control (ADRC) strategy based on a natural selection particle swarm (NSPSO) algorithm is proposed for the hypersonic vehicle flight control. The NFOPIλDμ ADRC method consists of a tracking-differentiator (TD), an NFOPIλDμ controller and an extended state observer (ESO). The NFOPIλDμ controller designed by combining an FOPIλDμ method and a nonlinear states error feedback control law (NLSEF) is to overcome concussion caused by the NLSEF and conversely compensate the insufficiency for relatively simple and rough signal processing caused by the FOPIλDμ method. The TD is applied to coordinate the contradiction between rapidity and overshoot. By attributing all uncertain factors to unknown disturbances, the ESO can achieve dynamic feedback compensation for these disturbances and thus reduce their effects. Simulation results show that the NFOPIλDμ ADRC method can make the hypersonic vehicle six-degree-of-freedom nonlinear model track desired nominal signals accurately and fast, has good stability, dynamic properties and strong robustness against external environmental disturbances.

Learning from ISS-modular adaptive NN control of nonlinear strict-feedback systems.

PubMed

Wang, Cong; Wang, Min; Liu, Tengfei; Hill, David J

2012-10-01

This paper studies learning from adaptive neural control (ANC) for a class of nonlinear strict-feedback systems with unknown affine terms. To achieve the purpose of learning, a simple input-to-state stability (ISS) modular ANC method is first presented to ensure the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in finite time. Subsequently, it is proven that learning with the proposed stable ISS-modular ANC can be achieved. The cascade structure and unknown affine terms of the considered systems make it very difficult to achieve learning using existing methods. To overcome these difficulties, the stable closed-loop system in the control process is decomposed into a series of linear time-varying (LTV) perturbed subsystems with the appropriate state transformation. Using a recursive design, the partial persistent excitation condition for the radial basis function neural network (NN) is established, which guarantees exponential stability of LTV perturbed subsystems. Consequently, accurate approximation of the closed-loop system dynamics is achieved in a local region along recurrent orbits of closed-loop signals, and learning is implemented during a closed-loop feedback control process. The learned knowledge is reused to achieve stability and an improved performance, thereby avoiding the tremendous repeated training process of NNs. Simulation studies are given to demonstrate the effectiveness of the proposed method.

Analysis and Experimentation of Control Strategies for Underactuated Spacecraft

DTIC Science & Technology

2009-09-01

control techniques that provide time -invariant global asymptotic stability of the fully actuated spacecraft system of equations. Although these control ...momentum wheel actuators in finite time under the restriction that the total angular momentum vector of the system is zero. This control methodology...can be stabilizable to an arbitrarily small region about the equilibrium of the system via time -invariant smooth state feedback control

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.

Global finite-time attitude stabilization for rigid spacecraft in the exponential coordinates

NASA Astrophysics Data System (ADS)

Shi, Xiao-Ning; Zhou, Zhi-Gang; Zhou, Di

2018-06-01

This paper addresses the global finite-time attitude stabilisation problem on the special orthogonal group (SO(3)) for a rigid spacecraft via homogeneous feedback approach. Considering the topological and geometric properties of SO(3), the logarithm map is utilised to transform the stabilisation problem on SO(3) into the one on its associated Lie algebra (?). A model-independent discontinuous state feedback plus dynamics compensation scheme is constructed to achieve the global finite-time attitude stabilisation in a coordinate-invariant way. In addition, to address the absence of angular velocity measurements, a sliding mode observer is proposed to reconstruct the unknown angular velocity information within finite time. Then, an observer-based finite-time output feedback control strategy is obtained. Numerical simulations are finally performed to demonstrate the effectiveness of the proposed finite-time controllers.

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.

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.

Oscillation control system for electric motor drive

DOEpatents

Slicker, J.M.; Sereshteh, A.

1988-08-30

A feedback system for controlling mechanical oscillations in the torsionally complaint drive train of an electric or other vehicle. Motor speed is converted in a processor to estimate state signals in which a plant model which are used to electronically modify the torque commands applied to the motor. 5 figs.

Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle.

PubMed

Xu, Bin; Yang, Chenguang; Pan, Yongping

2015-10-01

This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an adaptive neural controller in the neural approximation domain, together with the robust controller that pulls the transient states back into the neural approximation domain from the outside. In comparison with the conventional control techniques, which could only achieve semiglobally uniformly ultimately bounded stability, the proposed control scheme guarantees all the signals in the closed-loop system are globally uniformly ultimately bounded, such that the conventional constraints on initial conditions of the neural control system can be relaxed. The simulation studies of hypersonic flight vehicle (HFV) are performed to demonstrate the effectiveness of the proposed global neural DSC design.

Adaptive output feedback NN control of a class of discrete-time MIMO nonlinear systems with unknown control directions.

PubMed

Li, Yanan; Yang, Chenguang; Ge, Shuzhi Sam; Lee, Tong Heng

2011-04-01

In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multiinput-multioutput nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. These systems are of couplings in every equation of each subsystem, and different subsystems may have different orders. To avoid the noncausal problem in the control design, the system is transformed into a predictor form by rigorous derivation. By exploring the properties of the block triangular form, implicit controls are developed for each subsystem such that the couplings of inputs and states among subsystems have been completely decoupled. The radial basis function NN is employed to approximate the unknown control. Each subsystem achieves a semiglobal uniformly ultimately bounded stability with the proposed control, and simulation results are presented to demonstrate its efficiency.

Control-oriented reduced order modeling of dipteran flapping flight

NASA Astrophysics Data System (ADS)

Faruque, Imraan

Flying insects achieve flight stabilization and control in a manner that requires only small, specialized neural structures to perform the essential components of sensing and feedback, achieving unparalleled levels of robust aerobatic flight on limited computational resources. An engineering mechanism to replicate these control strategies could provide a dramatic increase in the mobility of small scale aerial robotics, but a formal investigation has not yet yielded tools that both quantitatively and intuitively explain flapping wing flight as an "input-output" relationship. This work uses experimental and simulated measurements of insect flight to create reduced order flight dynamics models. The framework presented here creates models that are relevant for the study of control properties. The work begins with automated measurement of insect wing motions in free flight, which are then used to calculate flight forces via an empirically-derived aerodynamics model. When paired with rigid body dynamics and experimentally measured state feedback, both the bare airframe and closed loop systems may be analyzed using frequency domain system identification. Flight dynamics models describing maneuvering about hover and cruise conditions are presented for example fruit flies (Drosophila melanogaster) and blowflies (Calliphorids). The results show that biologically measured feedback paths are appropriate for flight stabilization and sexual dimorphism is only a minor factor in flight dynamics. A method of ranking kinematic control inputs to maximize maneuverability is also presented, showing that the volume of reachable configurations in state space can be dramatically increased due to appropriate choice of kinematic inputs.

Single link flexible beam testbed project. Thesis

NASA Technical Reports Server (NTRS)

Hughes, Declan

1992-01-01

This thesis describes the single link flexible beam testbed at the CLaMS laboratory in terms of its hardware, software, and linear model, and presents two controllers, each including a hub angle proportional-derivative (PD) feedback compensator and one augmented by a second static gain full state feedback loop, based upon a synthesized strictly positive real (SPR) output, that increases specific flexible mode pole damping ratios w.r.t the PD only case and hence reduces unwanted residual oscillation effects. Restricting full state feedback gains so as to produce a SPR open loop transfer function ensures that the associated compensator has an infinite gain margin and a phase margin of at least (-90, 90) degrees. Both experimental and simulation data are evaluated in order to compare some different observer performance when applied to the real testbed and to the linear model when uncompensated flexible modes are included.

Disturbance maintains alternative biome states.

PubMed

Dantas, Vinícius de L; Hirota, Marina; Oliveira, Rafael S; Pausas, Juli G

2016-01-01

Understanding the mechanisms controlling the distribution of biomes remains a challenge. Although tropical biome distribution has traditionally been explained by climate and soil, contrasting vegetation types often occur as mosaics with sharp boundaries under very similar environmental conditions. While evidence suggests that these biomes are alternative states, empirical broad-scale support to this hypothesis is still lacking. Using community-level field data and a novel resource-niche overlap approach, we show that, for a wide range of environmental conditions, fire feedbacks maintain savannas and forests as alternative biome states in both the Neotropics and the Afrotropics. In addition, wooded grasslands and savannas occurred as alternative grassy states in the Afrotropics, depending on the relative importance of fire and herbivory feedbacks. These results are consistent with landscape scale evidence and suggest that disturbance is a general factor driving and maintaining alternative biome states and vegetation mosaics in the tropics. © 2015 John Wiley & Sons Ltd/CNRS.

Neural substrates of visuomotor learning based on improved feedback control and prediction

PubMed Central

Grafton, Scott T.; Schmitt, Paul; Horn, John Van; Diedrichsen, Jörn

2008-01-01

Motor skills emerge from learning feedforward commands as well as improvements in feedback control. These two components of learning were investigated in a compensatory visuomotor tracking task on a trial-by-trial basis. Between trial learning was characterized with a state-space model to provide smoothed estimates of feedforward and feedback learning, separable from random fluctuations in motor performance and error. The resultant parameters were correlated with brain activity using magnetic resonance imaging. Learning related to the generation of a feedforward command correlated with activity in dorsal premotor cortex, inferior parietal lobule, supplementary motor area and cingulate motor area, supporting a role of these areas in retrieving and executing a predictive motor command. Modulation of feedback control was associated with activity in bilateral posterior superior parietal lobule as well as right ventral premotor cortex. Performance error correlated with activity in a widespread cortical and subcortical network including bilateral parietal, premotor and rostral anterior cingulate cortex as well as the cerebellar cortex. Finally, trial-by-trial changes of kinematics, as measured by mean absolute hand acceleration, correlated with activity in motor cortex and anterior cerebellum. The results demonstrate that incremental, learning dependent changes can be modeled on a trial-by-trial basis and neural substrates for feedforward control of novel motor programs are localized to secondary motor areas. PMID:18032069

Design Of Combined Stochastic Feedforward/Feedback Control

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1989-01-01

Methodology accommodates variety of control structures and design techniques. In methodology for combined stochastic feedforward/feedback control, main objectives of feedforward and feedback control laws seen clearly. Inclusion of error-integral feedback, dynamic compensation, rate-command control structure, and like integral element of methodology. Another advantage of methodology flexibility to develop variety of techniques for design of feedback control with arbitrary structures to obtain feedback controller: includes stochastic output feedback, multiconfiguration control, decentralized control, or frequency and classical control methods. Control modes of system include capture and tracking of localizer and glideslope, crab, decrab, and flare. By use of recommended incremental implementation, control laws simulated on digital computer and connected with nonlinear digital simulation of aircraft and its systems.

A flatness-based control approach to drug infusion for cardiac function regulation

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Zervos, Nikolaos; Melkikh, Alexey

2016-12-01

A new control method based on differential flatness theory is developed in this article, aiming at solving the problem of regulation of haemodynamic parameters, Actually control of the cardiac output (volume of blood pumped out by heart per unit of time) and of the arterial blood pressure is achieved through the administered infusion of cardiovascular drugs, such as dopamine and sodium nitroprusside. Time delays between the control inputs and the system's outputs are taken into account. Using the principle of dynamic extension, which means that by considering certain control inputs and their derivatives as additional state variables, a state-space description for the heart's function is obtained. It is proven that the dynamic model of the heart is a differentially flat one. This enables its transformation into a linear canonical and decoupled form, for which the design of a stabilizing feedback controller becomes possible. The proposed feedback controller is of proven stability and assures fast and accurate tracking of the reference setpoints by the outputs of the heart's dynamic model. Moreover, by using a Kalman Filter-based disturbances' estimator, it becomes possible to estimate in real-time and compensate for the model uncertainty and external perturbation inputs that affect the heart's model.

Real-time control of walking using recordings from dorsal root ganglia

NASA Astrophysics Data System (ADS)

Holinski, B. J.; Everaert, D. G.; Mushahwar, V. K.; Stein, R. B.

2013-10-01

Objective. The goal of this study was to decode sensory information from the dorsal root ganglia (DRG) in real time, and to use this information to adapt the control of unilateral stepping with a state-based control algorithm consisting of both feed-forward and feedback components. Approach. In five anesthetized cats, hind limb stepping on a walkway or treadmill was produced by patterned electrical stimulation of the spinal cord through implanted microwire arrays, while neuronal activity was recorded from the DRG. Different parameters, including distance and tilt of the vector between hip and limb endpoint, integrated gyroscope and ground reaction force were modelled from recorded neural firing rates. These models were then used for closed-loop feedback. Main results. Overall, firing-rate-based predictions of kinematic sensors (limb endpoint, integrated gyroscope) were the most accurate with variance accounted for >60% on average. Force prediction had the lowest prediction accuracy (48 ± 13%) but produced the greatest percentage of successful rule activations (96.3%) for stepping under closed-loop feedback control. The prediction of all sensor modalities degraded over time, with the exception of tilt. Significance. Sensory feedback from moving limbs would be a desirable component of any neuroprosthetic device designed to restore walking in people after a spinal cord injury. This study provides a proof-of-principle that real-time feedback from the DRG is possible and could form part of a fully implantable neuroprosthetic device with further development.

