Backstepping Design of Adaptive Neural Fault-Tolerant Control for MIMO Nonlinear Systems.
Gao, Hui; Song, Yongduan; Wen, Changyun
In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.
On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2011-01-01
This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.
Shi, Wuxi; Luo, Rui; Li, Baoquan
2017-01-01
In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Khazaee, Mostafa; Markazi, Amir H D; Omidi, Ehsan
2015-11-01
In this paper, a new Adaptive Fuzzy Predictive Sliding Mode Control (AFP-SMC) is presented for nonlinear systems with uncertain dynamics and unknown input delay. The control unit consists of a fuzzy inference system to approximate the ideal linearization control, together with a switching strategy to compensate for the estimation errors. Also, an adaptive fuzzy predictor is used to estimate the future values of the system states to compensate for the time delay. The adaptation laws are used to tune the controller and predictor parameters, which guarantee the stability based on a Lyapunov-Krasovskii functional. To evaluate the method effectiveness, the simulation and experiment on an overhead crane system are presented. According to the obtained results, AFP-SMC can effectively control the uncertain nonlinear systems, subject to input delays of known bound. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Hybrid supervisory control using recurrent fuzzy neural network for tracking periodic inputs.
Lin, F J; Wai, R J; Hong, C M
2001-01-01
A hybrid supervisory control system using a recurrent fuzzy neural network (RFNN) is proposed to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive for the tracking of periodic reference inputs. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMLSM. Then, a hybrid supervisory control system, which combines a supervisory control system and an intelligent control system, is proposed to control the mover of the PMLSM for periodic motion. The supervisory control law is designed based on the uncertainty bounds of the controlled system to stabilize the system states around a predefined bound region. Since the supervisory control law will induce excessive and chattering control effort, the intelligent control system is introduced to smooth and reduce the control effort when the system states are inside the predefined bound region. In the intelligent control system, the RFNN control is the main tracking controller which is used to mimic a idea control law and a compensated control is proposed to compensate the difference between the idea control law and the RFNN control. The RFNN has the merits of fuzzy inference, dynamic mapping and fast convergence speed, In addition, an online parameter training methodology, which is derived using the Lyapunov stability theorem and the gradient descent method, is proposed to increase the learning capability of the RFNN. The proposed hybrid supervisory control system using RFNN can track various periodic reference inputs effectively with robust control performance.
Adaptive control of a quadrotor aerial vehicle with input constraints and uncertain parameters
NASA Astrophysics Data System (ADS)
Tran, Trong-Toan; Ge, Shuzhi Sam; He, Wei
2018-05-01
In this paper, we address the problem of adaptive bounded control for the trajectory tracking of a Quadrotor Aerial Vehicle (QAV) while the input saturations and uncertain parameters with the known bounds are simultaneously taken into account. First, to deal with the underactuated property of the QAV model, we decouple and construct the QAV model as a cascaded structure which consists of two fully actuated subsystems. Second, to handle the input constraints and uncertain parameters, we use a combination of the smooth saturation function and smooth projection operator in the control design. Third, to ensure the stability of the overall system of the QAV, we develop the technique for the cascaded system in the presence of both the input constraints and uncertain parameters. Finally, the region of stability of the closed-loop system is constructed explicitly, and our design ensures the asymptotic convergence of the tracking errors to the origin. The simulation results are provided to illustrate the effectiveness of the proposed method.
Effects of control inputs on the estimation of stability and control parameters of a light airplane
NASA Technical Reports Server (NTRS)
Cannaday, R. L.; Suit, W. T.
1977-01-01
The maximum likelihood parameter estimation technique was used to determine the values of stability and control derivatives from flight test data for a low-wing, single-engine, light airplane. Several input forms were used during the tests to investigate the consistency of parameter estimates as it relates to inputs. These consistencies were compared by using the ensemble variance and estimated Cramer-Rao lower bound. In addition, the relationship between inputs and parameter correlations was investigated. Results from the stabilator inputs are inconclusive but the sequence of rudder input followed by aileron input or aileron followed by rudder gave more consistent estimates than did rudder or ailerons individually. Also, square-wave inputs appeared to provide slightly improved consistency in the parameter estimates when compared to sine-wave inputs.
Ye, Dan; Chen, Mengmeng; Li, Kui
2017-11-01
In this paper, we consider the distributed containment control problem of multi-agent systems with actuator bias faults based on observer method. The objective is to drive the followers into the convex hull spanned by the dynamic leaders, where the input is unknown but bounded. By constructing an observer to estimate the states and bias faults, an effective distributed adaptive fault-tolerant controller is developed. Different from the traditional method, an auxiliary controller gain is designed to deal with the unknown inputs and bias faults together. Moreover, the coupling gain can be adjusted online through the adaptive mechanism without using the global information. Furthermore, the proposed control protocol can guarantee that all the signals of the closed-loop systems are bounded and all the followers converge to the convex hull with bounded residual errors formed by the dynamic leaders. Finally, a decoupled linearized longitudinal motion model of the F-18 aircraft is used to demonstrate the effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam
2009-01-01
This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.
Robust stability bounds for multi-delay networked control systems
NASA Astrophysics Data System (ADS)
Seitz, Timothy; Yedavalli, Rama K.; Behbahani, Alireza
2018-04-01
In this paper, the robust stability of a perturbed linear continuous-time system is examined when controlled using a sampled-data networked control system (NCS) framework. Three new robust stability bounds on the time-invariant perturbations to the original continuous-time plant matrix are presented guaranteeing stability for the corresponding discrete closed-loop augmented delay-free system (ADFS) with multiple time-varying sensor and actuator delays. The bounds are differentiated from previous work by accounting for the sampled-data nature of the NCS and for separate communication delays for each sensor and actuator, not a single delay. Therefore, this paper expands the knowledge base in multiple inputs multiple outputs (MIMO) sampled-data time delay systems. Bounds are presented for unstructured, semi-structured, and structured perturbations.
Statistical plant set estimation using Schroeder-phased multisinusoidal input design
NASA Technical Reports Server (NTRS)
Bayard, D. S.
1992-01-01
A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.
Finite-time H∞ control for linear continuous system with norm-bounded disturbance
NASA Astrophysics Data System (ADS)
Meng, Qingyi; Shen, Yanjun
2009-04-01
In this paper, the definition of finite-time H∞ control is presented. The system under consideration is subject to time-varying norm-bounded exogenous disturbance. The main aim of this paper is focused on the design a state feedback controller which ensures that the closed-loop system is finite-time bounded (FTB) and reduces the effect of the disturbance input on the controlled output to a prescribed level. A sufficient condition is presented for the solvability of this problem, which can be reduced to a feasibility problem involving linear matrix inequalities (LMIs). A detailed solving method is proposed for the restricted linear matrix inequalities. Finally, examples are given to show the validity of the methodology.
Hu, Qinglei
2007-10-01
This paper presents a dual-stage control system design method for the flexible spacecraft attitude maneuvering control by use of on-off thrusters and active vibration control by input shaper. In this design approach, attitude control system and vibration suppression were designed separately using lower order model. As a stepping stone, an integral variable structure controller with the assumption of knowing the upper bounds of the mismatched lumped perturbation has been designed which ensures exponential convergence of attitude angle and angular velocity in the presence of bounded uncertainty/disturbances. To reconstruct estimates of the system states for use in a full information variable structure control law, an asymptotic variable structure observer is also employed. In addition, the thruster output is modulated in pulse-width pulse-frequency so that the output profile is similar to the continuous control histories. For actively suppressing the induced vibration, the input shaping technique is used to modify the existing command so that less vibration will be caused by the command itself, which only requires information about the vibration frequency and damping of the closed-loop system. The rationale behind this hybrid control scheme is that the integral variable structure controller can achieve good precision pointing, even in the presence of uncertainties/disturbances, whereas the shaped input attenuator is applied to actively suppress the undesirable vibrations excited by the rapid maneuvers. Simulation results for the spacecraft model show precise attitude control and vibration suppression.
Command Filtering-Based Fuzzy Control for Nonlinear Systems With Saturation Input.
Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Lin, Chong
2017-09-01
In this paper, command filtering-based fuzzy control is designed for uncertain multi-input multioutput (MIMO) nonlinear systems with saturation nonlinearity input. First, the command filtering method is employed to deal with the explosion of complexity caused by the derivative of virtual controllers. Then, fuzzy logic systems are utilized to approximate the nonlinear functions of MIMO systems. Furthermore, error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. The developed method will guarantee all signals of the systems are bounded. The effectiveness and advantages of the theoretic result are obtained by a simulation example.
Wang, Huanqing; Chen, Bing; Liu, Xiaoping; Liu, Kefu; Lin, Chong
2013-12-01
This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.
New control concepts for uncertain water resources systems: 1. Theory
NASA Astrophysics Data System (ADS)
Georgakakos, Aris P.; Yao, Huaming
1993-06-01
A major complicating factor in water resources systems management is handling unknown inputs. Stochastic optimization provides a sound mathematical framework but requires that enough data exist to develop statistical input representations. In cases where data records are insufficient (e.g., extreme events) or atypical of future input realizations, stochastic methods are inadequate. This article presents a control approach where input variables are only expected to belong in certain sets. The objective is to determine sets of admissible control actions guaranteeing that the system will remain within desirable bounds. The solution is based on dynamic programming and derived for the case where all sets are convex polyhedra. A companion paper (Yao and Georgakakos, this issue) addresses specific applications and problems in relation to reservoir system management.
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Rosen, I. G.
1987-01-01
The approximation of optimal discrete-time linear quadratic Gaussian (LQG) compensators for distributed parameter control systems with boundary input and unbounded measurement is considered. The approach applies to a wide range of problems that can be formulated in a state space on which both the discrete-time input and output operators are continuous. Approximating compensators are obtained via application of the LQG theory and associated approximation results for infinite dimensional discrete-time control systems with bounded input and output. Numerical results for spline and modal based approximation schemes used to compute optimal compensators for a one dimensional heat equation with either Neumann or Dirichlet boundary control and pointwise measurement of temperature are presented and discussed.
Wang, Jianhui; Liu, Zhi; Chen, C L Philip; Zhang, Yun
2017-10-12
Hysteresis exists ubiquitously in physical actuators. Besides, actuator failures/faults may also occur in practice. Both effects would deteriorate the transient tracking performance, and even trigger instability. In this paper, we consider the problem of compensating for actuator failures and input hysteresis by proposing a fuzzy control scheme for stochastic nonlinear systems. Compared with the existing research on stochastic nonlinear uncertain systems, it is found that how to guarantee a prescribed transient tracking performance when taking into account actuator failures and hysteresis simultaneously also remains to be answered. Our proposed control scheme is designed on the basis of the fuzzy logic system and backstepping techniques for this purpose. It is proven that all the signals remain bounded and the tracking error is ensured to be within a preestablished bound with the failures of hysteretic actuator. Finally, simulations are provided to illustrate the effectiveness of the obtained theoretical results.
Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang
2017-07-01
This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.