Real-time control of walking using recordings from dorsal root ganglia

PubMed Central

Holinski, B J; Everaert, D G; Mushahwar, V K; Stein, R B

2013-01-01

Objective The goal of this study was to decode sensory information from the dorsal root ganglia (DRG) in real time, and to use this information to adapt the control of unilateral stepping with a state-based control algorithm consisting of both feed-forward and feedback components. Approach In five anesthetized cats, hind limb stepping on a walkway or treadmill was produced by patterned electrical stimulation of the spinal cord through implanted microwire arrays, while neuronal activity was recorded from the dorsal root ganglia. Different parameters, including distance and tilt of the vector between hip and limb endpoint, integrated gyroscope and ground reaction force were modeled from recorded neural firing rates. These models were then used for closed-loop feedback. Main Results Overall, firing-rate based predictions of kinematic sensors (limb endpoint, integrated gyroscope) were the most accurate with variance accounted for >60% on average. Force prediction had the lowest prediction accuracy (48±13%) but produced the greatest percentage of successful rule activations (96.3%) for stepping under closed-loop feedback control. The prediction of all sensor modalities degraded over time, with the exception of tilt. Significance Sensory feedback from moving limbs would be a desirable component of any neuroprosthetic device designed to restore walking in people after a spinal cord injury. This study provides a proof-of-principle that real-time feedback from the DRG is possible and could form part of a fully implantable neuroprosthetic device with further development. PMID:23928579

Voluntarily controlled but not merely observed visual feedback affects postural sway

PubMed Central

Asai, Tomohisa; Hiromitsu, Kentaro; Imamizu, Hiroshi

2018-01-01

Online stabilization of human standing posture utilizes multisensory afferences (e.g., vision). Whereas visual feedback of spontaneous postural sway can stabilize postural control especially when observers concentrate on their body and intend to minimize postural sway, the effect of intentional control of visual feedback on postural sway itself remains unclear. This study assessed quiet standing posture in healthy adults voluntarily controlling or merely observing visual feedback. The visual feedback (moving square) had either low or high gain and was either horizontally flipped or not. Participants in the voluntary-control group were instructed to minimize their postural sway while voluntarily controlling visual feedback, whereas those in the observation group were instructed to minimize their postural sway while merely observing visual feedback. As a result, magnified and flipped visual feedback increased postural sway only in the voluntary-control group. Furthermore, regardless of the instructions and feedback manipulations, the experienced sense of control over visual feedback positively correlated with the magnitude of postural sway. We suggest that voluntarily controlled, but not merely observed, visual feedback is incorporated into the feedback control system for posture and begins to affect postural sway. PMID:29682421

Equicontrollability and the model following problem

NASA Technical Reports Server (NTRS)

Curran, R. T.

1971-01-01

Equicontrollability and its application to the linear time-invariant model-following problem are discussed. The problem is presented in the form of two systems, the plant and the model. The requirement is to find a controller to apply to the plant so that the resultant compensated plant behaves, in an input-output sense, the same as the model. All systems are assumed to be linear and time-invariant. The basic approach is to find suitable equicontrollable realizations of the plant and model and to utilize feedback so as to produce a controller of minimal state dimension. The concept of equicontrollability is a generalization of control canonical (phase variable) form applied to multivariable systems. It allows one to visualize clearly the effects of feedback and to pinpoint the parameters of a multivariable system which are invariant under feedback. The basic contributions are the development of equicontrollable form; solution of the model-following problem in an entirely algorithmic way, suitable for computer programming; and resolution of questions on system decoupling.

Coordination of the Arc Regulatory System and Pheromone-Mediated Positive Feedback in Controlling the Vibrio fischeri lux Operon

PubMed Central

Septer, Alecia N.; Stabb, Eric V.

2012-01-01

Bacterial pheromone signaling is often governed both by environmentally responsive regulators and by positive feedback. This regulatory combination has the potential to coordinate a group response among distinct subpopulations that perceive key environmental stimuli differently. We have explored the interplay between an environmentally responsive regulator and pheromone-mediated positive feedback in intercellular signaling by Vibrio fischeri ES114, a bioluminescent bacterium that colonizes the squid Euprymna scolopes. Bioluminescence in ES114 is controlled in part by N-(3-oxohexanoyl)-L-homoserine lactone (3OC6), a pheromone produced by LuxI that together with LuxR activates transcription of the luxICDABEG operon, initiating a positive feedback loop and inducing luminescence. The lux operon is also regulated by environmentally responsive regulators, including the redox-responsive ArcA/ArcB system, which directly represses lux in culture. Here we show that inactivating arcA leads to increased 3OC6 accumulation to initiate positive feedback. In the absence of positive feedback, arcA-mediated control of luminescence was only ∼2-fold, but luxI-dependent positive feedback contributed more than 100 fold to the net induction of luminescence in the arcA mutant. Consistent with this overriding importance of positive feedback, 3OC6 produced by the arcA mutant induced luminescence in nearby wild-type cells, overcoming their ArcA repression of lux. Similarly, we found that artificially inducing ArcA could effectively repress luminescence before, but not after, positive feedback was initiated. Finally, we show that 3OC6 produced by a subpopulation of symbiotic cells can induce luminescence in other cells co-colonizing the host. Our results suggest that even transient loss of ArcA-mediated regulation in a sub-population of cells can induce luminescence in a wider community. Moreover, they indicate that 3OC6 can communicate information about both cell density and the state of ArcA/ArcB. PMID:23152924

Prescribed-performance fault-tolerant control for feedback linearisable systems with an aircraft application

NASA Astrophysics Data System (ADS)

Gao, Gang; Wang, Jinzhi; Wang, Xianghua

2017-05-01

This paper investigates fault-tolerant control (FTC) for feedback linearisable systems (FLSs) and its application to an aircraft. To ensure desired transient and steady-state behaviours of the tracking error under actuator faults, the dynamic effect caused by the actuator failures on the error dynamics of a transformed model is analysed, and three control strategies are designed. The first FTC strategy is proposed as a robust controller, which relies on the explicit information about several parameters of the actuator faults. To eliminate the need for these parameters and the input chattering phenomenon, the robust control law is later combined with the adaptive technique to generate the adaptive FTC law. Next, the adaptive control law is further improved to achieve the prescribed performance under more severe input disturbance. Finally, the proposed control laws are applied to an air-breathing hypersonic vehicle (AHV) subject to actuator failures, which confirms the effectiveness of the proposed strategies.

Advanced Shock Position Control for Mode Transition in a Turbine Based Combined Cycle Engine Inlet Model

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.; Stueber, Thomas J.

2013-01-01

A dual flow-path inlet system is being tested to evaluate methodologies for a Turbine Based Combined Cycle (TBCC) propulsion system to perform a controlled inlet mode transition. Prior to experimental testing, simulation models are used to test, debug, and validate potential control algorithms. One simulation package being used for testing is the High Mach Transient Engine Cycle Code simulation, known as HiTECC. This paper discusses the closed loop control system, which utilizes a shock location sensor to improve inlet performance and operability. Even though the shock location feedback has a coarse resolution, the feedback allows for a reduction in steady state error and, in some cases, better performance than with previous proposed pressure ratio based methods. This paper demonstrates the design and benefit with the implementation of a proportional-integral controller, an H-Infinity based controller, and a disturbance observer based controller.

Active Control of Thermal Convection in a Rectangular Loop by Changing its Spatial Orientation

NASA Astrophysics Data System (ADS)

Bratsun, Dmitry A.; Krasnyakov, Ivan V.; Zyuzgin, Alexey V.

2018-02-01

The problem of the automatic control of the fluid flow in a rectangular convective loop heated from below is studied theoretically and experimentally. The control is performed by using a feedback subsystem which changes the convection regimes by introducing small discrete changes in the spatial orientation of the loop with respect to gravity. We focus on effects that arise when the feedback controller operates with an unavoidable time delay, which is cause by the thermal inertia of the medium. The mathematical model of the phenomenon is developed. The dynamic regimes of the convection in the thermosyphon loop under control are studied. It is shown that the proposed control method can successfully stabilize not only a no-motion state of the fluid, but also time-dependent modes of convection including the irregular fluid flow at high values of the Rayleigh number. It is shown that the excessive gain of the proportional feedback can result in oscillations in the loop orientation exciting the unsteady convection modes. The comparison of the experimental data obtained for dielectric oil and dodecane with theory is given, and their good agreement is demonstrated.

Active Control of Thermal Convection in a Rectangular Loop by Changing its Spatial Orientation

NASA Astrophysics Data System (ADS)

Bratsun, Dmitry A.; Krasnyakov, Ivan V.; Zyuzgin, Alexey V.

2017-12-01

The problem of the automatic control of the fluid flow in a rectangular convective loop heated from below is studied theoretically and experimentally. The control is performed by using a feedback subsystem which changes the convection regimes by introducing small discrete changes in the spatial orientation of the loop with respect to gravity. We focus on effects that arise when the feedback controller operates with an unavoidable time delay, which is cause by the thermal inertia of the medium. The mathematical model of the phenomenon is developed. The dynamic regimes of the convection in the thermosyphon loop under control are studied. It is shown that the proposed control method can successfully stabilize not only a no-motion state of the fluid, but also time-dependent modes of convection including the irregular fluid flow at high values of the Rayleigh number. It is shown that the excessive gain of the proportional feedback can result in oscillations in the loop orientation exciting the unsteady convection modes. The comparison of the experimental data obtained for dielectric oil and dodecane with theory is given, and their good agreement is demonstrated.

Command and control interfaces for advanced neuroprosthetic applications.

PubMed

Scott, T R; Haugland, M

2001-10-01

Command and control interfaces permit the intention and situation of the user to influence the operation of the neural prosthesis. The wishes of the user are communicated via command interfaces to the neural prosthesis and the situation of the user by feedback control interfaces. Both these interfaces have been reviewed separately and are discussed in light of the current state of the art and projections for the future. It is apparent that as system functional complexity increases, the need for simpler command interfaces will increase. Such systems will demand more information to function effectively in order not to unreasonably increase user attention overhead. This will increase the need for bioelectric and biomechanical signals in a comprehensible form via elegant feedback control interfaces. Implementing such systems will also increase the computational demand on such neural prostheses.

Development of a two-dimensional skin friction balance nulling circuit using multivariable control theory

NASA Technical Reports Server (NTRS)

Tripp, John S.; Patek, Stephen D.

1988-01-01

Measurement of planar skin friction forces in aerodynamic testing currently requires installation of two perpendicularly mounted, single-axis balances; consequently, force components must be sensed at two distinct locations. A two-axis instrument developed at the Langley Research Center to overcome this disadvantage allows measurement of a two-dimensional force at one location. This paper describes a feedback-controlled nulling circuit developed for the NASA two-axis balance which, without external compensation, is inherently unstable because of its low friction mechanical design. Linear multivariable control theory is applied to an experimentally validated mathematical model of the balance to synthesize a state-variable feedback control law. Pole placement techniques and computer simulation studies are employed to select eigenvalues which provide ideal transient response with decoupled sensing dynamics.

Exploring quantum thermodynamics in continuous measurement of superconducting qubits

NASA Astrophysics Data System (ADS)

Murch, Kater

The extension of thermodynamics into the realm of quantum mechanics, where quantum fluctuations dominate and systems need not occupy definite states, poses unique challenges. Superconducting quantum circuits offer exquisite control over the environment of simple quantum systems allowing the exploration of thermodynamics at the quantum level through measurement and feedback control. We use a superconducting transmon qubit that is resonantly coupled to a waveguide cavity as an effectively one-dimensional quantum emitter. By driving the emitter and detecting the fluorescence with a near-quantum-limited Josephson parametric amplifier, we track the evolution of the quantum state and characterize the work and heat along single quantum trajectories. By using quantum feedback control to compensate for heat exchanged with the emitter's environment we are able to extract the work statistics associated with the quantum evolution and examine fundamental fluctuation theorems in non-equilibrium thermodynamics. This work was supported by the Alfred P. Sloan Foundation, the National Science Foundation, and the Office of Naval Research.

Analysis of Control Strategies for Aircraft Flight Upset Recovery

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Cox, David E.; Muri, Daniel G.