NASA Technical Reports Server (NTRS)
Desoer, C. A.; Polak, E.; Zadeh, L. A.
1974-01-01
A series of research projects is briefly summarized which includes investigations in the following areas: (1) mathematical programming problems for large system and infinite-dimensional spaces, (2) bounded-input bounded-output stability, (3) non-parametric approximations, and (4) differential games. A list of reports and papers which were published over the ten year period of research is included.
NASA Astrophysics Data System (ADS)
Chen, Chao; Liu, Qian; Zhao, Jun
2018-01-01
This paper studies the problem of stabilisation of switched nonlinear systems with output and input constraints. We propose a recursive approach to solve this issue. None of the subsystems are assumed to be stablisable while the switched system is stabilised by dual design of controllers for subsystems and a switching law. When only dealing with bounded input, we provide nested switching controllers using an extended backstepping procedure. If both input and output constraints are taken into consideration, a Barrier Lyapunov Function is employed during operation to construct multiple Lyapunov functions for switched nonlinear system in the backstepping procedure. As a practical example, the control design of an equilibrium manifold expansion model of aero-engine is given to demonstrate the effectiveness of the proposed design method.
Ghabraei, Soheil; Moradi, Hamed; Vossoughi, Gholamreza
2015-09-01
To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler-turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler-turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input-output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Lu, Jianbo; Li, Dewei; Xi, Yugeng
2013-07-01
This article is concerned with probability-based constrained model predictive control (MPC) for systems with both structured uncertainties and time delays, where a random input delay and multiple fixed state delays are included. The process of input delay is governed by a discrete-time finite-state Markov chain. By invoking an appropriate augmented state, the system is transformed into a standard structured uncertain time-delay Markov jump linear system (MJLS). For the resulting system, a multi-step feedback control law is utilised to minimise an upper bound on the expected value of performance objective. The proposed design has been proved to stabilise the closed-loop system in the mean square sense and to guarantee constraints on control inputs and system states. Finally, a numerical example is given to illustrate the proposed results.
Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.
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.
VC-dimension of univariate decision trees.
Yildiz, Olcay Taner
2015-02-01
In this paper, we give and prove the lower bounds of the Vapnik-Chervonenkis (VC)-dimension of the univariate decision tree hypothesis class. The VC-dimension of the univariate decision tree depends on the VC-dimension values of its subtrees and the number of inputs. Via a search algorithm that calculates the VC-dimension of univariate decision trees exhaustively, we show that our VC-dimension bounds are tight for simple trees. To verify that the VC-dimension bounds are useful, we also use them to get VC-generalization bounds for complexity control using structural risk minimization in decision trees, i.e., pruning. Our simulation results show that structural risk minimization pruning using the VC-dimension bounds finds trees that are more accurate as those pruned using cross validation.
A control problem for Burgers' equation with bounded input/output
NASA Technical Reports Server (NTRS)
Burns, John A.; Kang, Sungkwon
1990-01-01
A stabilization problem for Burgers' equation is considered. Using linearization, various controllers are constructed which minimize certain weighted energy functionals. These controllers produce the desired degree of stability for the closed-loop nonlinear system. A numerical scheme for computing the feedback gain functional is developed and several numerical experiments are performed to show the theoretical results.
Adaptive Fuzzy Bounded Control for Consensus of Multiple Strict-Feedback Nonlinear Systems.
Wang, Wei; Tong, Shaocheng
2018-02-01
This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different from the existing results, the bounds of the control inputs are known as a priori, and they can be determined by the feedback control gains. To realize smooth and fast learning, a predictor is introduced to estimate each error surface, and the corresponding predictor error is employed to learn the optimal fuzzy parameter vector. It is proved that the developed adaptive fuzzy control scheme guarantees the uniformly ultimate boundedness of the closed-loop systems, and the tracking error converges to a small neighborhood of the origin. The simulation results and comparisons are provided to show the validity of the control strategy presented in this paper.
Performance bounds for nonlinear systems with a nonlinear ℒ2-gain property
NASA Astrophysics Data System (ADS)
Zhang, Huan; Dower, Peter M.
2012-09-01
Nonlinear ℒ2-gain is a finite gain concept that generalises the notion of conventional (linear) finite ℒ2-gain to admit the application of ℒ2-gain analysis tools of a broader class of nonlinear systems. The computation of tight comparison function bounds for this nonlinear ℒ2-gain property is important in applications such as small gain design. This article presents an approximation framework for these comparison function bounds through the formulation and solution of an optimal control problem. Key to the solution of this problem is the lifting of an ℒ2-norm input constraint, which is facilitated via the introduction of an energy saturation operator. This admits the solution of the optimal control problem of interest via dynamic programming and associated numerical methods, leading to the computation of the proposed bounds. Two examples are presented to demonstrate this approach.
Alaoui-Mhamdi, Mohamed; Dhib, Amel; Bouhaddioui, Abderrahim; Ziadi, Boutheina; Turki, Souad; Aleya, Lotfi
2014-09-01
Balances of nitrogen and phosphate were studied in the Allal El Fassi reservoir (Morocco); the results showing that nitrogen input (296 mg m(-2) d(-1)) was 161% higher than output (183 mg m(-2) d(-1)). Phosphate input (35.65 mg m(-2) d(-1)) was 865% higher than output (4.12 mg m(-2) d(-1)), causing a progressive increase in the internal phosphate stock. Sedimentation flux was equally high (53.80 and 18 mg m(-2) d(-1)) for both nitrogen and phosphate input, mainly from the Sebou River and in particulate form which immediately settles upon arrival in the reservoir. The release of nitrogen and phosphate from the sediment (5.40 and 1.15 mg m(-2) d(-1), respectively) depended on physicochemical and biological (bacteria and viruses) variability and the calcareous nature of the catchment basin. Calcium-bound phosphate prevailed in the reservoir. Drastic control of phosphate input is suggested to avoid accumulation of calcium-bound phosphate which may dissociate and thereby contribute to eutrophication.
Wang, Yingyang; Hu, Jianbo
2018-05-19
An improved prescribed performance controller is proposed for the longitudinal model of an air-breathing hypersonic vehicle (AHV) subject to uncertain dynamics and input nonlinearity. Different from the traditional non-affine model requiring non-affine functions to be differentiable, this paper utilizes a semi-decomposed non-affine model with non-affine functions being locally semi-bounded and possibly in-differentiable. A new error transformation combined with novel prescribed performance functions is proposed to bypass complex deductions caused by conventional error constraint approaches and circumvent high frequency chattering in control inputs. On the basis of backstepping technique, the improved prescribed performance controller with low structural and computational complexity is designed. The methodology guarantees the altitude and velocity tracking error within transient and steady state performance envelopes and presents excellent robustness against uncertain dynamics and deadzone input nonlinearity. Simulation results demonstrate the efficacy of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Xia, Kewei; Huo, Wei
2016-05-01
This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.
Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong
2017-10-01
This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.
Robust fault-tolerant tracking control design for spacecraft under control input saturation.
Bustan, Danyal; Pariz, Naser; Sani, Seyyed Kamal Hosseini
2014-07-01
In this paper, a continuous globally stable tracking control algorithm is proposed for a spacecraft in the presence of unknown actuator failure, control input saturation, uncertainty in inertial matrix and external disturbances. The design method is based on variable structure control and has the following properties: (1) fast and accurate response in the presence of bounded disturbances; (2) robust to the partial loss of actuator effectiveness; (3) explicit consideration of control input saturation; and (4) robust to uncertainty in inertial matrix. In contrast to traditional fault-tolerant control methods, the proposed controller does not require knowledge of the actuator faults and is implemented without explicit fault detection and isolation processes. In the proposed controller a single parameter is adjusted dynamically in such a way that it is possible to prove that both attitude and angular velocity errors will tend to zero asymptotically. The stability proof is based on a Lyapunov analysis and the properties of the singularity free quaternion representation of spacecraft dynamics. Results of numerical simulations state that the proposed controller is successful in achieving high attitude performance in the presence of external disturbances, actuator failures, and control input saturation. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.
Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip
2015-05-01
An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.
Time-response shaping using output to input saturation transformation
NASA Astrophysics Data System (ADS)
Chambon, E.; Burlion, L.; Apkarian, P.
2018-03-01
For linear systems, the control law design is often performed so that the resulting closed loop meets specific frequency-domain requirements. However, in many cases, it may be observed that the obtained controller does not enforce time-domain requirements amongst which the objective of keeping a scalar output variable in a given interval. In this article, a transformation is proposed to convert prescribed bounds on an output variable into time-varying saturations on the synthesised linear scalar control law. This transformation uses some well-chosen time-varying coefficients so that the resulting time-varying saturation bounds do not overlap in the presence of disturbances. Using an anti-windup approach, it is obtained that the origin of the resulting closed loop is globally asymptotically stable and that the constrained output variable satisfies the time-domain constraints in the presence of an unknown finite-energy-bounded disturbance. An application to a linear ball and beam model is presented.
Robust Controller Design: A Bounded-Input-Bounded-Output Worst-Case Approach
1992-03-01
show that 2 implies 1, suppose 1 does not hold, i.e., that p(M) > 1. The Perron - Frobenius theory for nonnegative matrices states that p(M) is itself an...Pz denote the positive cones inside X, Z consisting of elements with nonnegative pointwise components. Define the operator .4 : X -* Z, decomposed...topology.) The dual cone P! again consists of the nonnegative elements in Z*. The Lagrangian can be defined as L(x,z ’) {< x,c" > + < Ax - b,z
Robust synergetic control design under inputs and states constraints
NASA Astrophysics Data System (ADS)
Rastegar, Saeid; Araújo, Rui; Sadati, Jalil
2018-03-01
In this paper, a novel robust-constrained control methodology for discrete-time linear parameter-varying (DT-LPV) systems is proposed based on a synergetic control theory (SCT) approach. It is shown that in DT-LPV systems without uncertainty, and for any unmeasured bounded additive disturbance, the proposed controller accomplishes the goal of stabilising the system by asymptotically driving the error of the controlled variable to a bounded set containing the origin and then maintaining it there. Moreover, given an uncertain DT-LPV system jointly subject to unmeasured and constrained additive disturbances, and constraints in states, input commands and reference signals (set points), then invariant set theory is used to find an appropriate polyhedral robust invariant region in which the proposed control framework is guaranteed to robustly stabilise the closed-loop system. Furthermore, this is achieved even for the case of varying non-zero control set points in such uncertain DT-LPV systems. The controller is characterised to have a simple structure leading to an easy implementation, and a non-complex design process. The effectiveness of the proposed method and the implications of the controller design on feasibility and closed-loop performance are demonstrated through application examples on the temperature control on a continuous-stirred tank reactor plant, on the control of a real-coupled DC motor plant, and on an open-loop unstable system example.
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.