2012-01-01

This paper proposes a framework for studying the ability of a control strategy, consisting of a control law and a command law, to recover an aircraft from ight conditions that may extend beyond the normal ight envelope. This study was carried out (i) by evaluating time responses of particular ight upsets, (ii) by evaluating local stability over an equilibrium manifold that included stall, and (iii) by bounding the set in the state space from where the vehicle can be safely own to wings-level ight. These states comprise what will be called the safely recoverable ight envelope (SRFE), which is a set containing the aircraft states from where a control strategy can safely stabilize the aircraft. By safe recovery it is implied that the tran- sient response stays between prescribed limits before converging to a steady horizontal ight. The calculation of the SRFE bounds yields the worst-case initial state corresponding to each control strategy. This information is used to compare alternative recovery strategies, determine their strengths and limitations, and identify the most e ective strategy. In regard to the control law, the authors developed feedback feedforward laws based on the gain scheduling of multivariable controllers. In regard to the command law, which is the mechanism governing the exogenous signals driving the feed- forward component of the controller, we developed laws with a feedback structure that combines local stability and transient response considera- tions. The upset recovery of the Generic Transport Model, a sub-scale twin-engine jet vehicle developed by NASA Langley Research Center, is used as a case study.

Three-terminal graphene single-electron transistor fabricated using feedback-controlled electroburning

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

Puczkarski, Paweł; Gehring, Pascal, E-mail: pascal.gehring@materials.ox.ac.uk; Lau, Chit S.

2015-09-28

We report room-temperature Coulomb blockade in a single layer graphene three-terminal single-electron transistor fabricated using feedback-controlled electroburning. The small separation between the side gate electrode and the graphene quantum dot results in a gate coupling up to 3 times larger compared to the value found for the back gate electrode. This allows for an effective tuning between the conductive and Coulomb blocked state using a small side gate voltage of about 1 V. The technique can potentially be used in the future to fabricate all-graphene based room temperature single-electron transistors or three terminal single molecule transistors with enhanced gate coupling.

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.

Loss-of-Control-Inhibitor Systems for Aircraft

NASA Technical Reports Server (NTRS)

AHarrah, Ralph C.

2007-01-01

Systems to provide improved tactile feedback to aircraft pilots are being developed to help the pilots maintain harmony between their control actions and the positions of aircraft control surfaces, thereby helping to prevent loss of control. A system of this type, denoted a loss-of-control-inhibitor system (LOCIS) can be implemented as a relatively simple addition to almost any pre-existing flight-control system. The LOCIS concept offers at least a partial solution to the problem of (1) keeping a pilot aware of the state of the control system and the aircraft and (2) maintaining sufficient control under conditions that, as described below, have been known to lead to loss of control. Current commercial aircraft exhibit uneven responses of primary flight-control surfaces to aggressive pilot control commands, leading to deterioration of pilots ability to control their aircraft. In severe cases, this phenomenon can result in loss of control and consequent loss of aircraft. For an older aircraft equipped with a purely mechanical control system, the loss of harmony between a pilot s command action and the control- surface response can be attributed to compliance in the control system (caused, for example, by stretching of control cables, flexing of push rods, or servo-valve distortion). In a newer aircraft equipped with a fly-by-wire control system, the major contributions to loss of harmony between the pilot and the control surfaces are delays attributable to computer cycle time, control shaping, filtering, aliasing, servo-valve distortion, and actuator rate limiting. In addition, a fly-by-wire control system provides no tactile feedback that would enable the pilot to sense such features of the control state as surface flutter, surface jam, position limiting, actuator rate limiting, and control limiting imposed by the aircraft operational envelope. Hence, for example, when a pilot is involved in aggressive closed-loop maneuvering, as when encountering a wake-vortex upset on final landing approach, the control-surface delay can lead to loss of control. Aggressive piloting can be triggered and exacerbated by control-system anomalies, which the pilot cannot diagnose because of the lack of symptoms caused by the absence of feedback through the controls. The purpose served by a LOCIS is to counteract these adverse effects by providing real-time feedback that notifies the pilot that the aircraft is tending to lag the pilot s commands. A LOCIS (see figure) includes cockpit control input-position sensors, control-surface output-position sensors, variable dampers (for example, shock absorbers containing magneto-rheological fluids such that the damping forces can be varied within times of the order of milliseconds by varying applied magnetic fields) attached to the cockpit control levers, electromagnet coils to apply the magnetic fields, and feedback control circuits to drive the electromagnet coils. The feedback control gains are chosen so that the current applied to each electromagnet coil results in a damping force that increases in a suitable nonlinear manner (e.g., exponentially) with the difference between the actual and commanded positions of the affected control surface. The increasing damping force both alerts the pilot to the onset of a potentially dangerous situation and resists the pilot s effort to command a control surface to change position at an excessive rate

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.

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

The impact of problem solving strategy with online feedback on students’ conceptual understanding

NASA Astrophysics Data System (ADS)

Pratiwi, H. Y.; Winarko, W.; Ayu, H. D.

2018-04-01

The study aimed to determine the impact of the implementation of problem solving strategy with online feedback towards the students’ concept understanding. This study used quasi experimental design with post-test only control design. The participants were all Physics Education students of Kanjuruhan University year 2015. Then, they were divided into two different groups; 30 students belong to experiment class and the remaining 30 students belong to class of control. The students’ concept understanding was measured by the concept understanding test on multiple integral lesson. The result of the concept understanding test was analyzed by prerequisite test and stated to be normal and homogenic distributed, then the hypothesis was examined by T-test. The result of the study shows that there is difference in the concept understanding between experiment class and control class. Next, the result also shows that the students’ concept understanding which was taught using problem solving strategy with online feedback was higher than those using conventional learning; with average score of 72,10 for experiment class and 52,27 for control class.

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.

Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior.

PubMed

Bell, Jennifer L; Taylor, Matthew A; Chen, Guang-Xiang; Kirk, Rachel D; Leatherman, Erin R

2017-02-01

Roadway incidents are the leading cause of work-related death in the United States. The objective of this research was to evaluate whether two types of feedback from a commercially available in-vehicle monitoring system (IVMS) would reduce the incidence of risky driving behaviors in drivers from two companies. IVMS were installed in 315 vehicles representing the industries of local truck transportation and oil and gas support operations, and data were collected over an approximate two-year period in intervention and control groups. In one period, intervention group drivers were given feedback from in-cab warning lights from an IVMS that indicated occurrence of harsh vehicle maneuvers. In another period, intervention group drivers viewed video recordings of their risky driving behaviors with supervisors, and were coached by supervisors on safe driving practices. Risky driving behaviors declined significantly more during the period with coaching plus instant feedback with lights in comparison to the period with lights-only feedback (ORadj=0.61 95% CI 0.43-0.86; Holm-adjusted p=0.035) and the control group (ORadj=0.52 95% CI 0.33-0.82; Holm-adjusted p=0.032). Lights-only feedback was not found to be significantly different than the control group's decline from baseline (ORadj=0.86 95% CI 0.51-1.43; Holm-adjusted p>0.05). The largest decline in the rate of risky driving behaviors occurred when feedback included both supervisory coaching and lights. Supervisory coaching is an effective form of feedback to improve driving habits in the workplace. The potential advantages and limitations of this IVMS-based intervention program are discussed. Published by Elsevier Ltd.

Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior

PubMed Central

Bell, Jennifer L.; Taylor, Matthew A.; Chen, Guang-Xiang; Kirk, Rachel D.; Leatherman, Erin R.

2017-01-01

Problem Roadway incidents are the leading cause of work-related death in the United States. Methods The objective of this research was to evaluate whether two types of feedback from a commercially available in-vehicle monitoring system (IVMS) would reduce the incidence of risky driving behaviors in drivers from two companies. IVMS were installed in 315 vehicles representing the industries of local truck transportation and oil and gas support operations, and data were collected over an approximate two-year period in intervention and control groups. In one period, intervention group drivers were given feedback from in-cab warning lights from an IVMS that indicated occurrence of harsh vehicle maneuvers. In another period, intervention group drivers viewed video recordings of their risky driving behaviors with supervisors, and were coached by supervisors on safe driving practices. Results Risky driving behaviors declined significantly more during the period with coaching plus instant feedback with lights in comparison to the period with lights-only feedback (ORadj = 0.61 95% CI 0.43–0.86; Holm-adjusted p = 0.035) and the control group (ORadj = 0.52 95% CI 0.33–0.82; Holm-adjusted p = 0.032). Lights-only feedback was not found to be significantly different than the control group's decline from baseline (ORadj = 0.86 95% CI 0.51–1.43; Holm-adjusted p > 0.05). Conclusions The largest decline in the rate of risky driving behaviors occurred when feedback included both supervisory coaching and lights. Practical applications Supervisory coaching is an effective form of feedback to improve driving habits in the workplace. The potential advantages and limitations of this IVMS-based intervention program are discussed. PMID:28160807

The effect of emotion on keystroke: an experimental study using facial feedback hypothesis.

PubMed

Tsui, Wei-Hsuan; Lee, Poming; Hsiao, Tzu-Chien

2013-01-01

The automatic emotion recognition technology is an important part of building intelligent systems to prevent the computers acting inappropriately. A novel approach for recognizing emotional state by their keystroke typing patterns on a standard keyboard was developed in recent years. However, there was very limited investigation about the phenomenon itself in the previous literatures. Hence, in our study, we conduct a controlled experiment to collect subjects' keystroke data in the different emotional states induced by facial feedback. We examine the difference of the keystroke data between positive and negative emotional states. The results prove the significance in the differences in the typing patterns under positive and negative emotions for all subjects. Our study provides an evidence for the reasonability about developing the technique of emotion recognition by keystroke.

A boundary PDE feedback control approach for the stabilization of mortgage price dynamics

NASA Astrophysics Data System (ADS)

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

2017-11-01

Several transactions taking place in financial markets are dependent on the pricing of mortgages (loans for the purchase of residences, land or farms). In this article, a method for stabilization of mortgage price dynamics is developed. It is considered that mortgage prices follow a PDE model which is equivalent to a multi-asset Black-Scholes PDE. Actually it is a diffusion process evolving in a 2D assets space, where the first asset is the house price and the second asset is the interest rate. By applying semi-discretization and a finite differences scheme this multi-asset PDE is transformed into a state-space model consisting of ordinary nonlinear differential equations. For the local subsystems, into which the mortgage PDE is decomposed, it becomes possible to apply boundary-based feedback control. The controller design proceeds by showing that the state-space model of the mortgage price PDE stands for a differentially flat system. Next, for each subsystem which is related to a nonlinear ODE, a virtual control input is computed, that can invert the subsystem's dynamics and can eliminate the subsystem's tracking error. From the last row of the state-space description, the control input (boundary condition) that is actually applied to the multi-factor mortgage price PDE system is found. This control input contains recursively all virtual control inputs which were computed for the individual ODE subsystems associated with the previous rows of the state-space equation. Thus, by tracing the rows of the state-space model backwards, at each iteration of the control algorithm, one can finally obtain the control input that should be applied to the mortgage price PDE system so as to assure that all its state variables will converge to the desirable setpoints. By showing the feasibility of such a control method it is also proven that through selected modification of the PDE boundary conditions the price of the mortgage can be made to converge and stabilize at specific reference values.

Adaptive Fuzzy Control Design for Stochastic Nonlinear Switched Systems With Arbitrary Switchings and Unmodeled Dynamics.

PubMed

Li, Yongming; Sui, Shuai; Tong, Shaocheng

2017-02-01

This paper deals with the problem of adaptive fuzzy output feedback control for a class of stochastic nonlinear switched systems. The controlled system in this paper possesses unmeasured states, completely unknown nonlinear system functions, unmodeled dynamics, and arbitrary switchings. A state observer which does not depend on the switching signal is constructed to tackle the unmeasured states. Fuzzy logic systems are employed to identify the completely unknown nonlinear system functions. Based on the common Lyapunov stability theory and stochastic small-gain theorem, a new robust adaptive fuzzy backstepping stabilization control strategy is developed. The stability of the closed-loop system on input-state-practically stable in probability is proved. The simulation results are given to verify the efficiency of the proposed fuzzy adaptive control scheme.

Effective Control of Computationally Simulated Wing Rock in Subsonic Flow

NASA Technical Reports Server (NTRS)

Kandil, Osama A.; Menzies, Margaret A.

1997-01-01

The unsteady compressible, full Navier-Stokes (NS) equations and the Euler equations of rigid-body dynamics are sequentially solved to simulate the delta wing rock phenomenon. The NS equations are solved time accurately, using the implicit, upwind, Roe flux-difference splitting, finite-volume scheme. The rigid-body dynamics equations are solved using a four-stage Runge-Kutta scheme. Once the wing reaches the limit-cycle response, an active control model using a mass injection system is applied from the wing surface to suppress the limit-cycle oscillation. The active control model is based on state feedback and the control law is established using pole placement techniques. The control law is based on the feedback of two states: the roll-angle and roll velocity. The primary model of the computational applications consists of a 80 deg swept, sharp edged, delta wing at 30 deg angle of attack in a freestream of Mach number 0.1 and Reynolds number of 0.4 x 10(exp 6). With a limit-cycle roll amplitude of 41.1 deg, the control model is applied, and the results show that within one and one half cycles of oscillation, the wing roll amplitude and velocity are brought to zero.

Design and test of a high power electromechanical actuator for thrust vector control

NASA Technical Reports Server (NTRS)

Cowan, J. R.; Myers, W. N.

1992-01-01

NASA-Marshall is involved in the development of electromechanical actuators (EMA) for thrust-vector control (TVC) system testing and implementation in spacecraft control/gimballing systems, with a view to the replacement of hydraulic hardware. TVC system control is furnished by solid state controllers and power supplies; a pair of resolvers supply position feedback to the controller for precise positioning. Performance comparisons between EMA and hydraulic TVC systems are performed.

Design and test of a high power electromechanical actuator for thrust vector control

NASA Astrophysics Data System (ADS)

Cowan, J. R.; Myers, W. N.

1992-07-01

NASA-Marshall is involved in the development of electromechanical actuators (EMA) for thrust-vector control (TVC) system testing and implementation in spacecraft control/gimballing systems, with a view to the replacement of hydraulic hardware. TVC system control is furnished by solid state controllers and power supplies; a pair of resolvers supply position feedback to the controller for precise positioning. Performance comparisons between EMA and hydraulic TVC systems are performed.

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.

Stabilization strategies of a general nonlinear car-following model with varying reaction-time delay of the drivers.

PubMed

Li, Shukai; Yang, Lixing; Gao, Ziyou; Li, Keping

2014-11-01

In this paper, the stabilization strategies of a general nonlinear car-following model with reaction-time delay of the drivers are investigated. The reaction-time delay of the driver is time varying and bounded. By using the Lyapunov stability theory, the sufficient condition for the existence of the state feedback control strategy for the stability of the car-following model is given in the form of linear matrix inequality, under which the traffic jam can be well suppressed with respect to the varying reaction-time delay. Moreover, by considering the external disturbance for the running cars, the robust state feedback control strategy is designed, which ensures robust stability and a smaller prescribed H∞ disturbance attenuation level for the traffic flow. Numerical examples are given to illustrate the effectiveness of the proposed methods. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Global desertification: Drivers and feedbacks

NASA Astrophysics Data System (ADS)

D'Odorico, Paolo; Bhattachan, Abinash; Davis, Kyle F.; Ravi, Sujith; Runyan, Christiane W.

2013-01-01

Desertification is a change in soil properties, vegetation or climate, which results in a persistent loss of ecosystem services that are fundamental to sustaining life. Desertification affects large dryland areas around the world and is a major cause of stress in human societies. Here we review recent research on the drivers, feedbacks, and impacts of desertification. A multidisciplinary approach to understanding the drivers and feedbacks of global desertification is motivated by our increasing need to improve global food production and to sustainably manage ecosystems in the context of climate change. Classic desertification theories look at this process as a transition between stable states in bistable ecosystem dynamics. Climate change (i.e., aridification) and land use dynamics are the major drivers of an ecosystem shift to a “desertified” (or “degraded”) state. This shift is typically sustained by positive feedbacks, which stabilize the system in the new state. Desertification feedbacks may involve land degradation processes (e.g., nutrient loss or salinization), changes in rainfall regime resulting from land-atmosphere interactions (e.g., precipitation recycling, dust emissions), or changes in plant community composition (e.g., shrub encroachment, decrease in vegetation cover). We analyze each of these feedback mechanisms and discuss their possible enhancement by interactions with socio-economic drivers. Large scale effects of desertification include the emigration of “environmental refugees” displaced from degraded areas, climatic changes, and the alteration of global biogeochemical cycles resulting from the emission and long-range transport of fine mineral dust. Recent research has identified some possible early warning signs of desertification, which can be used as indicators of resilience loss and imminent shift to desert-like conditions. We conclude with a brief discussion on some desertification control strategies implemented in different regions around the world.

GLIMPSE: Google Glass interface for sensory feedback in myoelectric hand prostheses.

PubMed

Markovic, Marko; Karnal, Hemanth; Graimann, Bernhard; Farina, Dario; Dosen, Strahinja

2017-06-01

Providing sensory feedback to the user of the prosthesis is an important challenge. The common approach is to use tactile stimulation, which is easy to implement but requires training and has limited information bandwidth. In this study, we propose an alternative approach based on augmented reality. We have developed the GLIMPSE, a Google Glass application which connects to the prosthesis via a Bluetooth interface and renders the prosthesis states (EMG signals, aperture, force and contact) using augmented reality (see-through display) and sound (bone conduction transducer). The interface was tested in healthy subjects that used the prosthesis with (FB group) and without (NFB group) feedback during a modified clothespins test that allowed us to vary the difficulty of the task. The outcome measures were the number of unsuccessful trials, the time to accomplish the task, and the subjective ratings of the relevance of the feedback. There was no difference in performance between FB and NFB groups in the case of a simple task (basic, same-color clothespins test), but the feedback significantly improved the performance in a more complex task (pins of different resistances). Importantly, the GLIMPSE feedback did not increase the time to accomplish the task. Therefore, the supplemental feedback might be useful in the tasks which are more demanding, and thereby less likely to benefit from learning and feedforward control. The subjects integrated the supplemental feedback with the intrinsic sources (vision and muscle proprioception), developing their own idiosyncratic strategies to accomplish the task. The present study demonstrates a novel self-contained, ready-to-deploy, wearable feedback interface. The interface was successfully tested and was proven to be feasible and functionally beneficial. The GLIMPSE can be used as a practical solution but also as a general and flexible instrument to investigate closed-loop prosthesis control.

L1 adaptive control of uncertain gear transmission servo systems with deadzone nonlinearity.

PubMed

Zuo, Zongyu; Li, Xiao; Shi, Zhiguang

2015-09-01

This paper deals with the adaptive control problem of Gear Transmission Servo (GTS) systems in the presence of unknown deadzone nonlinearity and viscous friction. A global differential homeomorphism based on a novel differentiable deadzone model is proposed first. Since there exist both matched and unmatched state-dependent unknown nonlinearities, a full-state feedback L1 adaptive controller is constructed to achieve uniformly bounded transient response in addition to steady-state performance. Finally, simulation results are included to show the elimination of limit cycles, in addition to demonstrating the main results in this paper. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Feedback control and heat transfer measurements in a Rayleigh-Bénard convection cell

NASA Astrophysics Data System (ADS)

Vial, M.; Hernández, R. H.

2017-07-01

We report experimental results on the heat transfer and instability onset of a Rayleigh-Bénard convection cell of aspect ratios 6:3:1 filled with a high Prandtl aqueous solution of glycerol under feedback control. We investigate the transient and stationary response of both local temperature readings and heat transfer fluxes on the Rayleigh Bénard cell in both conductive and convective states when we perform two independent feedback control actions on both hot and cold walls. We evaluate the performance of both controllers to maintain a temperature gradient independently if the system is below or above the convection threshold. As the convection cell can be rotated at 180° about the shorter axis of the cell, it was possible to perform transitions between thermal conduction and convection regimes and vice versa under a constant temperature difference maintained by both independent controllers. The experimental setup provided an accurate measurement of the critical Rayleigh number and the evolution of the Nusselt number as a function of the Rayleigh number in the moderately supercritical regime (R a <1 04). Flow visualizations show a steady cellular convection pattern formed by 6 transverse rolls throughout the range of Rayleigh numbers.

Flight test results for the Digital Integrated Automatic Landing Systems (DIALS): A modern control full-state feedback design

NASA Technical Reports Server (NTRS)

Hueschen, R. M.

1984-01-01

The Digital Integrated Automatic Landing System (DIALS) is discussed. The DIALS is a modern control theory design performing all the maneuver modes associated with current autoland systems: localizer capture and track, glideslope capture and track, decrab, and flare. The DIALS is an integrated full-state feedback system which was designed using direct-digital methods. The DIALS uses standard aircraft sensors and the digital Microwave Landing System (MLS) signals as measurements. It consists of separately designed longitudinal and lateral channels although some cross-coupling variables are fed between channels for improved state estimates and trajectory commands. The DIALS was implemented within the 16-bit fixed-point flight computers of the ATOPS research aircraft, a small twin jet commercial transport outfitted with a second research cockpit and a fly-by-wire system. The DIALS became the first modern control theory design to be successfully flight tested on a commercial-type aircraft. Flight tests were conducted in late 1981 using a wide coverage MLS on Runway 22 at Wallops Flight Center. All the modes were exercised including the capture and track of steep glidescopes up to 5 degrees.

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.

Dynamics of the Coupled Human-climate System Resulting from Closed-loop Control of Solar Geoengineering

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

MacMartin, Douglas; Kravitz, Benjamin S.; Keith, David

2014-07-08

If solar radiation management (SRM) were ever implemented, feedback of the observed climate state might be used to adjust the radiative forcing of SRM, in order to compensate for uncertainty in either the forcing or the climate response; this would also compensate for unexpected changes in the system, e.g. a nonlinear change in climate sensitivity. This feedback creates an emergent coupled human-climate system, with entirely new dynamics. In addition to the intended response to greenhouse-gas induced changes, the use of feedback would also result in a geoengineering response to natural climate variability. We use a simple box-diffusion dynamic model tomore » understand how changing feedback-control parameters and time delay affect the behavior of this coupled natural-human system, and verify these predictions using the HadCM3L general circulation model. In particular, some amplification of natural variability is unavoidable; any time delay (e.g., to average out natural variability, or due to decision-making) exacerbates this amplification, with oscillatory behavior possible if there is a desire for rapid correction (high feedback gain), but a delayed response needed for decision making. Conversely, the need for feedback to compensate for uncertainty, combined with a desire to avoid excessive amplification, results in a limit on how rapidly SRM could respond to uncertain changes.« less

Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems.

PubMed

Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

2016-01-01

This paper presents a novel adaptive neural network (NN) control of single-input and single-output uncertain nonlinear discrete-time systems under event sampled NN inputs. In this control scheme, the feedback signals are transmitted, and the NN weights are tuned in an aperiodic manner at the event sampled instants. After reviewing the NN approximation property with event sampled inputs, an adaptive state estimator (SE), consisting of linearly parameterized NNs, is utilized to approximate the unknown system dynamics in an event sampled context. The SE is viewed as a model and its approximated dynamics and the state vector, during any two events, are utilized for the event-triggered controller design. An adaptive event-trigger condition is derived by using both the estimated NN weights and a dead-zone operator to determine the event sampling instants. This condition both facilitates the NN approximation and reduces the transmission of feedback signals. The ultimate boundedness of both the NN weight estimation error and the system state vector is demonstrated through the Lyapunov approach. As expected, during an initial online learning phase, events are observed more frequently. Over time with the convergence of the NN weights, the inter-event times increase, thereby lowering the number of triggered events. These claims are illustrated through the simulation results.

Large space structures control algorithm characterization

NASA Technical Reports Server (NTRS)

Fogel, E.

1983-01-01

Feedback control algorithms are developed for sensor/actuator pairs on large space systems. These algorithms have been sized in terms of (1) floating point operation (FLOP) demands; (2) storage for variables; and (3) input/output data flow. FLOP sizing (per control cycle) was done as a function of the number of control states and the number of sensor/actuator pairs. Storage for variables and I/O sizing was done for specific structure examples.

Adaptive Control Allocation in the Presence of Actuator Failures

NASA Technical Reports Server (NTRS)

Liu, Yu; Crespo, Luis G.

2010-01-01

In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

Exact results for Schrödinger cats in driven-dissipative systems and their feedback control

NASA Astrophysics Data System (ADS)

Minganti, Fabrizio; Bartolo, Nicola; Lolli, Jared; Casteels, Wim; Ciuti, Cristiano

2016-05-01

In quantum optics, photonic Schrödinger cats are superpositions of two coherent states with opposite phases and with a significant number of photons. Recently, these states have been observed in the transient dynamics of driven-dissipative resonators subject to engineered two-photon processes. Here we present an exact analytical solution of the steady-state density matrix for this class of systems, including one-photon losses, which are considered detrimental for the achievement of cat states. We demonstrate that the unique steady state is a statistical mixture of two cat-like states with opposite parity, in spite of significant one-photon losses. The transient dynamics to the steady state depends dramatically on the initial state and can pass through a metastable regime lasting orders of magnitudes longer than the photon lifetime. By considering individual quantum trajectories in photon-counting configuration, we find that the system intermittently jumps between two cats. Finally, we propose and study a feedback protocol based on this behaviour to generate a pure cat-like steady state.

Feedback and feedforward adaptation to visuomotor delay during reaching and slicing movements.