An-Min Zou; Kumar, K D; Zeng-Guang Hou; Xi Liu
2011-08-01
A finite-time attitude tracking control scheme is proposed for spacecraft using terminal sliding mode and Chebyshev neural network (NN) (CNN). The four-parameter representations (quaternion) are used to describe the spacecraft attitude for global representation without singularities. The attitude state (i.e., attitude and velocity) error dynamics is transformed to a double integrator dynamics with a constraint on the spacecraft attitude. With consideration of this constraint, a novel terminal sliding manifold is proposed for the spacecraft. In order to guarantee that the output of the NN used in the controller is bounded by the corresponding bound of the approximated unknown function, a switch function is applied to generate a switching between the adaptive NN control and the robust controller. Meanwhile, a CNN, whose basis functions are implemented using only desired signals, is introduced to approximate the desired nonlinear function and bounded external disturbances online, and the robust term based on the hyperbolic tangent function is applied to counteract NN approximation errors in the adaptive neural control scheme. Most importantly, the finite-time stability in both the reaching phase and the sliding phase can be guaranteed by a Lyapunov-based approach. Finally, numerical simulations on the attitude tracking control of spacecraft in the presence of an unknown mass moment of inertia matrix, bounded external disturbances, and control input constraints are presented to demonstrate the performance of the proposed controller.
Plant Growth and Phosphorus Uptake of Three Riparian Grass Species
USDA-ARS?s Scientific Manuscript database
Riparian buffers can significantly reduce sediment-bound phosphorus (P) entering surface water, but control of dissolved P inputs is more challenging. Because plant roots remove P from soil solution, it follows that plant uptake will reduce dissolved P losses. We evaluated P uptake of smooth bromegr...
Output feedback control of a quadrotor UAV using neural networks.
Dierks, Travis; Jagannathan, Sarangapani
2010-01-01
In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.
Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong
2011-12-01
In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.
A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.
Leibfried, Felix; Braun, Daniel A
2015-08-01
Rate distortion theory describes how to communicate relevant information most efficiently over a channel with limited capacity. One of the many applications of rate distortion theory is bounded rational decision making, where decision makers are modeled as information channels that transform sensory input into motor output under the constraint that their channel capacity is limited. Such a bounded rational decision maker can be thought to optimize an objective function that trades off the decision maker's utility or cumulative reward against the information processing cost measured by the mutual information between sensory input and motor output. In this study, we interpret a spiking neuron as a bounded rational decision maker that aims to maximize its expected reward under the computational constraint that the mutual information between the neuron's input and output is upper bounded. This abstract computational constraint translates into a penalization of the deviation between the neuron's instantaneous and average firing behavior. We derive a synaptic weight update rule for such a rate distortion optimizing neuron and show in simulations that the neuron efficiently extracts reward-relevant information from the input by trading off its synaptic strengths against the collected reward.
Li, Zhijun; Su, Chun-Yi
2013-09-01
In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.
Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2017-11-01
A neural network (NN) adaptive control design problem is addressed for a class of uncertain multi-input-multi-output (MIMO) nonlinear systems in block-triangular form. The considered systems contain uncertainty dynamics and their states are enforced to subject to bounded constraints as well as the couplings among various inputs and outputs are inserted in each subsystem. To stabilize this class of systems, a novel adaptive control strategy is constructively framed by using the backstepping design technique and NNs. The novel integral barrier Lyapunov functionals (BLFs) are employed to overcome the violation of the full state constraints. The proposed strategy can not only guarantee the boundedness of the closed-loop system and the outputs are driven to follow the reference signals, but also can ensure all the states to remain in the predefined compact sets. Moreover, the transformed constraints on the errors are used in the previous BLF, and accordingly it is required to determine clearly the bounds of the virtual controllers. Thus, it can relax the conservative limitations in the traditional BLF-based controls for the full state constraints. This conservatism can be solved in this paper and it is for the first time to control this class of MIMO systems with the full state constraints. The performance of the proposed control strategy can be verified through a simulation example.
NASA Astrophysics Data System (ADS)
Song, Rui-Zhuo; Xiao, Wen-Dong; Wei, Qing-Lai
2014-05-01
We develop an online adaptive dynamic programming (ADP) based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.
NASA Technical Reports Server (NTRS)
Rhee, Ihnseok; Speyer, Jason L.
1990-01-01
A game theoretic controller is developed for a linear time-invariant system with parameter uncertainties in system and input matrices. The input-output decomposition modeling for the plant uncertainty is adopted. The uncertain dynamic system is represented as an internal feedback loop in which the system is assumed forced by fictitious disturbance caused by the parameter uncertainty. By considering the input and the fictitious disturbance as two noncooperative players, a differential game problem is constructed. It is shown that the resulting time invariant controller stabilizes the uncertain system for a prescribed uncertainty bound. This game theoretic controller is applied to the momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Inclusion of the external disturbance torque to the design procedure results in a dynamical feedback controller which consists of conventional PID control and cyclic disturbance rejection filter. It is shown that the game theoretic design, comparing to the LQR design or pole placement design, improves the stability robustness with respect to inertia variations.
Distributed Optimal Consensus Control for Multiagent Systems With Input Delay.
Zhang, Huaipin; Yue, Dong; Zhao, Wei; Hu, Songlin; Dou, Chunxia; Huaipin Zhang; Dong Yue; Wei Zhao; Songlin Hu; Chunxia Dou; Hu, Songlin; Zhang, Huaipin; Dou, Chunxia; Yue, Dong; Zhao, Wei
2018-06-01
This paper addresses the problem of distributed optimal consensus control for a continuous-time heterogeneous linear multiagent system subject to time varying input delays. First, by discretization and model transformation, the continuous-time input-delayed system is converted into a discrete-time delay-free system. Two delicate performance index functions are defined for these two systems. It is shown that the performance index functions are equivalent and the optimal consensus control problem of the input-delayed system can be cast into that of the delay-free system. Second, by virtue of the Hamilton-Jacobi-Bellman (HJB) equations, an optimal control policy for each agent is designed based on the delay-free system and a novel value iteration algorithm is proposed to learn the solutions to the HJB equations online. The proposed adaptive dynamic programming algorithm is implemented on the basis of a critic-action neural network (NN) structure. Third, it is proved that local consensus errors of the two systems and weight estimation errors of the critic-action NNs are uniformly ultimately bounded while the approximated control policies converge to their target values. Finally, two simulation examples are presented to illustrate the effectiveness of the developed method.
Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.
Kiumarsi, Bahare; Lewis, Frank L
2015-01-01
This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Cui, Guozeng; Xu, Shengyuan; Ma, Qian; Li, Yongmin; Zhang, Zhengqiang
2018-05-01
In this paper, the problem of prescribed performance distributed output consensus for higher-order non-affine nonlinear multi-agent systems with unknown dead-zone input is investigated. Fuzzy logical systems are utilised to identify the unknown nonlinearities. By introducing prescribed performance, the transient and steady performance of synchronisation errors are guaranteed. Based on Lyapunov stability theory and the dynamic surface control technique, a new distributed consensus algorithm for non-affine nonlinear multi-agent systems is proposed, which ensures cooperatively uniformly ultimately boundedness of all signals in the closed-loop systems and enables the output of each follower to synchronise with the leader within predefined bounded error. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.
Li, Yongming; Tong, Shaocheng
2017-12-01
In this paper, an adaptive fuzzy output constrained control design approach is addressed for multi-input multioutput uncertain stochastic nonlinear systems in nonstrict-feedback form. The nonlinear systems addressed in this paper possess unstructured uncertainties, unknown gain functions and unknown stochastic disturbances. Fuzzy logic systems are utilized to tackle the problem of unknown nonlinear uncertainties. The barrier Lyapunov function technique is employed to solve the output constrained problem. In the framework of backstepping design, an adaptive fuzzy control design scheme is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.
Hybrid Decompositional Verification for Discovering Failures in Adaptive Flight Control Systems
NASA Technical Reports Server (NTRS)
Thompson, Sarah; Davies, Misty D.; Gundy-Burlet, Karen
2010-01-01
Adaptive flight control systems hold tremendous promise for maintaining the safety of a damaged aircraft and its passengers. However, most currently proposed adaptive control methodologies rely on online learning neural networks (OLNNs), which necessarily have the property that the controller is changing during the flight. These changes tend to be highly nonlinear, and difficult or impossible to analyze using standard techniques. In this paper, we approach the problem with a variant of compositional verification. The overall system is broken into components. Undesirable behavior is fed backwards through the system. Components which can be solved using formal methods techniques explicitly for the ranges of safe and unsafe input bounds are treated as white box components. The remaining black box components are analyzed with heuristic techniques that try to predict a range of component inputs that may lead to unsafe behavior. The composition of these component inputs throughout the system leads to overall system test vectors that may elucidate the undesirable behavior
Niu, Ben; Li, Lu
2018-06-01
This brief proposes a new neural-network (NN)-based adaptive output tracking control scheme for a class of disturbed multiple-input multiple-output uncertain nonlinear switched systems with input delays. By combining the universal approximation ability of radial basis function NNs and adaptive backstepping recursive design with an improved multiple Lyapunov function (MLF) scheme, a novel adaptive neural output tracking controller design method is presented for the switched system. The feature of the developed design is that different coordinate transformations are adopted to overcome the conservativeness caused by adopting a common coordinate transformation for all subsystems. It is shown that all the variables of the resulting closed-loop system are semiglobally uniformly ultimately bounded under a class of switching signals in the presence of MLF and that the system output can follow the desired reference signal. To demonstrate the practicability of the obtained result, an adaptive neural output tracking controller is designed for a mass-spring-damper system.
Observer-based state tracking control of uncertain stochastic systems via repetitive controller
NASA Astrophysics Data System (ADS)
Sakthivel, R.; Susana Ramya, L.; Selvaraj, P.
2017-08-01
This paper develops the repetitive control scheme for state tracking control of uncertain stochastic time-varying delay systems via equivalent-input-disturbance approach. The main purpose of this work is to design a repetitive controller to guarantee the tracking performance under the effects of unknown disturbances with bounded frequency and parameter variations. Specifically, a new set of linear matrix inequality (LMI)-based conditions is derived based on the suitable Lyapunov-Krasovskii functional theory for designing a repetitive controller which guarantees stability and desired tracking performance. More precisely, an equivalent-input-disturbance estimator is incorporated into the control design to reduce the effect of the external disturbances. Simulation results are provided to demonstrate the desired control system stability and their tracking performance. A practical stream water quality preserving system is also provided to show the effectiveness and advantage of the proposed approach.
A Note on the Disturbance Decoupling Problem for Retarded Systems.
1984-10-01
disturbance decoupling problem f or linear control system is to design a feedback control law in such a way that the disturbances do not * influence...and in 141 by Pandolfi who analyses the situation in some detail. HeU concludes that for retarded systems one needs an unbounded feedback control law...ult) 6 JP is the control input, d(t) 6 AR is same disturbance, and z(t) e 3k is the output to be regularted. We assume that L is a bounded linear
Computer program for single input-output, single-loop feedback systems
NASA Technical Reports Server (NTRS)
1976-01-01
Additional work is reported on a completely automatic computer program for the design of single input/output, single loop feedback systems with parameter uncertainly, to satisfy time domain bounds on the system response to step commands and disturbances. The inputs to the program are basically the specified time-domain response bounds, the form of the constrained plant transfer function and the ranges of the uncertain parameters of the plant. The program output consists of the transfer functions of the two free compensation networks, in the form of the coefficients of the numerator and denominator polynomials, and the data on the prescribed bounds and the extremes actually obtained for the system response to commands and disturbances.