PubMed

Botzer, Lior; Karniel, Amir

2013-07-01

It has been suggested that the brain and in particular the cerebellum and motor cortex adapt to represent the environment during reaching movements under various visuomotor perturbations. It is well known that significant delay is present in neural conductance and processing; however, the possible representation of delay and adaptation to delayed visual feedback has been largely overlooked. Here we investigated the control of reaching movements in human subjects during an imposed visuomotor delay in a virtual reality environment. In the first experiment, when visual feedback was unexpectedly delayed, the hand movement overshot the end-point target, indicating a vision-based feedback control. Over the ensuing trials, movements gradually adapted and became accurate. When the delay was removed unexpectedly, movements systematically undershot the target, demonstrating that adaptation occurred within the vision-based feedback control mechanism. In a second experiment designed to broaden our understanding of the underlying mechanisms, we revealed similar after-effects for rhythmic reversal (out-and-back) movements. We present a computational model accounting for these results based on two adapted forward models, each tuned for a specific modality delay (proprioception or vision), and a third feedforward controller. The computational model, along with the experimental results, refutes delay representation in a pure forward vision-based predictor and suggests that adaptation occurred in the forward vision-based predictor, and concurrently in the state-based feedforward controller. Understanding how the brain compensates for conductance and processing delays is essential for understanding certain impairments concerning these neural delays as well as for the development of brain-machine interfaces. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration

PubMed Central

Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B.

2017-01-01

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of speech but retain the ability to make online feedback corrections; indeed, the patients show an increased sensitivity to feedback. These results indicate that the cerebellum forms a crucial part of the feedforward control system for speech but is not essential for online, feedback control. PMID:28842410

Feedback from the heart: Emotional learning and memory is controlled by cardiac cycle, interoceptive accuracy and personality.

PubMed

Pfeifer, Gaby; Garfinkel, Sarah N; Gould van Praag, Cassandra D; Sahota, Kuljit; Betka, Sophie; Critchley, Hugo D

2017-05-01

Feedback processing is critical to trial-and-error learning. Here, we examined whether interoceptive signals concerning the state of cardiovascular arousal influence the processing of reinforcing feedback during the learning of 'emotional' face-name pairs, with subsequent effects on retrieval. Participants (N=29) engaged in a learning task of face-name pairs (fearful, neutral, happy faces). Correct and incorrect learning decisions were reinforced by auditory feedback, which was delivered either at cardiac systole (on the heartbeat, when baroreceptors signal the contraction of the heart to the brain), or at diastole (between heartbeats during baroreceptor quiescence). We discovered a cardiac influence on feedback processing that enhanced the learning of fearful faces in people with heightened interoceptive ability. Individuals with enhanced accuracy on a heartbeat counting task learned fearful face-name pairs better when feedback was given at systole than at diastole. This effect was not present for neutral and happy faces. At retrieval, we also observed related effects of personality: First, individuals scoring higher for extraversion showed poorer retrieval accuracy. These individuals additionally manifested lower resting heart rate and lower state anxiety, suggesting that attenuated levels of cardiovascular arousal in extraverts underlies poorer performance. Second, higher extraversion scores predicted higher emotional intensity ratings of fearful faces reinforced at systole. Third, individuals scoring higher for neuroticism showed higher retrieval confidence for fearful faces reinforced at diastole. Our results show that cardiac signals shape feedback processing to influence learning of fearful faces, an effect underpinned by personality differences linked to psychophysiological arousal. Copyright © 2017 Elsevier B.V. All rights reserved.

Coordinated three-dimensional motion of the head and torso by dynamic neural networks.

PubMed

Kim, J; Hemami, H

1998-01-01

The problem of trajectory tracking control of a three dimensional (3D) model of the human upper torso and head is considered. The torso and the head are modeled as two rigid bodies connected at one point, and the Newton-Euler method is used to derive the nonlinear differential equations that govern the motion of the system. The two-link system is driven by six pairs of muscle like actuators that possess physiologically inspired alpha like and gamma like inputs, and spindle like and Golgi tendon organ like outputs. These outputs are utilized as reflex feedback for stability and stiffness control, in a long loop feedback for the purpose of estimating the state of the system (somesthesis), and as part of the input to the controller. Ideal delays of different duration are included in the feedforward and feedback paths of the system to emulate such delays encountered in physiological systems. Dynamical neural networks are trained to learn effective control of the desired maneuvers of the system. The feasibility of the controller is demonstrated by computer simulation of the successful execution of the desired maneuvers. This work demonstrates the capabilities of neural circuits in controlling highly nonlinear systems with multidelays in their feedforward and feedback paths. The ultimate long range goal of this research is toward understanding the working of the central nervous system in controlling movement. It is an interdisciplinary effort relying on mechanics, biomechanics, neuroscience, system theory, physiology and anatomy, and its short range relevance to rehabilitation must be noted.

Sensorless Estimation and Nonlinear Control of a Rotational Energy Harvester

NASA Astrophysics Data System (ADS)

Nunna, Kameswarie; Toh, Tzern T.; Mitcheson, Paul D.; Astolfi, Alessandro

2013-12-01

It is important to perform sensorless monitoring of parameters in energy harvesting devices in order to determine the operating states of the system. However, physical measurements of these parameters is often a challenging task due to the unavailability of access points. This paper presents, as an example application, the design of a nonlinear observer and a nonlinear feedback controller for a rotational energy harvester. A dynamic model of a rotational energy harvester with its power electronic interface is derived and validated. This model is then used to design a nonlinear observer and a nonlinear feedback controller which yield a sensorless closed-loop system. The observer estimates the mechancial quantities from the measured electrical quantities while the control law sustains power generation across a range of source rotation speeds. The proposed scheme is assessed through simulations and experiments.

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.

Through-wafer optical probe characterization for microelectromechanical systems positional state monitoring and feedback control

NASA Astrophysics Data System (ADS)

Dawson, Jeremy M.; Chen, Jingdong; Brown, Kolin S.; Famouri, Parviz F.; Hornak, Lawrence A.

2000-12-01

Implementation of closed-loop microelectromechanical system (MEMS) control enables mechanical microsystems to adapt to the demands of the environment that they are actuating, opening a broad range of new opportunities for future MEMS applications. Integrated optical microsystems have the potential to enable continuous in situ optical interrogation of MEMS microstructure position fully decoupled from the means of mechanical actuation that is necessary for realization of feedback control. We present the results of initial research evaluating through-wafer optical microprobes for surface micromachined MEMS integrated optical position monitoring. Results from the through-wafer free-space optical probe of a lateral comb resonator fabricated using the multiuser MEMS process service (MUMPS) indicate significant positional information content with an achievable return probe signal dynamic range of up to 80% arising from film transmission contrast. Static and dynamic deflection analysis and experimental results indicate a through-wafer probe positional signal sensitivity of 40 mV/micrometers for the present setup or 10% signal change per micrometer. A simulation of the application of nonlinear sliding control is presented illustrating position control of the lateral comb resonator structure given the availability of positional state information.

Decentralized Adaptive Neural Output-Feedback DSC for Switched Large-Scale Nonlinear Systems.

PubMed

Lijun Long; Jun Zhao

2017-04-01

In this paper, for a class of switched large-scale uncertain nonlinear systems with unknown control coefficients and unmeasurable states, a switched-dynamic-surface-based decentralized adaptive neural output-feedback control approach is developed. The approach proposed extends the classical dynamic surface control (DSC) technique for nonswitched version to switched version by designing switched first-order filters, which overcomes the problem of multiple "explosion of complexity." Also, a dual common coordinates transformation of all subsystems is exploited to avoid individual coordinate transformations for subsystems that are required when applying the backstepping recursive design scheme. Nussbaum-type functions are utilized to handle the unknown control coefficients, and a switched neural network observer is constructed to estimate the unmeasurable states. Combining with the average dwell time method and backstepping and the DSC technique, decentralized adaptive neural controllers of subsystems are explicitly designed. It is proved that the approach provided can guarantee the semiglobal uniformly ultimately boundedness for all the signals in the closed-loop system under a class of switching signals with average dwell time, and the tracking errors to a small neighborhood of the origin. A two inverted pendulums system is provided to demonstrate the effectiveness of the method proposed.

Comparison of adaptive critic-based and classical wide-area controllers for power systems.

PubMed

Ray, Swakshar; Venayagamoorthy, Ganesh Kumar; Chaudhuri, Balarko; Majumder, Rajat

2008-08-01

An adaptive critic design (ACD)-based damping controller is developed for a thyristor-controlled series capacitor (TCSC) installed in a power system with multiple poorly damped interarea modes. The performance of this ACD computational intelligence-based method is compared with two classical techniques, which are observer-based state-feedback (SF) control and linear matrix inequality LMI-H(infinity) robust control. Remote measurements are used as feedback signals to the wide-area damping controller for modulating the compensation of the TCSC. The classical methods use a linearized model of the system whereas the ACD method is purely measurement-based, leading to a nonlinear controller with fixed parameters. A comparative analysis of the controllers' performances is carried out under different disturbance scenarios. The ACD-based design has shown promising performance with very little knowledge of the system compared to classical model-based controllers. This paper also discusses the advantages and disadvantages of ACDs, SF, and LMI-H(infinity).

State-space control of prosthetic hand shape.

PubMed

Velliste, M; McMorland, A J C; Diril, E; Clanton, S T; Schwartz, A B

2012-01-01

In the field of neuroprosthetic control, there is an emerging need for simplified control of high-dimensional devices. Advances in robotic technology have led to the development of prosthetic arms that now approach the look and number of degrees of freedom (DoF) of a natural arm. These arms, and especially hands, now have more controllable DoFs than the number of control DoFs available in many applications. In natural movements, high correlations exist between multiple joints, such as finger flexions. Therefore, discrepancy between the number of control and effector DoFs can be overcome by a control scheme that maps low-DoF control space to high-DoF joint space. Imperfect effectors, sensor noise and interactions with external objects require the use of feedback controllers. The incorporation of feedback in a system where the command is in a different space, however, is challenging, requiring a potentially difficult inverse high-DoF to low-DoF transformation. Here we present a solution to this problem based on the Extended Kalman Filter.

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

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

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.

Determination of Trajectories for a Gliding Parachute System

DTIC Science & Technology

1975-04-01

use of such items. Destroy this report when no longer needed. Do not return it to the originator. * jiT >T^>’TyT>’V’v,>T>’*.y^jrw\\gwJ^ "-’ v*»’v -*iv...The terminal error serves as a penalty function which penalizes undesirable terminal states by the extent to which they deviate from the desired...the open-loop control becomes, in effect , feedback control with the sequence of initial conditions serving as the current state. The major advantage

Deterministic entanglement of superconducting qubits by parity measurement and feedback.

PubMed

Ristè, D; Dukalski, M; Watson, C A; de Lange, G; Tiggelman, M J; Blanter, Ya M; Lehnert, K W; Schouten, R N; DiCarlo, L

2013-10-17

The stochastic evolution of quantum systems during measurement is arguably the most enigmatic feature of quantum mechanics. Measuring a quantum system typically steers it towards a classical state, destroying the coherence of an initial quantum superposition and the entanglement with other quantum systems. Remarkably, the measurement of a shared property between non-interacting quantum systems can generate entanglement, starting from an uncorrelated state. Of special interest in quantum computing is the parity measurement, which projects the state of multiple qubits (quantum bits) to a state with an even or odd number of excited qubits. A parity meter must discern the two qubit-excitation parities with high fidelity while preserving coherence between same-parity states. Despite numerous proposals for atomic, semiconducting and superconducting qubits, realizing a parity meter that creates entanglement for both even and odd measurement results has remained an outstanding challenge. Here we perform a time-resolved, continuous parity measurement of two superconducting qubits using the cavity in a three-dimensional circuit quantum electrodynamics architecture and phase-sensitive parametric amplification. Using postselection, we produce entanglement by parity measurement reaching 88 per cent fidelity to the closest Bell state. Incorporating the parity meter in a feedback-control loop, we transform the entanglement generation from probabilistic to fully deterministic, achieving 66 per cent fidelity to a target Bell state on demand. These realizations of a parity meter and a feedback-enabled deterministic measurement protocol provide key ingredients for active quantum error correction in the solid state.

LPV gain-scheduled control of SCR aftertreatment systems

NASA Astrophysics Data System (ADS)

Meisami-Azad, Mona; Mohammadpour, Javad; Grigoriadis, Karolos M.; Harold, Michael P.; Franchek, Matthew A.

2012-01-01

Hydrocarbons, carbon monoxide and some of other polluting emissions produced by diesel engines are usually lower than those produced by gasoline engines. While great strides have been made in the exhaust aftertreatment of vehicular pollutants, the elimination of nitrogen oxide (NO x ) from diesel vehicles is still a challenge. The primary reason is that diesel combustion is a fuel-lean process, and hence there is significant unreacted oxygen in the exhaust. Selective catalytic reduction (SCR) is a well-developed technology for power plants and has been recently employed for reducing NO x emissions from automotive sources and in particular, heavy-duty diesel engines. In this article, we develop a linear parameter-varying (LPV) feedforward/feedback control design method for the SCR aftertreatment system to decrease NO x emissions while keeping ammonia slippage to a desired low level downstream the catalyst. The performance of the closed-loop system obtained from the interconnection of the SCR system and the output feedback LPV control strategy is then compared with other control design methods including sliding mode, and observer-based static state-feedback parameter-varying control. To reduce the computational complexity involved in the control design process, the number of LPV parameters in the developed quasi-LPV (qLPV) model is reduced by applying the principal component analysis technique. An LPV feedback/feedforward controller is then designed for the qLPV model with reduced number of scheduling parameters. The designed full-order controller is further simplified to a first-order transfer function with a parameter-varying gain and pole. Finally, simulation results using both a low-order model and a high-fidelity and high-order model of SCR reactions in GT-POWER interfaced with MATLAB/SIMULINK illustrate the high NO x conversion efficiency of the closed-loop SCR system using the proposed parameter-varying control law.

Control of AUVs using differential flatness theory and the derivative-free nonlinear Kalman Filter

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Raffo, Guilerme

2015-12-01

The paper proposes nonlinear control and filtering for Autonomous Underwater Vessels (AUVs) based on differential flatness theory and on the use of the Derivative-free nonlinear Kalman Filter. First, it is shown that the 6-DOF dynamic model of the AUV is a differentially flat one. This enables its transformation into the linear canonical (Brunovsky) form and facilitates the design of a state feedback controller. A problem that has to be dealt with is the uncertainty about the parameters of the AUV's dynamic model, as well the external perturbations which affect its motion. To cope with this, it is proposed to use a disturbance observer which is based on the Derivative-free nonlinear Kalman Filter. The considered filtering method consists of the standard Kalman Filter recursion applied on the linearized model of the vessel and of an inverse transformation based on differential flatness theory, which enables to obtain estimates of the state variables of the initial nonlinear model of the vessel. The Kalman Filter-based disturbance observer performs simultaneous estimation of the non-measurable state variables of the AUV and of the perturbation terms that affect its dynamics. By estimating such disturbances, their compensation is also succeeded through suitable modification of the feedback control input. The efficiency of the proposed AUV control and estimation scheme is confirmed through simulation experiments.

Learning the Art of Electronics

NASA Astrophysics Data System (ADS)

Hayes, Thomas C.; Horowitz, Paul

2016-03-01

1. DC circuits; 2. RC circuits; 3. Diode circuits; 4. Transistors I; 5. Transistors II; 6. Operational amplifiers I; 7. Operational amplifiers II: nice positive feedback; 8. Operational amplifiers III; 9. Operational amplifiers IV: nasty positive feedback; 10. Operational amplifiers V: PID motor control loop; 11. Voltage regulators; 12. MOSFET switches; 13. Group audio project; 14. Logic gates; 15. Logic compilers, sequential circuits, flip-flops; 16. Counters; 17. Memory: state machines; 18. Analog to digital: phase-locked loop; 19. Microcontrollers and microprocessors I: processor/controller; 20. I/O, first assembly language; 21. Bit operations; 22. Interrupt: ADC and DAC; 23. Moving pointers, serial buses; 24. Dallas Standalone Micro, SiLabs SPI RAM; 25. Toys in the attic; Appendices; Index.

Passivity-based control of linear time-invariant systems modelled by bond graph

NASA Astrophysics Data System (ADS)

Galindo, R.; Ngwompo, R. F.

2018-02-01

Closed-loop control systems are designed for linear time-invariant (LTI) controllable and observable systems modelled by bond graph (BG). Cascade and feedback interconnections of BG models are realised through active bonds with no loading effect. The use of active bonds may lead to non-conservation of energy and the overall system is modelled by proposed pseudo-junction structures. These structures are build by adding parasitic elements to the BG models and the overall system may become singularly perturbed. The structures for these interconnections can be seen as consisting of inner structures that satisfy energy conservation properties and outer structures including multiport-coupled dissipative fields. These fields highlight energy properties like passivity that are useful for control design. In both interconnections, junction structures and dissipative fields for the controllers are proposed, and passivity is guaranteed for the closed-loop systems assuring robust stability. The cascade interconnection is applied to the structural representation of closed-loop transfer functions, when a stabilising controller is applied to a given nominal plant. Applications are given when the plant and the controller are described by state-space realisations. The feedback interconnection is used getting necessary and sufficient stability conditions based on the closed-loop characteristic polynomial, solving a pole-placement problem and achieving zero-stationary state error.

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.

To make people save energy tell them what others do but also who they are: a preliminary study

PubMed Central

Graffeo, Michele; Ritov, Ilana; Bonini, Nicolao; Hadjichristidis, Constantinos

2015-01-01

A way to make people save energy is by informing them that “comparable others” save more. We investigated whether, one can further improve this nudge by manipulating Who the “comparable others” are. We asked participants to imagine receiving feedback stating that their energy consumption exceeded that of “comparable others” by 10%. We varied Who the “comparable others” were in a 2 × 2 design: they were a household that was located either in the same neighborhood as themselves or in a different neighborhood, and its members were either identified (by names and a photograph) or unidentified. We also included two control conditions: one where no feedback was provided, and one where only statistical feedback was provided (feedback about an average household). We found that it matters Who the “comparable others” are. The most effective feedback was when the referent household was from the same neighborhood as the individual's and its members were not identified. PMID:26379603

Learning from negative feedback in patients with major depressive disorder is attenuated by SSRI antidepressants

PubMed Central

Herzallah, Mohammad M.; Moustafa, Ahmed A.; Natsheh, Joman Y.; Abdellatif, Salam M.; Taha, Mohamad B.; Tayem, Yasin I.; Sehwail, Mahmud A.; Amleh, Ivona; Petrides, Georgios; Myers, Catherine E.; Gluck, Mark A.

2013-01-01

One barrier to interpreting past studies of cognition and major depressive disorder (MDD) has been the failure in many studies to adequately dissociate the effects of MDD from the potential cognitive side effects of selective serotonin reuptake inhibitors (SSRIs) use. To better understand how remediation of depressive symptoms affects cognitive function in MDD, we evaluated three groups of subjects: medication-naïve patients with MDD, medicated patients with MDD receiving the SSRI paroxetine, and healthy control (HC) subjects. All were administered a category-learning task that allows for dissociation between learning from positive feedback (reward) vs. learning from negative feedback (punishment). Healthy subjects learned significantly better from positive feedback than medication-naïve and medicated MDD groups, whose learning accuracy did not differ significantly. In contrast, medicated patients with MDD learned significantly less from negative feedback than medication-naïve patients with MDD and healthy subjects, whose learning accuracy was comparable. A comparison of subject’s relative sensitivity to positive vs. negative feedback showed that both the medicated MDD and HC groups conform to Kahneman and Tversky’s (1979) Prospect Theory, which expects losses (negative feedback) to loom psychologically slightly larger than gains (positive feedback). However, medicated MDD and HC profiles are not similar, which indicates that the state of medicated MDD is not “normal” when compared to HC, but rather balanced with less learning from both positive and negative feedback. On the other hand, medication-naïve patients with MDD violate Prospect Theory by having significantly exaggerated learning from negative feedback. This suggests that SSRI antidepressants impair learning from negative feedback, while having negligible effect on learning from positive feedback. Overall, these findings shed light on the importance of dissociating the cognitive consequences of MDD from those of SSRI treatment, and from cognitive evaluation of MDD subjects in a medication-naïve state before the administration of antidepressants. Future research is needed to correlate the mood-elevating effects and the cognitive balance between reward- and punishment-based learning related to SSRIs. PMID:24065894

Learning from negative feedback in patients with major depressive disorder is attenuated by SSRI antidepressants.

PubMed

Herzallah, Mohammad M; Moustafa, Ahmed A; Natsheh, Joman Y; Abdellatif, Salam M; Taha, Mohamad B; Tayem, Yasin I; Sehwail, Mahmud A; Amleh, Ivona; Petrides, Georgios; Myers, Catherine E; Gluck, Mark A

2013-01-01

One barrier to interpreting past studies of cognition and major depressive disorder (MDD) has been the failure in many studies to adequately dissociate the effects of MDD from the potential cognitive side effects of selective serotonin reuptake inhibitors (SSRIs) use. To better understand how remediation of depressive symptoms affects cognitive function in MDD, we evaluated three groups of subjects: medication-naïve patients with MDD, medicated patients with MDD receiving the SSRI paroxetine, and healthy control (HC) subjects. All were administered a category-learning task that allows for dissociation between learning from positive feedback (reward) vs. learning from negative feedback (punishment). Healthy subjects learned significantly better from positive feedback than medication-naïve and medicated MDD groups, whose learning accuracy did not differ significantly. In contrast, medicated patients with MDD learned significantly less from negative feedback than medication-naïve patients with MDD and healthy subjects, whose learning accuracy was comparable. A comparison of subject's relative sensitivity to positive vs. negative feedback showed that both the medicated MDD and HC groups conform to Kahneman and Tversky's (1979) Prospect Theory, which expects losses (negative feedback) to loom psychologically slightly larger than gains (positive feedback). However, medicated MDD and HC profiles are not similar, which indicates that the state of medicated MDD is not "normal" when compared to HC, but rather balanced with less learning from both positive and negative feedback. On the other hand, medication-naïve patients with MDD violate Prospect Theory by having significantly exaggerated learning from negative feedback. This suggests that SSRI antidepressants impair learning from negative feedback, while having negligible effect on learning from positive feedback. Overall, these findings shed light on the importance of dissociating the cognitive consequences of MDD from those of SSRI treatment, and from cognitive evaluation of MDD subjects in a medication-naïve state before the administration of antidepressants. Future research is needed to correlate the mood-elevating effects and the cognitive balance between reward- and punishment-based learning related to SSRIs.

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.

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.

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.

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.

The detection and stabilisation of limit cycle for deterministic finite automata

NASA Astrophysics Data System (ADS)

Han, Xiaoguang; Chen, Zengqiang; Liu, Zhongxin; Zhang, Qing

2018-04-01

In this paper, the topological structure properties of deterministic finite automata (DFA), under the framework of the semi-tensor product of matrices, are investigated. First, the dynamics of DFA are converted into a new algebraic form as a discrete-time linear system by means of Boolean algebra. Using this algebraic description, the approach of calculating the limit cycles of different lengths is given. Second, we present two fundamental concepts, namely, domain of attraction of limit cycle and prereachability set. Based on the prereachability set, an explicit solution of calculating domain of attraction of a limit cycle is completely characterised. Third, we define the globally attractive limit cycle, and then the necessary and sufficient condition for verifying whether all state trajectories of a DFA enter a given limit cycle in a finite number of transitions is given. Fourth, the problem of whether a DFA can be stabilised to a limit cycle by the state feedback controller is discussed. Criteria for limit cycle-stabilisation are established. All state feedback controllers which implement the minimal length trajectories from each state to the limit cycle are obtained by using the proposed algorithm. Finally, an illustrative example is presented to show the theoretical results.

Synchrony suppression in ensembles of coupled oscillators via adaptive vanishing feedback.

PubMed

Montaseri, Ghazal; Yazdanpanah, Mohammad Javad; Pikovsky, Arkady; Rosenblum, Michael

2013-09-01

Synchronization and emergence of a collective mode is a general phenomenon, frequently observed in ensembles of coupled self-sustained oscillators of various natures. In several circumstances, in particular in cases of neurological pathologies, this state of the active medium is undesirable. Destruction of this state by a specially designed stimulation is a challenge of high clinical relevance. Typically, the precise effect of an external action on the ensemble is unknown, since the microscopic description of the oscillators and their interactions are not available. We show that, desynchronization in case of a large degree of uncertainty about important features of the system is nevertheless possible; it can be achieved by virtue of a feedback loop with an additional adaptation of parameters. The adaptation also ensures desynchronization of ensembles with non-stationary, time-varying parameters. We perform the stability analysis of the feedback-controlled system and demonstrate efficient destruction of synchrony for several models, including those of spiking and bursting neurons.

Synchrony suppression in ensembles of coupled oscillators via adaptive vanishing feedback

NASA Astrophysics Data System (ADS)

Montaseri, Ghazal; Javad Yazdanpanah, Mohammad; Pikovsky, Arkady; Rosenblum, Michael

2013-09-01

Synchronization and emergence of a collective mode is a general phenomenon, frequently observed in ensembles of coupled self-sustained oscillators of various natures. In several circumstances, in particular in cases of neurological pathologies, this state of the active medium is undesirable. Destruction of this state by a specially designed stimulation is a challenge of high clinical relevance. Typically, the precise effect of an external action on the ensemble is unknown, since the microscopic description of the oscillators and their interactions are not available. We show that, desynchronization in case of a large degree of uncertainty about important features of the system is nevertheless possible; it can be achieved by virtue of a feedback loop with an additional adaptation of parameters. The adaptation also ensures desynchronization of ensembles with non-stationary, time-varying parameters. We perform the stability analysis of the feedback-controlled system and demonstrate efficient destruction of synchrony for several models, including those of spiking and bursting neurons.

Synthesis of hover autopilots for rotary-wing VTOL aircraft

NASA Technical Reports Server (NTRS)

Hall, W. E.; Bryson, A. E., Jr.