Liu, Xiaoyang; Ho, Daniel W C; Cao, Jinde; Xu, Wenying
This brief investigates the problem of finite-time robust consensus (FTRC) for second-order nonlinear multiagent systems with external disturbances. Based on the global finite-time stability theory of discontinuous homogeneous systems, a novel finite-time convergent discontinuous disturbed observer (DDO) is proposed for the leader-following multiagent systems. The states of the designed DDO are then used to design the control inputs to achieve the FTRC of nonlinear multiagent systems in the presence of bounded disturbances. The simulation results are provided to validate the effectiveness of these theoretical results.This brief investigates the problem of finite-time robust consensus (FTRC) for second-order nonlinear multiagent systems with external disturbances. Based on the global finite-time stability theory of discontinuous homogeneous systems, a novel finite-time convergent discontinuous disturbed observer (DDO) is proposed for the leader-following multiagent systems. The states of the designed DDO are then used to design the control inputs to achieve the FTRC of nonlinear multiagent systems in the presence of bounded disturbances. The simulation results are provided to validate the effectiveness of these theoretical results.
Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai
2015-07-01
The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.
NASA Astrophysics Data System (ADS)
Bu, Xiangwei; Wu, Xiaoyan; He, Guangjun; Huang, Jiaqi
2016-03-01
This paper investigates the design of a novel adaptive neural controller for the longitudinal dynamics of a flexible air-breathing hypersonic vehicle with control input constraints. To reduce the complexity of controller design, the vehicle dynamics is decomposed into the velocity subsystem and the altitude subsystem, respectively. For each subsystem, only one neural network is utilized to approach the lumped unknown function. By employing a minimal-learning parameter method to estimate the norm of ideal weight vectors rather than their elements, there are only two adaptive parameters required for neural approximation. Thus, the computational burden is lower than the ones derived from neural back-stepping schemes. Specially, to deal with the control input constraints, additional systems are exploited to compensate the actuators. Lyapunov synthesis proves that all the closed-loop signals involved are uniformly ultimately bounded. Finally, simulation results show that the adopted compensation scheme can tackle actuator constraint effectively and moreover velocity and altitude can stably track their reference trajectories even when the physical limitations on control inputs are in effect.
A time delay controller for magnetic bearings
NASA Technical Reports Server (NTRS)
Youcef-Toumi, K.; Reddy, S.
1991-01-01
The control of systems with unknown dynamics and unpredictable disturbances has raised some challenging problems. This is particularly important when high system performance needs to be guaranteed at all times. Recently, the Time Delay Control has been suggested as an alternative control scheme. The proposed control system does not require an explicit plant model nor does it depend on the estimation of specific plant parameters. Rather, it combines adaptation with past observations to directly estimate the effect of the plant dynamics. A control law is formulated for a class of dynamic systems and a sufficient condition is presented for control systems stability. The derivation is based on the bounded input-bounded output stability approach using L sub infinity function norms. The control scheme is implemented on a five degrees of freedom high speed and high precision magnetic bearing. The control performance is evaluated using step responses, frequency responses, and disturbance rejection properties. The experimental data show an excellent control performance despite the system complexity.
Li, Dong-Juan; Li, Da-Peng
2017-09-14
In this paper, an adaptive output feedback control is framed for uncertain nonlinear discrete-time systems. The considered systems are a class of multi-input multioutput nonaffine nonlinear systems, and they are in the nested lower triangular form. Furthermore, the unknown dead-zone inputs are nonlinearly embedded into the systems. These properties of the systems will make it very difficult and challenging to construct a stable controller. By introducing a new diffeomorphism coordinate transformation, the controlled system is first transformed into a state-output model. By introducing a group of new variables, an input-output model is finally obtained. Based on the transformed model, the implicit function theorem is used to determine the existence of the ideal controllers and the approximators are employed to approximate the ideal controllers. By using the mean value theorem, the nonaffine functions of systems can become an affine structure but nonaffine terms still exist. The adaptation auxiliary terms are skillfully designed to cancel the effect of the dead-zone input. Based on the Lyapunov difference theorem, the boundedness of all the signals in the closed-loop system can be ensured and the tracking errors are kept in a bounded compact set. The effectiveness of the proposed technique is checked by a simulation study.
Decentralized model reference adaptive control of large flexible structures
NASA Technical Reports Server (NTRS)
Lee, Fu-Ming; Fong, I-Kong; Lin, Yu-Hwan
1988-01-01
A decentralized model reference adaptive control (DMRAC) method is developed for large flexible structures (LFS). The development follows that of a centralized model reference adaptive control for LFS that have been shown to be feasible. The proposed method is illustrated using a simply supported beam with collocated actuators and sensors. Results show that the DMRAC can achieve either output regulation or output tracking with adequate convergence, provided the reference model inputs and their time derivatives are integrable, bounded, and approach zero as t approaches infinity.
NASA Astrophysics Data System (ADS)
Hu, Qinglei
2010-02-01
Semi-globally input-to-state stable (ISS) control law is derived for flexible spacecraft attitude maneuvers in the presence of parameter uncertainties and external disturbances. The modified rodrigues parameters (MRP) are used as the kinematic variables since they are nonsingular for all possible rotations. This novel simple control is a proportional-plus-derivative (PD) type controller plus a sign function through a special Lyapunov function construction involving the sum of quadratic terms in the angular velocities, kinematic parameters, modal variables and the cross state weighting. A sufficient condition under which this nonlinear PD-type control law can render the system semi-globally input-to-state stable is provided such that the closed-loop system is robust with respect to any disturbance within a quantifiable restriction on the amplitude, as well as the set of initial conditions, if the control gains are designed appropriately. In addition to detailed derivations of the new controllers design and a rigorous sketch of all the associated stability and attitude convergence proofs, extensive simulation studies have been conducted to validate the design and the results are presented to highlight the ensuring closed-loop performance benefits when compared with the conventional control schemes.
Semi-active control of a cable-stayed bridge under multiple-support excitations.
Dai, Ze-Bing; Huang, Jin-Zhi; Wang, Hong-Xia
2004-03-01
This paper presents a semi-active strategy for seismic protection of a benchmark cable-stayed bridge with consideration of multiple-support excitations. In this control strategy, Magnetorheological (MR) dampers are proposed as control devices, a LQG-clipped-optimal control algorithm is employed. An active control strategy, shown in previous researches to perform well at controlling the benchmark bridge when uniform earthquake motion was assumed, is also used in this study to control this benchmark bridge with consideration of multiple-support excitations. The performance of active control system is compared to that of the presented semi-active control strategy. Because the MR fluid damper is a controllable energy- dissipation device that cannot add mechanical energy to the structural system, the proposed control strategy is fail-safe in that bounded-input, bounded-output stability of the controlled structure is guaranteed. The numerical results demonstrated that the performance of the presented control design is nearly the same as that of the active control system; and that the MR dampers can effectively be used to control seismically excited cable-stayed bridges with multiple-support excitations.
Liu, Yan-Jun; Tong, Shaocheng
2015-03-01
In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n-step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.
Safe Upper-Bounds Inference of Energy Consumption for Java Bytecode Applications
NASA Technical Reports Server (NTRS)
Navas, Jorge; Mendez-Lojo, Mario; Hermenegildo, Manuel V.
2008-01-01
Many space applications such as sensor networks, on-board satellite-based platforms, on-board vehicle monitoring systems, etc. handle large amounts of data and analysis of such data is often critical for the scientific mission. Transmitting such large amounts of data to the remote control station for analysis is usually too expensive for time-critical applications. Instead, modern space applications are increasingly relying on autonomous on-board data analysis. All these applications face many resource constraints. A key requirement is to minimize energy consumption. Several approaches have been developed for estimating the energy consumption of such applications (e.g. [3, 1]) based on measuring actual consumption at run-time for large sets of random inputs. However, this approach has the limitation that it is in general not possible to cover all possible inputs. Using formal techniques offers the potential for inferring safe energy consumption bounds, thus being specially interesting for space exploration and safety-critical systems. We have proposed and implemented a general frame- work for resource usage analysis of Java bytecode [2]. The user defines a set of resource(s) of interest to be tracked and some annotations that describe the cost of some elementary elements of the program for those resources. These values can be constants or, more generally, functions of the input data sizes. The analysis then statically derives an upper bound on the amount of those resources that the program as a whole will consume or provide, also as functions of the input data sizes. This article develops a novel application of the analysis of [2] to inferring safe upper bounds on the energy consumption of Java bytecode applications. We first use a resource model that describes the cost of each bytecode instruction in terms of the joules it consumes. With this resource model, we then generate energy consumption cost relations, which are then used to infer safe upper bounds. How energy consumption for each bytecode instruction is measured is beyond the scope of this paper. Instead, this paper is about how to infer safe energy consumption estimations assuming that those energy consumption costs are provided. For concreteness, we use a simplified version of an existing resource model [1] in which an energy consumption cost for individual Java opcodes is defined.
Localized modelling and feedback control of linear instabilities in 2-D wall bounded shear flows
NASA Astrophysics Data System (ADS)
Tol, Henry; Kotsonis, Marios; de Visser, Coen
2016-11-01
A new approach is presented for control of instabilities in 2-D wall bounded shear flows described by the linearized Navier-Stokes equations (LNSE). The control design accounts both for spatially localized actuators/sensors and the dominant perturbation dynamics in an optimal control framework. An inflow disturbance model is proposed for streamwise instabilities that drive laminar-turbulent transition. The perturbation modes that contribute to the transition process can be selected and are included in the control design. A reduced order model is derived from the LNSE that captures the input-output behavior and the dominant perturbation dynamics. This model is used to design an optimal controller for suppressing the instability growth. A 2-D channel flow and a 2-D boundary layer flow over a flat plate are considered as application cases. Disturbances are generated upstream of the control domain and the resulting flow perturbations are estimated/controlled using wall shear measurements and localized unsteady blowing and suction at the wall. It will be shown that the controller is able to cancel the perturbations and is robust to unmodelled disturbances.