1972-01-01

The practical situation is considered where imperfect information on only a few rotor and fuselage state variables is available. Filters are designed to estimate all the state variables from noisy measurements of fuselage pitch/roll angles and from noisy measurements of both fuselage and rotor pitch/roll angles. The mean square response of the vehicle to a very gusty, random wind is computed using various filter/controllers and is found to be quite satisfactory although, of course, not so good as when one has perfect information (idealized case). The second part of the report considers precision hover over a point on the ground. A vehicle model without rotor dynamics is used and feedback signals in position and integral of position error are added. The mean square response of the vehicle to a very gusty, random wind is computed, assuming perfect information feedback, and is found to be excellent. The integral error feedback gives zero position error for a steady wind, and smaller position error for a random wind.

Structural analysis and design of multivariable control systems: An algebraic approach

NASA Technical Reports Server (NTRS)

Tsay, Yih Tsong; Shieh, Leang-San; Barnett, Stephen

1988-01-01

The application of algebraic system theory to the design of controllers for multivariable (MV) systems is explored analytically using an approach based on state-space representations and matrix-fraction descriptions. Chapters are devoted to characteristic lambda matrices and canonical descriptions of MIMO systems; spectral analysis, divisors, and spectral factors of nonsingular lambda matrices; feedback control of MV systems; and structural decomposition theories and their application to MV control systems.

Project Management Using Modern Guidance, Navigation and Control Theory

NASA Technical Reports Server (NTRS)

Hill, Terry R.

2011-01-01

Implementing guidance, navigation, and control (GN&C) theory principles and applying them to the human element of project management and control is not a new concept. As both the literature on the subject and the real-world applications are neither readily available nor comprehensive with regard to how such principles might be applied, this paper has been written to educate the project manager on the "laws of physics" of his or her project (not to teach a GN&C engineer how to become a project manager) and to provide an intuitive, mathematical explanation as to the control and behavior of projects. This paper will also address how the fundamental principles of modern GN&C were applied to the National Aeronautics and Space Administration's (NASA) Constellation Program (CxP) space suit project, ensuring the project was managed within cost, schedule, and budget. A project that is akin to a physical system can be modeled and managed using the same over arching principles of GN&C that would be used if that project were a complex vehicle, a complex system(s), or complex software with time-varying processes (at times nonlinear) containing multiple data inputs of varying accuracy and a range of operating points. The classic GN&C theory approach could thus be applied to small, well-defined projects; yet when working with larger, multiyear projects necessitating multiple organizational structures, numerous external influences, and a multitude of diverse resources, modern GN&C principles are required to model and manage the project. The fundamental principles of a GN&C system incorporate these basic concepts: State, Behavior, Feedback Control, Navigation, Guidance and Planning Logic systems. The State of a system defines the aspects of the system that can change over time; e.g., position, velocity, acceleration, coordinate-based attitude, and temperature, etc. The Behavior of the system focuses more on what changes are possible within the system; this is denoted in the state of the system. The behavior of a system, as captured in the system modeling, when properly done will aid in accurately predicting future system performance. The Feedback Control system understands the state and behavior of the system and uses feedback to adjust control inputs into the system. The feedback, which is the right arm of the Control system, allows change to be affected in the overall system; it therefore is important to not only correctly identify the system feedback inputs, but also the system response to the feedback inputs. The Navigation system takes multiple data inputs and based on a priori knowledge of the inputs, develops a statistically based weighting of the inputs and measurements to determine the system's state. Guidance and Planning Logic of the system, complete with an understanding of where the system is (provided by the Navigation system), will in turn determine where the system needs to be and how to get it there. With any system/project, it is critical that the objective of the system/project be clearly defined -- not only to plan but to measure performance and to aid in guiding the system or the project. The system principles discussed above, which can be and have been applied to the current CxP space suit development project, can also be mapped to real-world constituents, thus allowing project managers to apply systems theories that are well defined in engineering and mathematics to a discipline (i.e., Project Management) that historically has been based in personal experience and intuition. This mapping of GN&C theory to Project Management will, in turn, permit a direct, methodical approach to Project Management, planning and control providing a tool to help predict (and guide) performance and an understanding of the project constraints, how the project can be controlled, and the impacts to external influences and inputs. This approach, to a project manager, flows down to the three bottom-line variables of cost, schedule, and scope ando the needed control of these three variables to successfully perform and complete a project.

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…

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems

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

Zhou, Yuyang; Zhang, Qichun; Wang, Hong

In this paper, a novel control algorithm is presented to enhance the performance of tracking property for a class of non-linear dynamic stochastic systems with unmeasurable variables. To minimize the entropy of tracking errors without changing the existing closed loop with PI controller, the enhanced performance loop is constructed based on the state estimation by extended Kalman Filter and the new controller is designed by full state feedback following this presented control algorithm. Besides, the conditions are obtained for the stability analysis in the mean square sense. In the end, the comparative simulation results are given to illustrate the effectivenessmore » of proposed control algorithm.« less

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.

Dynamics modeling and periodic control of horizontal-axis wind turbines

NASA Astrophysics Data System (ADS)

Stol, Karl Alexander

2001-07-01

The development of large multi-megawatt wind turbines has increased the need for active feedback control to meet multiple performance objectives. Power regulation is still of prime concern but there is an increasing interest in mitigating loads for these very large, dynamically soft and highly integrated power systems. This work explores the opportunities for utilizing state space modeling, modal analysis, and multi-objective controllers in advanced horizontal-axis wind turbines. A linear state-space representation of a generic, multiple degree-of-freedom wind turbine is developed to test various control methods and paradigms. The structural model, SymDyn, provides for limited flexibility in the tower, drive train and blades assuming a rigid component architecture with joint springs and dampers. Equations of motion are derived symbolically, verified by numerical simulation, and implemented in the Matlab with Simulink computational environment. AeroDyn, an industry-standard aerodynamics package for wind turbines, provides the aerodynamic load data through interfaced subroutines. Linearization of the structural model produces state equations with periodic coefficients due to the interaction of rotating and non-rotating components. Floquet theory is used to extract the necessary modal properties and several parametric studies identify the damping levels and dominant dynamic coupling influences. Two separate issues of control design are investigated: full-state feedback and state estimation. Periodic gains are developed using time-varying LQR techniques and many different time-invariant control designs are constructed, including a classical PID controller. Disturbance accommodating control (DAC) allows the estimation of wind speed for minimization of the disturbance effects on the system. Controllers are tested in simulation for multiple objectives using measurement of rotor position and rotor speed only and actuation of independent blade pitch. It is found that periodic control is capable of reducing cyclic blade bending moments while regulating speed but that optimal performance requires additional sensor information. Periodic control is also the only design found that could successfully control the yaw alignment although blade loads are increased as a consequence. When speed regulation is the only performance objective then a time-invariant state-space design or PID is appropriate.

Feedback linearization of singularly perturbed systems based on canonical similarity transformations

NASA Astrophysics Data System (ADS)

Kabanov, A. A.

2018-05-01

This paper discusses the problem of feedback linearization of a singularly perturbed system in a state-dependent coefficient form. The result is based on the introduction of a canonical similarity transformation. The transformation matrix is constructed from separate blocks for fast and slow part of an original singularly perturbed system. The transformed singular perturbed system has a linear canonical form that significantly simplifies a control design problem. Proposed similarity transformation allows accomplishing linearization of the system without considering the virtual output (as it is needed for normal form method), a technique of a transition from phase coordinates of the transformed system to state variables of the original system is simpler. The application of the proposed approach is illustrated through example.

Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration.

PubMed

Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B

2017-09-20

The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of speech but retain the ability to make online feedback corrections; indeed, the patients show an increased sensitivity to feedback. These results indicate that the cerebellum forms a crucial part of the feedforward control system for speech but is not essential for online, feedback control. Copyright © 2017 the authors 0270-6474/17/379249-10$15.00/0.

Motivational and metacognitive feedback in SQL-Tutor*

NASA Astrophysics Data System (ADS)

Hull, Alison; du Boulay, Benedict

2015-04-01

Motivation and metacognition are strongly intertwined, with learners high in self-efficacy more likely to use a variety of self-regulatory learning strategies, as well as to persist longer on challenging tasks. The aim of the research was to improve the learner's focus on the process and experience of problem-solving while using an Intelligent Tutoring System (ITS) and including motivational and metacognitive feedback based on the learner's past states and experiences. An existing ITS, SQL-Tutor, was used with first-year undergraduates studying a database module. The study used two versions of SQL-Tutor: the Control group used a base version providing domain feedback and the Study group used an extended version that also provided motivational and metacognitive feedback. This paper summarises the pre- and post-process results. Comparisons between groups showed some differing trends both in learning outcomes and behaviour in favour of the Study group.

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.

Mean state dependence of ENSO diversity resulting from an intermediate coupled model

NASA Astrophysics Data System (ADS)

Xie, Ruihuang; Jin, Fei-Fei; Mu, Mu

2016-04-01

ENSO diversity is referred to the event-to-event differences in the amplitude, longitudinal location of maximum sea surface temperature (SST) anomalies and evolutional mechanisms, as manifested in both observation data and climate model simulations. Previous studies argued that westerly wind burst (WWB) has strong influence on ENSO diversity. Here, we bring evidences, from a modified intermediate complexity Zebiak-Cane (ZC) coupled model, to illustrate that the ENSO diversity is also determined by the mean states. Stabilities of the linearized ZC model reveal that the mean state with weak (strong) wind stress and deep (shallow) thermocline prefers ENSO variation in the equitorial eastern (central) Pacific with a four-year (two-year) period. Weak wind stress and deep thermocline make the thermocline (TH) feedback the dominant contribution to the growth of ENSO SST anomalies, whereas the opposite mean state favors the zonal advective (ZA) feedback. Different leading dynamical SST-controller makes ENSO display its diversity. In a mean state that resembles the recent climate in the tropical Pacific, the four-year and two-year ENSO variations coexist with similar growth rate. Even without WWB forcing, the nonlinear integration results with adjusted parameters in this special mean state also present at least two types of El Niño, in which the maximum warming rates are contributed by either TH or ZA feedback. The consistency between linear and nonlinear model results indicates that the ENSO diversity is dependent on the mean states.

Designing a stable feedback control system for blind image deconvolution.

PubMed

Cheng, Shichao; Liu, Risheng; Fan, Xin; Luo, Zhongxuan

2018-05-01

Blind image deconvolution is one of the main low-level vision problems with wide applications. Many previous works manually design regularization to simultaneously estimate the latent sharp image and the blur kernel under maximum a posterior framework. However, it has been demonstrated that such joint estimation strategies may lead to the undesired trivial solution. In this paper, we present a novel perspective, using a stable feedback control system, to simulate the latent sharp image propagation. The controller of our system consists of regularization and guidance, which decide the sparsity and sharp features of latent image, respectively. Furthermore, the formational model of blind image is introduced into the feedback process to avoid the image restoration deviating from the stable point. The stability analysis of the system indicates the latent image propagation in blind deconvolution task can be efficiently estimated and controlled by cues and priors. Thus the kernel estimation used for image restoration becomes more precision. Experimental results show that our system is effective on image propagation, and can perform favorably against the state-of-the-art blind image deconvolution methods on different benchmark image sets and special blurred images. Copyright © 2018 Elsevier Ltd. All rights reserved.

Public Health Climate Change Adaptation Planning Using Stakeholder Feedback.

PubMed

Eidson, Millicent; Clancy, Kathleen A; Birkhead, Guthrie S

2016-01-01

Public health climate change adaptation planning is an urgent priority requiring stakeholder feedback. The 10 Essential Public Health Services can be applied to adaptation activities. To develop a state health department climate and health adaptation plan as informed by stakeholder feedback. With Centers for Disease Control and Prevention (CDC) funding, the New York State Department of Health (NYSDOH) implemented a 2010-2013 climate and health planning process, including 7 surveys on perceptions and adaptation priorities. New York State Department of Health program managers participated in initial (n = 41, denominator unknown) and follow-up (72.2%) needs assessments. Surveillance system information was collected from 98.1% of surveillance system managers. For adaptation prioritization surveys, participants included 75.4% of NYSDOH leaders; 60.3% of local health departments (LHDs); and 53.7% of other stakeholders representing environmental, governmental, health, community, policy, academic, and business organizations. Interviews were also completed with 38.9% of other stakeholders. In 2011 surveys, 34.1% of state health program directors believed that climate change would impact their program priorities. However, 84.6% of state health surveillance system managers provided ideas for using databases for climate and health monitoring/surveillance. In 2012 surveys, 46.5% of state health leaders agreed they had sufficient information about climate and health compared to 17.1% of LHDs (P = .0046) and 40.9% of other stakeholders (nonsignificant difference). Significantly fewer (P < .0001) LHDs (22.9%) were incorporating or considering incorporating climate and health into planning compared to state health leaders (55.8%) and other stakeholders (68.2%). Stakeholder groups agreed on the 4 highest priority adaptation categories including core public health activities such as surveillance, coordination/collaboration, education, and policy development. Feedback from diverse stakeholders was utilized by NYSDOH to develop its Climate and Health Strategic Map in 2013. The CDC Building Resilience Against Climate Effects (BRACE) framework and funding provides a collaborative model for state climate and health adaptation planning.