Tian, Jiayi; Zhang, Shifeng; Zhang, Yinhui; Li, Tong
2018-03-01
Since motion control plant (y (n) =f(⋅)+d) was repeatedly used to exemplify how active disturbance rejection control (ADRC) works when it was proposed, the integral chain system subject to matched disturbances is always regarded as a canonical form and even misconstrued as the only form that ADRC is applicable to. In this paper, a systematic approach is first presented to apply ADRC to a generic nonlinear uncertain system with mismatched disturbances and a robust output feedback autopilot for an airbreathing hypersonic vehicle (AHV) is devised based on that. The key idea is to employ the feedback linearization (FL) and equivalent input disturbance (EID) technique to decouple nonlinear uncertain system into several subsystems in canonical form, thus it would be much easy to directly design classical/improved linear/nonlinear ADRC controller for each subsystem. It is noticed that all disturbances are taken into account when implementing FL rather than just omitting that in previous research, which greatly enhances controllers' robustness against external disturbances. For autopilot design, ADRC strategy enables precise tracking for velocity and altitude reference command in the presence of severe parametric perturbations and atmospheric disturbances only using measurable output information. Bounded-input-bounded-output (BIBO) stable is analyzed for closed-loop system. To illustrate the feasibility and superiority of this novel design, a series of comparative simulations with some prominent and representative methods are carried out on a benchmark longitudinal AHV model. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Generalized Hofmann quantum process fidelity bounds for quantum filters
NASA Astrophysics Data System (ADS)
Sedlák, Michal; Fiurášek, Jaromír
2016-04-01
We propose and investigate bounds on the quantum process fidelity of quantum filters, i.e., probabilistic quantum operations represented by a single Kraus operator K . These bounds generalize the Hofmann bounds on the quantum process fidelity of unitary operations [H. F. Hofmann, Phys. Rev. Lett. 94, 160504 (2005), 10.1103/PhysRevLett.94.160504] and are based on probing the quantum filter with pure states forming two mutually unbiased bases. Determination of these bounds therefore requires far fewer measurements than full quantum process tomography. We find that it is particularly suitable to construct one of the probe bases from the right eigenstates of K , because in this case the bounds are tight in the sense that if the actual filter coincides with the ideal one, then both the lower and the upper bounds are equal to 1. We theoretically investigate the application of these bounds to a two-qubit optical quantum filter formed by the interference of two photons on a partially polarizing beam splitter. For an experimentally convenient choice of factorized input states and measurements we study the tightness of the bounds. We show that more stringent bounds can be obtained by more sophisticated processing of the data using convex optimization and we compare our methods for different choices of the input probe states.
Leveraging Environmental Correlations: The Thermodynamics of Requisite Variety
NASA Astrophysics Data System (ADS)
Boyd, Alexander B.; Mandal, Dibyendu; Crutchfield, James P.
2017-06-01
Key to biological success, the requisite variety that confronts an adaptive organism is the set of detectable, accessible, and controllable states in its environment. We analyze its role in the thermodynamic functioning of information ratchets—a form of autonomous Maxwellian Demon capable of exploiting fluctuations in an external information reservoir to harvest useful work from a thermal bath. This establishes a quantitative paradigm for understanding how adaptive agents leverage structured thermal environments for their own thermodynamic benefit. General ratchets behave as memoryful communication channels, interacting with their environment sequentially and storing results to an output. The bulk of thermal ratchets analyzed to date, however, assume memoryless environments that generate input signals without temporal correlations. Employing computational mechanics and a new information-processing Second Law of Thermodynamics (IPSL) we remove these restrictions, analyzing general finite-state ratchets interacting with structured environments that generate correlated input signals. On the one hand, we demonstrate that a ratchet need not have memory to exploit an uncorrelated environment. On the other, and more appropriate to biological adaptation, we show that a ratchet must have memory to most effectively leverage structure and correlation in its environment. The lesson is that to optimally harvest work a ratchet's memory must reflect the input generator's memory. Finally, we investigate achieving the IPSL bounds on the amount of work a ratchet can extract from its environment, discovering that finite-state, optimal ratchets are unable to reach these bounds. In contrast, we show that infinite-state ratchets can go well beyond these bounds by utilizing their own infinite "negentropy". We conclude with an outline of the collective thermodynamics of information-ratchet swarms.
NASA Astrophysics Data System (ADS)
Cruz Jiménez, Miriam Guadalupe; Meyer Baese, Uwe; Jovanovic Dolecek, Gordana
2017-12-01
New theoretical lower bounds for the number of operators needed in fixed-point constant multiplication blocks are presented. The multipliers are constructed with the shift-and-add approach, where every arithmetic operation is pipelined, and with the generalization that n-input pipelined additions/subtractions are allowed, along with pure pipelining registers. These lower bounds, tighter than the state-of-the-art theoretical limits, are particularly useful in early design stages for a quick assessment in the hardware utilization of low-cost constant multiplication blocks implemented in the newest families of field programmable gate array (FPGA) integrated circuits.
Liu, Yan-Jun; Gao, Ying; Tong, Shaocheng; Chen, C L Philip
2016-01-01
In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, the dead zone, in this paper, is a kind of nonlinear dead zone. To overcome the noncausal problem, which leads to the control scheme infeasible, the systems can be transformed into a m -step-ahead predictor. Due to nonlinear dead-zone appearance, the transformed predictor still contains the nonaffine function. In addition, it is assumed that the gain function of dead-zone input and the control direction are unknown. These conditions bring about the difficulties and the complicacy in the controller design. Thus, the implicit function theorem is applied to deal with nonaffine dead-zone appearance, the problem caused by the unknown control direction can be resolved through applying the discrete Nussbaum gain, and the neural networks are used to approximate the unknown function. Based on the Lyapunov theory, all the signals of the resulting closed-loop system are proved to be semiglobal uniformly ultimately bounded. Moreover, the tracking error is proved to be regulated to a small neighborhood around zero. The feasibility of the proposed approach is demonstrated by a simulation example.
Partial and total actuator faults accommodation for input-affine nonlinear process plants.
Mihankhah, Amin; Salmasi, Farzad R; Salahshoor, Karim
2013-05-01
In this paper, a new fault-tolerant control system is proposed for input-affine nonlinear plants based on Model Reference Adaptive System (MRAS) structure. The proposed method has the capability to accommodate both partial and total actuator failures along with bounded external disturbances. In this methodology, the conventional MRAS control law is modified by augmenting two compensating terms. One of these terms is added to eliminate the nonlinear dynamic, while the other is reinforced to compensate the distractive effects of the total actuator faults and external disturbances. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed method. Moreover, the control structure has good robustness capability against the parameter variation. The performance of this scheme is evaluated using a CSTR system and the results were satisfactory. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Yang, Xiong; Liu, Derong; Wang, Ding
2014-03-01
In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.
On the Directional Dependence and Null Space Freedom in Uncertainty Bound Identification
NASA Technical Reports Server (NTRS)
Lim, K. B.; Giesy, D. P.
1997-01-01
In previous work, the determination of uncertainty models via minimum norm model validation is based on a single set of input and output measurement data. Since uncertainty bounds at each frequency is directionally dependent for multivariable systems, this will lead to optimistic uncertainty levels. In addition, the design freedom in the uncertainty model has not been utilized to further reduce uncertainty levels. The above issues are addressed by formulating a min- max problem. An analytical solution to the min-max problem is given to within a generalized eigenvalue problem, thus avoiding a direct numerical approach. This result will lead to less conservative and more realistic uncertainty models for use in robust control.
Non-predictor control of a class of feedforward nonlinear systems with unknown time-varying delays
NASA Astrophysics Data System (ADS)
Koo, Min-Sung; Choi, Ho-Lim
2016-08-01
This paper generalises the several recent results on the control of feedforward time-delay nonlinear systems. First, in view of system formulation, there are unknown time-varying delays in both states and main control input. Also, the considered nonlinear system has extended feedforward nonlinearities. Second, in view of control solution, our proposed controller is a non-predictor feedback controller whereas smith-predictor type controllers are used in the several existing results. Moreover, our controller does not need any information on the unknown delays except their upper bounds. Thus, our result has certain merits in both system formulation and control solution perspective. The analysis and example are given for clear illustration.
Probabilistic Parameter Uncertainty Analysis of Single Input Single Output Control Systems
NASA Technical Reports Server (NTRS)
Smith, Brett A.; Kenny, Sean P.; Crespo, Luis G.
2005-01-01
The current standards for handling uncertainty in control systems use interval bounds for definition of the uncertain parameters. This approach gives no information about the likelihood of system performance, but simply gives the response bounds. When used in design, current methods of m-analysis and can lead to overly conservative controller design. With these methods, worst case conditions are weighted equally with the most likely conditions. This research explores a unique approach for probabilistic analysis of control systems. Current reliability methods are examined showing the strong areas of each in handling probability. A hybrid method is developed using these reliability tools for efficiently propagating probabilistic uncertainty through classical control analysis problems. The method developed is applied to classical response analysis as well as analysis methods that explore the effects of the uncertain parameters on stability and performance metrics. The benefits of using this hybrid approach for calculating the mean and variance of responses cumulative distribution functions are shown. Results of the probabilistic analysis of a missile pitch control system, and a non-collocated mass spring system, show the added information provided by this hybrid analysis.
Aeroservoelastic Uncertainty Model Identification from Flight Data
NASA Technical Reports Server (NTRS)
Brenner, Martin J.
2001-01-01
Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.
Program Monitoring with LTL in EAGLE
NASA Technical Reports Server (NTRS)
Barringer, Howard; Goldberg, Allen; Havelund, Klaus; Sen, Koushik
2004-01-01
We briefly present a rule-based framework called EAGLE, shown to be capable of defining and implementing finite trace monitoring logics, including future and past time temporal logic, extended regular expressions, real-time and metric temporal logics (MTL), interval logics, forms of quantified temporal logics, and so on. In this paper we focus on a linear temporal logic (LTL) specialization of EAGLE. For an initial formula of size m, we establish upper bounds of O(m(sup 2)2(sup m)log m) and O(m(sup 4)2(sup 2m)log(sup 2) m) for the space and time complexity, respectively, of single step evaluation over an input trace. This bound is close to the lower bound O(2(sup square root m) for future-time LTL presented. EAGLE has been successfully used, in both LTL and metric LTL forms, to test a real-time controller of an experimental NASA planetary rover.
Achieving unequal error protection with convolutional codes
NASA Technical Reports Server (NTRS)
Mills, D. G.; Costello, D. J., Jr.; Palazzo, R., Jr.
1994-01-01
This paper examines the unequal error protection capabilities of convolutional codes. Both time-invariant and periodically time-varying convolutional encoders are examined. The effective free distance vector is defined and is shown to be useful in determining the unequal error protection (UEP) capabilities of convolutional codes. A modified transfer function is used to determine an upper bound on the bit error probabilities for individual input bit positions in a convolutional encoder. The bound is heavily dependent on the individual effective free distance of the input bit position. A bound relating two individual effective free distances is presented. The bound is a useful tool in determining the maximum possible disparity in individual effective free distances of encoders of specified rate and memory distribution. The unequal error protection capabilities of convolutional encoders of several rates and memory distributions are determined and discussed.
Formation Control for Water-Jet USV Based on Bio-Inspired Method
NASA Astrophysics Data System (ADS)
Fu, Ming-yu; Wang, Duan-song; Wang, Cheng-long
2018-03-01
The formation control problem for underactuated unmanned surface vehicles (USVs) is addressed by a distributed strategy based on virtual leader strategy. The control system takes account of disturbance induced by external environment. With the coordinate transformation, the advantage of the proposed scheme is that the control point can be any point of the ship instead of the center of gravity. By introducing bio-inspired model, the formation control problem is addressed with backstepping method. This avoids complicated computation, simplifies the control law, and smoothes the input signals. The system uniform ultimate boundness is proven by Lyapunov stability theory with Young inequality. Simulation results are presented to verify the effectiveness and robust of the proposed controller.
Adaptive State Predictor Based Human Operator Modeling on Longitudinal and Lateral Control
NASA Technical Reports Server (NTRS)
Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.
2015-01-01
Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to categorize these interactions of the pilot with an adaptive controller compensating during control surface failures. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored. A gradient descent estimator (GDE), a least squares estimator with exponential forgetting (LSEEF), and a least squares estimator with bounded gain forgetting (LSEBGF) used the experiment data to predict pilot stick input. Previous results have found that the GDE and LSEEF methods are fairly accurate in predicting longitudinal stick input from commanded pitch. This paper discusses the accuracy of each of the three methods - GDE, LSEEF, and LSEBGF - to predict both pilot longitudinal and lateral stick input from the flight director's commanded pitch and bank attitudes.
NASA Astrophysics Data System (ADS)
Kim, Jung Hoon; Hur, Sung-Moon; Oh, Yonghwan
2018-03-01
This paper is concerned with performance analysis of proportional-derivative/proportional-integral-derivative (PD/PID) controller for bounded persistent disturbances in a robotic manipulator. Even though the notion of input-to-state stability (ISS) has been widely used to deal with the effect of disturbances in control of a robotic manipulator, the corresponding studies cannot be directly applied to the treatment of persistent disturbances occurred in robotic manipulators. This is because the conventional studies relevant to ISS consider the H∞ performance for robotic systems, which is confined to the treatment of decaying disturbances, i.e. the disturbances those in the L2 space. To deal with the effect of persistent disturbances in robotic systems, we first provide a new treatment of ISS in the L∞ sense because bounded persistent disturbances should be intrinsically regarded as elements of the L∞ space. We next derive state-space representations of trajectory tracking control in the robotic systems which allow us to define the problem formulations more clearly. We then propose a novel control law that has a PD/PID control form, by which the trajectory tracking system satisfies the reformulated ISS. Furthermore, we can obtain a theoretical argument about the L∞ gain from the disturbance to the regulated output through the proposed control law. Finally, experimental studies for a typical 3-degrees of freedom robotic manipulator are given to demonstrate the effectiveness of the method introduced in this paper.
Voltage mode electronically tunable full-wave rectifier
NASA Astrophysics Data System (ADS)
Petrović, Predrag B.; Vesković, Milan; Đukić, Slobodan
2017-01-01
The paper presents a new realization of bipolar full-wave rectifier of input sinusoidal signals, employing one MO-CCCII (multiple output current controlled current conveyor), a zero-crossing detector (ZCD), and one resistor connected to fixed potential. The circuit provides the operating frequency up to 10 MHz with increased linearity and precision in processing of input voltage signal, with a very low harmonic distortion. The errors related to the signal processing and errors bound were investigated and provided in the paper. The PSpice simulations are depicted and agree well with the theoretical anticipation. The maximum power consumption of the converter is approximately 2.83 mW, at ±1.2 V supply voltages.
NASA Astrophysics Data System (ADS)
Li, Zhifu; Hu, Yueming; Li, Di
2016-08-01
For a class of linear discrete-time uncertain systems, a feedback feed-forward iterative learning control (ILC) scheme is proposed, which is comprised of an iterative learning controller and two current iteration feedback controllers. The iterative learning controller is used to improve the performance along the iteration direction and the feedback controllers are used to improve the performance along the time direction. First of all, the uncertain feedback feed-forward ILC system is presented by an uncertain two-dimensional Roesser model system. Then, two robust control schemes are proposed. One can ensure that the feedback feed-forward ILC system is bounded-input bounded-output stable along time direction, and the other can ensure that the feedback feed-forward ILC system is asymptotically stable along time direction. Both schemes can guarantee the system is robust monotonically convergent along the iteration direction. Third, the robust convergent sufficient conditions are given, which contains a linear matrix inequality (LMI). Moreover, the LMI can be used to determine the gain matrix of the feedback feed-forward iterative learning controller. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed schemes.
Marathon: An Open Source Software Library for the Analysis of Markov-Chain Monte Carlo Algorithms
Rechner, Steffen; Berger, Annabell
2016-01-01
We present the software library marathon, which is designed to support the analysis of sampling algorithms that are based on the Markov-Chain Monte Carlo principle. The main application of this library is the computation of properties of so-called state graphs, which represent the structure of Markov chains. We demonstrate applications and the usefulness of marathon by investigating the quality of several bounding methods on four well-known Markov chains for sampling perfect matchings and bipartite graphs. In a set of experiments, we compute the total mixing time and several of its bounds for a large number of input instances. We find that the upper bound gained by the famous canonical path method is often several magnitudes larger than the total mixing time and deteriorates with growing input size. In contrast, the spectral bound is found to be a precise approximation of the total mixing time. PMID:26824442
Sun, Liang; Huo, Wei; Jiao, Zongxia
2017-03-01
This paper studies relative pose control for a rigid spacecraft with parametric uncertainties approaching to an unknown tumbling target in disturbed space environment. State feedback controllers for relative translation and relative rotation are designed in an adaptive nonlinear robust control framework. The element-wise and norm-wise adaptive laws are utilized to compensate the parametric uncertainties of chaser and target spacecraft, respectively. External disturbances acting on two spacecraft are treated as a lumped and bounded perturbation input for system. To achieve the prescribed disturbance attenuation performance index, feedback gains of controllers are designed by solving linear matrix inequality problems so that lumped disturbance attenuation with respect to the controlled output is ensured in the L 2 -gain sense. Moreover, in the absence of lumped disturbance input, asymptotical convergence of relative pose are proved by using the Lyapunov method. Numerical simulations are performed to show that position tracking and attitude synchronization are accomplished in spite of the presence of couplings and uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Consideration of plant behaviour in optimal servo-compensator design
NASA Astrophysics Data System (ADS)
Moase, W. H.; Manzie, C.
2016-07-01
Where the most prevalent optimal servo-compensator formulations penalise the behaviour of an error system, this paper considers the problem of additionally penalising the actual states and inputs of the plant. Doing so has the advantage of enabling the penalty function to better resemble an economic cost. This is especially true of problems where control effort needs to be sensibly allocated across weakly redundant inputs or where one wishes to use penalties to soft-constrain certain states or inputs. It is shown that, although the resulting cost function grows unbounded as its horizon approaches infinity, it is possible to formulate an equivalent optimisation problem with a bounded cost. The resulting optimisation problem is similar to those in earlier studies but has an additional 'correction term' in the cost function, and a set of equality constraints that arise when there are redundant inputs. A numerical approach to solve the resulting optimisation problem is presented, followed by simulations on a micro-macro positioner that illustrate the benefits of the proposed servo-compensator design approach.
Jiang, Ye; Hu, Qinglei; Ma, Guangfu
2010-01-01
In this paper, a robust adaptive fault-tolerant control approach to attitude tracking of flexible spacecraft is proposed for use in situations when there are reaction wheel/actuator failures, persistent bounded disturbances and unknown inertia parameter uncertainties. The controller is designed based on an adaptive backstepping sliding mode control scheme, and a sufficient condition under which this control law can render the system semi-globally input-to-state stable is also provided such that the closed-loop system is robust with respect to any disturbance within a quantifiable restriction on the amplitude, as well as the set of initial conditions, if the control gains are designed appropriately. Moreover, in the design, the control law does not need a fault detection and isolation mechanism even if the failure time instants, patterns and values on actuator failures are also unknown for the designers, as motivated from a practical spacecraft control application. In addition to detailed derivations of the new controller design and a rigorous sketch of all the associated stability and attitude error convergence proofs, illustrative simulation results of an application to flexible spacecraft show that high precise attitude control and vibration suppression are successfully achieved using various scenarios of controlling effective failures. 2009. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Graham, Emily B.; Tfaily, Malak M.; Crump, Alex R.; Goldman, Amy E.; Bramer, Lisa M.; Arntzen, Evan; Romero, Elvira; Resch, C. Tom; Kennedy, David W.; Stegen, James C.
2017-12-01
In light of increasing terrestrial carbon (C) transport across aquatic boundaries, the mechanisms governing organic carbon (OC) oxidation along terrestrial-aquatic interfaces are crucial to future climate predictions. Here we investigate the biochemistry, metabolic pathways, and thermodynamics corresponding to OC oxidation in the Columbia River corridor using ultrahigh-resolution C characterization. We leverage natural vegetative differences to encompass variation in terrestrial C inputs. Our results suggest that decreases in terrestrial C deposition associated with diminished riparian vegetation induce oxidation of physically bound OC. We also find that contrasting metabolic pathways oxidize OC in the presence and absence of vegetation and—in direct conflict with the "priming" concept—that inputs of water-soluble and thermodynamically favorable terrestrial OC protect bound-OC from oxidation. In both environments, the most thermodynamically favorable compounds appear to be preferentially oxidized regardless of which OC pool microbiomes metabolize. In turn, we suggest that the extent of riparian vegetation causes sediment microbiomes to locally adapt to oxidize a particular pool of OC but that common thermodynamic principles govern the oxidation of each pool (i.e., water-soluble or physically bound). Finally, we propose a mechanistic conceptualization of OC oxidation along terrestrial-aquatic interfaces that can be used to model heterogeneous patterns of OC loss under changing land cover distributions.
Quadratic stabilisability of multi-agent systems under switching topologies
NASA Astrophysics Data System (ADS)
Guan, Yongqiang; Ji, Zhijian; Zhang, Lin; Wang, Long
2014-12-01
This paper addresses the stabilisability of multi-agent systems (MASs) under switching topologies. Necessary and/or sufficient conditions are presented in terms of graph topology. These conditions explicitly reveal how the intrinsic dynamics of the agents, the communication topology and the external control input affect stabilisability jointly. With the appropriate selection of some agents to which the external inputs are applied and the suitable design of neighbour-interaction rules via a switching topology, an MAS is proved to be stabilisable even if so is not for each of uncertain subsystem. In addition, a method is proposed to constructively design a switching rule for MASs with norm-bounded time-varying uncertainties. The switching rules designed via this method do not rely on uncertainties, and the switched MAS is quadratically stabilisable via decentralised external self-feedback for all uncertainties. With respect to applications of the stabilisability results, the formation control and the cooperative tracking control are addressed. Numerical simulations are presented to demonstrate the effectiveness of the proposed results.