Fuzzy attitude control of solar sail via linear matrix inequalities

NASA Astrophysics Data System (ADS)

Baculi, Joshua; Ayoubi, Mohammad A.

2017-09-01

This study presents a fuzzy tracking controller based on the Takagi-Sugeno (T-S) fuzzy model of the solar sail. First, the T-S fuzzy model is constructed by linearizing the existing nonlinear equations of motion of the solar sail. Then, the T-S fuzzy model is used to derive the state feedback controller gains for the Twin Parallel Distributed Compensation (TPDC) technique. The TPDC tracks and stabilizes the attitude of the solar sail to any desired state in the presence of parameter uncertainties and external disturbances while satisfying actuator constraints. The performance of the TPDC is compared to a PID controller that is tuned using the Ziegler-Nichols method. Numerical simulation shows the TPDC outperforms the PID controller when stabilizing the solar sail to a desired state.

Electro-optic chaotic system based on the reverse-time chaos theory and a nonlinear hybrid feedback loop.

PubMed

Jiang, Xingxing; Cheng, Mengfan; Luo, Fengguang; Deng, Lei; Fu, Songnian; Ke, Changjian; Zhang, Minming; Tang, Ming; Shum, Ping; Liu, Deming

2016-12-12

A novel electro-optic chaos source is proposed on the basis of the reverse-time chaos theory and an analog-digital hybrid feedback loop. The analog output of the system can be determined by the numeric states of shift registers, which makes the system robust and easy to control. The dynamical properties as well as the complexity dependence on the feedback parameters are investigated in detail. The correlation characteristics of the system are also studied. Two improving strategies which were established in digital field and analog field are proposed to conceal the time-delay signature. The proposed scheme has the potential to be used in radar and optical secure communication systems.

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.

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.

A new atomic force microscope force ramp technique using digital force feedback control reveals mechanically weak protein unfolding events.

PubMed

Kawakami, M; Smith, D A

2008-12-10

We have developed a new force ramp modification of the atomic force microscope (AFM) which can control multiple unfolding events of a multi-modular protein using software-based digital force feedback control. With this feedback the force loading rate can be kept constant regardless the length of soft elastic linkage or number of unfolded polypeptide domains. An unfolding event is detected as a sudden drop in force, immediately after which the feedback control reduces the applied force to a low value of a few pN by lowering the force set point. Hence the remaining folded domains can relax and the subsequent force ramp is applied to relaxed protein domains identically in each case. We have applied this technique to determine the kinetic parameters x(u), which is the distance between the native state and transition state, and α(0), which is the unfolding rate constant at zero force, for the mechanical unfolding of a pentamer of I27 domains of titin. In each force ramp the unfolding probability depends on the number of folded domains remaining in the system and we had to take account of this effect in the analysis of unfolding force data. We obtained values of x(u) and α(0) to be 0.28 nm and 1.02 × 10(-3) s(-1), which are in good agreement with those obtained from conventional constant velocity experiments. This method reveals unfolding data at low forces that are not seen in constant velocity experiments and corrects for the change in stiffness that occurs with most mechanical systems throughout the unfolding process to allow constant force ramp experiments to be carried out. In addition, a mechanically weak structure was detected, which formed from the fully extended polypeptide chain during a force quench. This indicates that the new technique will allow studies of the folding kinetics of previously hidden, mechanically weak species.

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.

Self-controlled video feedback on tactical skills for soccer teams results in more active involvement of players.

PubMed

van Maarseveen, Mariëtte J J; Oudejans, Raôul R D; Savelsbergh, Geert J P

2018-02-01

Many studies have shown that self-controlled feedback is beneficial for learning motor tasks, and that learners prefer to receive feedback after supposedly good trials. However, to date all studies conducted on self-controlled learning have used individual tasks and mainly relatively simple skills. Therefore, the aim of this study was to examine self-controlled feedback on tactical skills in small-sided soccer games. Highly talented youth soccer players were assigned to a self-control or yoked group and received video feedback on their offensive performance in 3 vs. 2 small-sided games. The results showed that the self-control group requested feedback mostly after good trials, that is, after they scored a goal. In addition, the perceived performance of the self-control group was higher on feedback than on no-feedback trials. Analyses of the conversations around the video feedback revealed that the players and coach discussed good and poor elements of performance and how to improve it. Although the coach had a major role in these conversations, the players of the self-control group spoke more and showed more initiative compared to the yoked group. The results revealed no significant beneficial effect of self-controlled feedback on performance as judged by the coach. Overall, the findings suggest that in such a complex situation as small-sided soccer games, self-controlled feedback is used both to confirm correct performance elements and to determine and correct errors, and that self-controlled learning stimulates the involvement of the learner in the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks.

PubMed

Hovakimyan, N; Nardi, F; Calise, A; Kim, Nakwan

2002-01-01

We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.

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.

Modeling, Control, and Estimation of Flexible, Aerodynamic Structures

NASA Astrophysics Data System (ADS)

Ray, Cody W.

Engineers have long been inspired by nature’s flyers. Such animals navigate complex environments gracefully and efficiently by using a variety of evolutionary adaptations for high-performance flight. Biologists have discovered a variety of sensory adaptations that provide flow state feedback and allow flying animals to feel their way through flight. A specialized skeletal wing structure and plethora of robust, adaptable sensory systems together allow nature’s flyers to adapt to myriad flight conditions and regimes. In this work, motivated by biology and the successes of bio-inspired, engineered aerial vehicles, linear quadratic control of a flexible, morphing wing design is investigated, helping to pave the way for truly autonomous, mission-adaptive craft. The proposed control algorithm is demonstrated to morph a wing into desired positions. Furthermore, motivated specifically by the sensory adaptations organisms possess, this work transitions to an investigation of aircraft wing load identification using structural response as measured by distributed sensors. A novel, recursive estimation algorithm is utilized to recursively solve the inverse problem of load identification, providing both wing structural and aerodynamic states for use in a feedback control, mission-adaptive framework. The recursive load identification algorithm is demonstrated to provide accurate load estimate in both simulation and experiment.

Feedback Control of Unsteady Flow and Vortex-Induced Vibration

NASA Astrophysics Data System (ADS)

Jaiman, Rajeev; Yao, Weigang

2017-11-01

We present an active feedback blowing and suction (AFBS) procedure via model reduction for unsteady wake flow and the vortex-induced vibration (VIV) of circular cylinders. The reduced-order model (ROM) for the AFBS procedure is developed by the eigensystem realization (ERA) algorithm, which provides a low-order representation of the unsteady flow dynamics in the neighbourhood of the equilibrium steady state. The actuation is considered via vertical suction and blowing jet at the porous surface of a circular cylinder with a body mounted force sensor. The resulting controller designed by linear low-order approximation is able to suppress the nonlinear saturated state. A systematic linear ROM-based stability analysis is performed to understand the eigenvalue distributions of elastically mounted circular cylinders. The results from the ROM analysis are consistent with those obtained from full nonlinear fluid-structure interaction simulations. A sensitivity study on the number of suction/blowing actuators, the angular arrangement of actuators, and the combined versus independent control architectures has been performed. Overall, the proposed control is found to be effective in suppressing the vortex street and the VIV for a range of reduced velocities and mass ratios.

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.

Using interpersonal affect regulation in simulated healthcare consultations: an experimental investigation of self-control resource depletion.

PubMed

Martínez-Íñigo, David; Mercado, Francisco; Totterdell, Peter

2015-01-01

Controlled Interpersonal Affect Regulation -the process of deliberately influencing the internal feeling states of others- occurs in a variety of interpersonal relationships and contexts. An incipient corpus of research shows that interpersonal affect regulation can be characterized as a goal-directed behavior that uses self-control processes which, according to the strength model of self-regulation, consumes a limited resource that is also used by other self-control processes. Using interpersonal affect-improving and affect-worsening regulation strategies can increase agent's resource depletion but there is reason to think that effects will partially rely on target's feedback in response to the regulation. Using a healthcare paradigm, an experiment was conducted to test the combined effects of interpersonal affect regulation use and patient feedback on healthcare workers' resource depletion, measured as self-reported experienced and expected emotional exhaustion, and persistence on a self-regulation task. Medical students (N = 78) were randomly assigned to a 2(interpersonal affect regulation: affect-worsening vs. affect-improving) × 2(patients' feedback: positive vs. negative) factorial between-subjects design and given instructions to play the role of doctors in interactions with two professional actors trained to act as patients. Analysis of covariance showed that affect-worsening was more depleting than affect-improving for all measures, whereas the recovery effects of positive feedback varied depending on strategy type and measure. The findings confirm the characterization of interpersonal affect regulation as potentially depleting, but suggest that the correspondence between the agent's strategy and the target's response needs to be taken into consideration. Use of affect-improving and positive feedback showed positive effects on self-rated performance, indicating that interpersonal affect regulation is relevant for organizational as well as personal outcomes.

Antithetic proportional-integral feedback for reduced variance and improved control performance of stochastic reaction networks.

PubMed

Briat, Corentin; Gupta, Ankit; Khammash, Mustafa

2018-06-01

The ability of a cell to regulate and adapt its internal state in response to unpredictable environmental changes is called homeostasis and this ability is crucial for the cell's survival and proper functioning. Understanding how cells can achieve homeostasis, despite the intrinsic noise or randomness in their dynamics, is fundamentally important for both systems and synthetic biology. In this context, a significant development is the proposed antithetic integral feedback (AIF) motif, which is found in natural systems, and is known to ensure robust perfect adaptation for the mean dynamics of a given molecular species involved in a complex stochastic biomolecular reaction network. From the standpoint of applications, one drawback of this motif is that it often leads to an increased cell-to-cell heterogeneity or variance when compared to a constitutive (i.e. open-loop) control strategy. Our goal in this paper is to show that this performance deterioration can be countered by combining the AIF motif and a negative feedback strategy. Using a tailored moment closure method, we derive approximate expressions for the stationary variance for the controlled network that demonstrate that increasing the strength of the negative feedback can indeed decrease the variance, sometimes even below its constitutive level. Numerical results verify the accuracy of these results and we illustrate them by considering three biomolecular networks with two types of negative feedback strategies. Our computational analysis indicates that there is a trade-off between the speed of the settling-time of the mean trajectories and the stationary variance of the controlled species; i.e. smaller variance is associated with larger settling-time. © 2018 The Author(s).

Using interpersonal affect regulation in simulated healthcare consultations: an experimental investigation of self-control resource depletion

PubMed Central

Martínez-Íñigo, David; Mercado, Francisco; Totterdell, Peter

2015-01-01

Controlled Interpersonal Affect Regulation –the process of deliberately influencing the internal feeling states of others– occurs in a variety of interpersonal relationships and contexts. An incipient corpus of research shows that interpersonal affect regulation can be characterized as a goal-directed behavior that uses self-control processes which, according to the strength model of self-regulation, consumes a limited resource that is also used by other self-control processes. Using interpersonal affect-improving and affect-worsening regulation strategies can increase agent’s resource depletion but there is reason to think that effects will partially rely on target’s feedback in response to the regulation. Using a healthcare paradigm, an experiment was conducted to test the combined effects of interpersonal affect regulation use and patient feedback on healthcare workers’ resource depletion, measured as self-reported experienced and expected emotional exhaustion, and persistence on a self-regulation task. Medical students (N = 78) were randomly assigned to a 2(interpersonal affect regulation: affect-worsening vs. affect-improving) × 2(patients’ feedback: positive vs. negative) factorial between-subjects design and given instructions to play the role of doctors in interactions with two professional actors trained to act as patients. Analysis of covariance showed that affect-worsening was more depleting than affect-improving for all measures, whereas the recovery effects of positive feedback varied depending on strategy type and measure. The findings confirm the characterization of interpersonal affect regulation as potentially depleting, but suggest that the correspondence between the agent’s strategy and the target’s response needs to be taken into consideration. Use of affect-improving and positive feedback showed positive effects on self-rated performance, indicating that interpersonal affect regulation is relevant for organizational as well as personal outcomes. PMID:26483737

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.

A Direct Adaptive Control Approach in the Presence of Model Mismatch

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.; Tao, Gang; Khong, Thuan

2009-01-01

This paper considers the problem of direct model reference adaptive control when the plant-model matching conditions are violated due to abnormal changes in the plant or incorrect knowledge of the plant's mathematical structure. The approach consists of direct adaptation of state feedback gains for state tracking, and simultaneous estimation of the plant-model mismatch. Because of the mismatch, the plant can no longer track the state of the original reference model, but may be able to track a new reference model that still provides satisfactory performance. The reference model is updated if the estimated plant-model mismatch exceeds a bound that is determined via robust stability and/or performance criteria. The resulting controller is a hybrid direct-indirect adaptive controller that offers asymptotic state tracking in the presence of plant-model mismatch as well as parameter deviations.