Zavou, Christina; Kkoushi, Antria; Koutsou, Achilleas; Christodoulou, Chris
2017-11-01
The aim of the current work is twofold: firstly to adapt an existing method measuring the input synchrony of a neuron driven only by excitatory inputs in such a way so as to account for inhibitory inputs as well and secondly to further appropriately adapt this measure so as to be correctly utilised on experimentally-recorded data. The existing method uses the normalized pre-spike slope (NPSS) of the membrane potential, resulting from observing the slope of depolarization of the membrane potential of a neuron prior to the moment of crossing the threshold within a short period of time, to identify the response-relevant input synchrony and through it to infer the operational mode of a neuron. The first adaptation of NPSS is made such that its upper bound calculation accommodates for the higher possible slope values caused by the lower average and minimum membrane potential values due to inhibitory inputs. Results indicate that when the input spike trains arrive randomly, the modified NPSS works as expected inferring that the neuron is operating as a temporal integrator. When the input spike trains arrive in perfect synchrony though, the modified NPSS works as expected only when the level of inhibition is much higher than the level of excitation. This suggests that calculation of the upper bound of the NPSS should be a function of the ratio between excitatory and inhibitory inputs in order to be able to correctly capture perfect synchrony at a neuron's input. In addition, we effectively demonstrate a process which has to be followed when aiming to use the NPSS on real neuron recordings. This process, which relies on empirical observations of the slope of depolarisation for estimating the bounds for the range of observed interspike interval lengths, is successfully applied to experimentally-recorded data showing that through it both a real neuron's operational mode and the amount of input synchrony that caused its firing can be inferred. Copyright © 2017 Elsevier B.V. All rights reserved.
Reducing Conservatism of Analytic Transient Response Bounds via Shaping Filters
NASA Technical Reports Server (NTRS)
Kwan, Aiyueh; Bedrossian, Nazareth; Jan, Jiann-Woei; Grigoriadis, Karolos; Hua, Tuyen (Technical Monitor)
1999-01-01
Recent results show that the peak transient response of a linear system to bounded energy inputs can be computed using the energy-to-peak gain of the system. However, analytically computed peak response bound can be conservative for a class of class bounded energy signals, specifically pulse trains generated from jet firings encountered in space vehicles. In this paper, shaping filters are proposed as a Methodology to reduce the conservatism of peak response analytic bounds. This Methodology was applied to a realistic Space Station assembly operation subject to jet firings. The results indicate that shaping filters indeed reduce the predicted peak response bounds.
NASA Technical Reports Server (NTRS)
Warsi, Saif A.
1989-01-01
A detailed operating manual is presented for a grid generating program that produces 3-D meshes for advanced turboprops. The code uses both algebraic and elliptic partial differential equation methods to generate single rotation and counterrotation, H or C type meshes for the z - r planes and H type for the z - theta planes. The code allows easy specification of geometrical constraints (such as blade angle, location of bounding surfaces, etc.), mesh control parameters (point distribution near blades and nacelle, number of grid points desired, etc.), and it has good runtime diagnostics. An overview is provided of the mesh generation procedure, sample input dataset with detailed explanation of all input, and example meshes.
Robust adaptive sliding mode control for uncertain systems with unknown time-varying delay input.
Benamor, Anouar; Messaoud, Hassani
2018-05-02
This article focuses on robust adaptive sliding mode control law for uncertain discrete systems with unknown time-varying delay input, where the uncertainty is assumed unknown. The main results of this paper are divided into three phases. In the first phase, we propose a new sliding surface is derived within the Linear Matrix Inequalities (LMIs). In the second phase, using the new sliding surface, the novel Robust Sliding Mode Control (RSMC) is proposed where the upper bound of uncertainty is supposed known. Finally, the novel approach of Robust Adaptive Sliding ModeControl (RASMC) has been defined for this type of systems, where the upper limit of uncertainty which is assumed unknown. In this new approach, we have estimate the upper limit of uncertainties and we have determined the control law based on a sliding surface that will converge to zero. This novel control laws are been validated in simulation on an uncertain numerical system with good results and comparative study. This efficiency is emphasized through the application of the new controls on the two physical systems which are the process trainer PT326 and hydraulic system two tanks. Published by Elsevier Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Graham, Emily B.; Tfaily, Malak M.; Crump, Alex R.
In light of increasing terrestrial carbon (C) transport across aquatic boundaries, the mechanisms governing organic carbon (OC) oxidation along terrestrial-aquatic interfaces are crucial to future climate predictions. Here, we investigate biochemistry, metabolic pathways, and thermodynamics corresponding to OC oxidation in the Columbia River corridor. We leverage natural vegetative differences to encompass variation in terrestrial C inputs. Our results suggest that decreases in terrestrial C deposition associated with diminished riparian vegetation induce oxidation of physically-bound (i.e., mineral and microbial) OC at terrestrial-aquatic interfaces. We also find that contrasting metabolic pathways oxidize OC in the presence and absence of vegetation and—in directmore » conflict with the concept of ‘priming’—that inputs of water-soluble and thermodynamically-favorable terrestrial OC protects bound-OC from oxidation. Based on our results, we propose a mechanistic conceptualization of OC oxidation along terrestrial-aquatic interfaces that can be used to model heterogeneous patterns of OC loss under changing land cover distributions.« less
Optimality of semiquantum nonlocality in the presence of high inconclusive rates
Lim, Charles Ci Wen
2016-02-01
Quantum nonlocality is a counterintuitive phenomenon that lies beyond the purview of causal influences. Recently, Bell inequalities have been generalized to the case of quantum inputs, leading to a powerful family of semiquantum Bell inequalities that are capable of detecting any entangled state. We focus on a different problem and investigate how the local indistinguishability of quantum inputs and postselection may affect the requirements to detect semiquantum nonlocality. Moreover, we consider a semiquantum nonlocal game based on locally indistinguishable qubit inputs, and derive its postselected local and quantum bounds by using a connection to the local distinguishability of quantum states.more » Interestingly, we find that the postselected local bound is independent of the measurement efficiency, and the achievable postselected Bell violation increases with decreasing measurement efficiency.« less
Offsite Radiological Consequence Analysis for the Bounding Flammable Gas Accident
DOE Office of Scientific and Technical Information (OSTI.GOV)
CARRO, C.A.
2003-07-30
This document quantifies the offsite radiological consequences of the bounding flammable gas accident for comparison with the 25 rem Evaluation Guideline established in DOE-STD-3009, Appendix A. The bounding flammable gas accident is a detonation in a single-shell tank The calculation applies reasonably conservation input parameters in accordance with DOE-STD-3009, Appendix A, guidance. Revision 1 incorporates comments received from Office of River Protection.
1989-07-01
the Government may have formulated or in any way supplied the said drawings, specifications, or other data, is not to be regarded by implication, or...of these gains gives a measure of the total amount of damping supplied by the actuators and colocated velocity sensors. In this sense, the sum of the...disturbances are assumed to be unknown but bounded time-varying pro - cesses. Second, inequality constraints on outputs (measurements) and inputs (con
Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai
2014-07-01
In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.
Synthesis of feedback systems with large plant ignorance for prescribed time domain tolerances
NASA Technical Reports Server (NTRS)
Horowitz, I. M.; Sidi, M.
1971-01-01
There is given a minimum-phase plant transfer function, with prescribed bounds on its parameter values. The plant is imbedded in a two-degree-of freedom feedback system, which is to be designed such that the system time response to a deterministic input lies within specified boundaries. Subject to the above, the design should be such as to minimize the effect of sensor noise at the input to the plant. This report presents a design procedure for this purpose, based on frequency response concepts. The time-domain tolerances are translated into equivalent frequency response tolerances. The latter lead to bounds on the loop transmission function in the form of continuous curves on the Nichols chart. The properties of the loop transmission function which satisfy these bounds with minimum effect of sensor noise, are derived.
Transfer Function Bounds for Partial-unit-memory Convolutional Codes Based on Reduced State Diagram
NASA Technical Reports Server (NTRS)
Lee, P. J.
1984-01-01
The performance of a coding system consisting of a convolutional encoder and a Viterbi decoder is analytically found by the well-known transfer function bounding technique. For the partial-unit-memory byte-oriented convolutional encoder with m sub 0 binary memory cells and (k sub 0 m sub 0) inputs, a state diagram of 2(K) (sub 0) was for the transfer function bound. A reduced state diagram of (2 (m sub 0) +1) is used for easy evaluation of transfer function bounds for partial-unit-memory codes.
Shih, Peter; Kaul, Brian C; Jagannathan, Sarangapani; Drallmeier, James A
2009-10-01
A novel reinforcement-learning-based output adaptive neural network (NN) controller, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility function and control inputs. All NN weights adapt online toward minimization of a performance index, utilizing the gradient-descent-based rule, in contrast with iteration-based adaptive-critic schemes. Lyapunov functions are used to show the stability of the closed-loop tracking error, weights, and observer estimates. Separation and certainty equivalence principles, persistency of excitation condition, and linearity in the unknown parameter assumption are not needed. Experimental results on a spark ignition (SI) engine operating lean at an equivalence ratio of 0.75 show a significant (25%) reduction in cyclic dispersion in heat release with control, while the average fuel input changes by less than 1% compared with the uncontrolled case. Consequently, oxides of nitrogen (NO(x)) drop by 30%, and unburned hydrocarbons drop by 16% with control. Overall, NO(x)'s are reduced by over 80% compared with stoichiometric levels.
NASA Astrophysics Data System (ADS)
Yu, Jiang-Bo; Zhao, Yan; Wu, Yu-Qiang
2014-04-01
This article considers the global robust output regulation problem via output feedback for a class of cascaded nonlinear systems with input-to-state stable inverse dynamics. The system uncertainties depend not only on the measured output but also all the unmeasurable states. By introducing an internal model, the output regulation problem is converted into a stabilisation problem for an appropriately augmented system. The designed dynamic controller could achieve the global asymptotic tracking control for a class of time-varying reference signals for the system output while keeping all other closed-loop signals bounded. It is of interest to note that the developed control approach can be applied to the speed tracking control of the fan speed control system. The simulation results demonstrate its effectiveness.
An efficient approach to ARMA modeling of biological systems with multiple inputs and delays
NASA Technical Reports Server (NTRS)
Perrott, M. H.; Cohen, R. J.
1996-01-01
This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.
Dual-user nonlinear teleoperation subjected to varying time delay and bounded inputs.
Zakerimanesh, Amir; Hashemzadeh, Farzad; Ghiasi, Amir Rikhtehgar
2017-05-01
A novel trilateral control architecture for Dual-master/Single-slave teleoperation system with taking account of saturation in actuators, nonlinear dynamics for telemanipulators and bounded varying time delay which affects the transmitted signals in the communication channels, is proposed in this paper. In this research, we will address the stability and desired position coordination problem of trilateral teleoperation system by extension of (nP+D) controller that is used for Single-master/Single-slave teleoperation system. Our proposed controller is weighted summation of nonlinear Proportional plus Damping (nP+D) controller that incorporate gravity compensation and the weights are specified by the dominance factor, which determines the supremacy of each user over the slave robot and over the other user. The asymptotic stability of closed loop dynamics is studied using Lyapunov-Krasovskii functional under conditions on the controller parameters, the actuator saturation characteristics and the maximum values of varying time delays. It is shown that these controllers satisfy the desired position coordination problem in free motion condition. To show the effectiveness of the proposed method, a number of simulations have been conducted on a varying time delay Dual-master/Single-slave teleoperation system using 3-DOF planar robots for each telemanipulator subjected to actuator saturation. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Davoodi, M.; Meskin, N.; Khorasani, K.
2018-03-01
The problem of simultaneous fault detection, isolation and tracking (SFDIT) control design for linear systems subject to both bounded energy and bounded peak disturbances is considered in this work. A dynamic observer is proposed and implemented by using the H∞/H-/L1 formulation of the SFDIT problem. A single dynamic observer module is designed that generates the residuals as well as the control signals. The objective of the SFDIT module is to ensure that simultaneously the effects of disturbances and control signals on the residual signals are minimised (in order to accomplish the fault detection goal) subject to the constraint that the transfer matrix from the faults to the residuals is equal to a pre-assigned diagonal transfer matrix (in order to accomplish the fault isolation goal), while the effects of disturbances, reference inputs and faults on the specified control outputs are minimised (in order to accomplish the fault-tolerant and tracking control goals). A set of linear matrix inequality (LMI) feasibility conditions are derived to ensure solvability of the problem. In order to illustrate and demonstrate the effectiveness of our proposed design methodology, the developed and proposed schemes are applied to an autonomous unmanned underwater vehicle (AUV).
Esfandiari, Kasra; Abdollahi, Farzaneh; Talebi, Heidar Ali
2017-09-01
In this paper, an identifier-critic structure is introduced to find an online near-optimal controller for continuous-time nonaffine nonlinear systems having saturated control signal. By employing two Neural Networks (NNs), the solution of Hamilton-Jacobi-Bellman (HJB) equation associated with the cost function is derived without requiring a priori knowledge about system dynamics. Weights of the identifier and critic NNs are tuned online and simultaneously such that unknown terms are approximated accurately and the control signal is kept between the saturation bounds. The convergence of NNs' weights, identification error, and system states is guaranteed using Lyapunov's direct method. Finally, simulation results are performed on two nonlinear systems to confirm the effectiveness of the proposed control strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.
Steering redundancy for self-driving vehicles using differential braking
NASA Astrophysics Data System (ADS)
Jonasson, M.; Thor, M.
2018-05-01
This paper describes how differential braking can be used to turn a vehicle in the context of providing fail-operational control for self-driving vehicles. Two vehicle models are developed with differential input. The models are used to explain the bounds of curvature that differential braking provides and they are then validated with measurements in a test vehicle. Particular focus is paid on wheel suspension effects that significantly influence the obtained curvature. The vehicle behaviour and its limitations due to wheel suspension effects are, owing to the vehicle models, defined and explained. Finally, a model-based controller is developed to control the vehicle curvature during a fault by differential braking. The controller is designed to compensate for wheel angle disturbance that is likely to occur during the control event.
New Algorithms and Lower Bounds for Sequential-Access Data Compression
NASA Astrophysics Data System (ADS)
Gagie, Travis
2009-02-01
This thesis concerns sequential-access data compression, i.e., by algorithms that read the input one or more times from beginning to end. In one chapter we consider adaptive prefix coding, for which we must read the input character by character, outputting each character's self-delimiting codeword before reading the next one. We show how to encode and decode each character in constant worst-case time while producing an encoding whose length is worst-case optimal. In another chapter we consider one-pass compression with memory bounded in terms of the alphabet size and context length, and prove a nearly tight tradeoff between the amount of memory we can use and the quality of the compression we can achieve. In a third chapter we consider compression in the read/write streams model, which allows us passes and memory both polylogarithmic in the size of the input. We first show how to achieve universal compression using only one pass over one stream. We then show that one stream is not sufficient for achieving good grammar-based compression. Finally, we show that two streams are necessary and sufficient for achieving entropy-only bounds.
Training feed-forward neural networks with gain constraints
Hartman
2000-04-01
Inaccurate input-output gains (partial derivatives of outputs with respect to inputs) are common in neural network models when input variables are correlated or when data are incomplete or inaccurate. Accurate gains are essential for optimization, control, and other purposes. We develop and explore a method for training feedforward neural networks subject to inequality or equality-bound constraints on the gains of the learned mapping. Gain constraints are implemented as penalty terms added to the objective function, and training is done using gradient descent. Adaptive and robust procedures are devised for balancing the relative strengths of the various terms in the objective function, which is essential when the constraints are inconsistent with the data. The approach has the virtue that the model domain of validity can be extended via extrapolation training, which can dramatically improve generalization. The algorithm is demonstrated here on artificial and real-world problems with very good results and has been advantageously applied to dozens of models currently in commercial use.
Input-output budgets for dissolved inorganic nitrogen (DIN) are summarized for 24 small watersheds at 15 locations in the northeasternUnited States. The study watersheds are completely forested, free of recent physical disturbances, and span a geographical region bounded by West ...
Global RNA association with the transcriptionally active chromosome of chloroplasts.
Lehniger, Marie-Kristin; Finster, Sabrina; Melonek, Joanna; Oetke, Svenja; Krupinska, Karin; Schmitz-Linneweber, Christian
2017-10-01
Processed chloroplast RNAs are co-enriched with preparations of the chloroplast transcriptionally active chromosome. Chloroplast genomes are organized as a polyploid DNA-protein structure called the nucleoid. Transcriptionally active chloroplast DNA together with tightly bound protein factors can be purified by gel filtration as a functional entity called the transcriptionally active chromosome (TAC). Previous proteomics analyses of nucleoids and of TACs demonstrated a considerable overlap in protein composition including RNA binding proteins. Therefore the RNA content of TAC preparations from Nicotiana tabacum was determined using whole genome tiling arrays. A large number of chloroplast RNAs was found to be associated with the TAC. The pattern of RNAs attached to the TAC consists of RNAs produced by different chloroplast RNA polymerases and differs from the pattern of RNA found in input controls. An analysis of RNA splicing and RNA editing of selected RNA species demonstrated that TAC-associated RNAs are processed to a similar extent as the RNA in input controls. Thus, TAC fractions contain a specific subset of the processed chloroplast transcriptome.
Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang
2010-09-01
This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.
Relative position coordinated control for spacecraft formation flying with communication delays
NASA Astrophysics Data System (ADS)
Ran, Dechao; Chen, Xiaoqian; Misra, Arun K.; Xiao, Bing
2017-08-01
This study addresses a relative position coordinated control problem for spacecraft formation flying subject to directed communication topology. Two different kinds of communication delay cases, including time-varying delays and arbitrarily bounded delays are investigated. Using the backstepping control technique, two virtual velocity control inputs are firstly designed to achieve coordinated position tracking for the kinematic subsystem. Furthermore, a hyperbolic tangent function is introduced to guarantee the boundedness of the virtual controller. Then, a finite-time control algorithm is designed for the dynamic subsystem. It can guarantee that the virtual velocity can be followed by the real velocity after finite time. It is theoretically proved that the proposed control scheme can asymptotically stabilize the closed-loop system. Numerical simulations are further presented that not only highlight closed-loop performance benefiting from the proposed control scheme, but also illustrate its superiority in comparison with conventional formation control schemes.
Alternatives for jet engine control
NASA Technical Reports Server (NTRS)
Sain, M. K.
1979-01-01
The research is classified in two categories: (1) the use of modern multivariable frequency domain methods for control of engine models in the neighborhood of a set-point, and (2) the use of nonlinear modelling and optimization techniques for control of engine models over a more extensive part of the flight envelope. Progress in the first category included the extension of CARDIAD (Complex Acceptability Region for Diagonal Dominance) methods developed with the help of the grant to the case of engine models with four inputs and four outputs. A suitable bounding procedure for the dominance function was determined. Progress in the second category had its principal focus on automatic nonlinear model generation. Simulations of models produced satisfactory results where compared with the NASA DYNGEN digital engine deck.
NASA Astrophysics Data System (ADS)
Horn, Joachim
Für die Stabilität eines linearen, zeitinvarianten Übertragungsgliedes existieren verschiedene Definitionen. Bei der asymptotischen Stabilität wird gefordert, dass der Systemausgang nach einer kurzzeitigen Systemanregung mit wachsender Zeit wieder gegen Null geht. Bei der BIBO-Stabilität (Bounded Input-Bounded Output) wird gefordert, dass bei einem beschränkten Systemeingang der Systemausgang ebenfalls beschränkt ist.
Modares, Hamidreza; Lewis, Frank L; Naghibi-Sistani, Mohammad-Bagher
2013-10-01
This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example.
An Inverse Neural Controller Based on the Applicability Domain of RBF Network Models
Alexandridis, Alex; Stogiannos, Marios; Papaioannou, Nikolaos; Zois, Elias; Sarimveis, Haralambos
2018-01-01
This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM) algorithm so that an approximation of the inverse system dynamics is obtained. PSO-NSFM offers models of high accuracy combined with small network structures. Next, the applicability domain concept is suitably tailored and embedded into the proposed control structure in order to ensure that extrapolation is avoided in the controller predictions. Finally, an error correction term, estimating the error produced by the unmodeled dynamics and/or unmeasured external disturbances, is included to the control scheme to increase robustness. The resulting controller guarantees bounded input-bounded state (BIBS) stability for the closed loop system when the open loop system is BIBS stable. The proposed methodology is evaluated on two different control problems, namely, the control of an experimental armature-controlled direct current (DC) motor and the stabilization of a highly nonlinear simulated inverted pendulum. For each one of these problems, appropriate case studies are tested, in which a conventional neural controller employing inverse models and a PID controller are also applied. The results reveal the ability of the proposed control scheme to handle and manipulate diverse data through a data fusion approach and illustrate the superiority of the method in terms of faster and less oscillatory responses. PMID:29361781
Robust on-off pulse control of flexible space vehicles
NASA Technical Reports Server (NTRS)
Wie, Bong; Sinha, Ravi
1993-01-01
The on-off reaction jet control system is often used for attitude and orbital maneuvering of various spacecraft. Future space vehicles such as the orbital transfer vehicles, orbital maneuvering vehicles, and space station will extensively use reaction jets for orbital maneuvering and attitude stabilization. The proposed robust fuel- and time-optimal control algorithm is used for a three-mass spacing model of flexible spacecraft. A fuel-efficient on-off control logic is developed for robust rest-to-rest maneuver of a flexible vehicle with minimum excitation of structural modes. The first part of this report is concerned with the problem of selecting a proper pair of jets for practical trade-offs among the maneuvering time, fuel consumption, structural mode excitation, and performance robustness. A time-optimal control problem subject to parameter robustness constraints is formulated and solved. The second part of this report deals with obtaining parameter insensitive fuel- and time- optimal control inputs by solving a constrained optimization problem subject to robustness constraints. It is shown that sensitivity to modeling errors can be significantly reduced by the proposed, robustified open-loop control approach. The final part of this report deals with sliding mode control design for uncertain flexible structures. The benchmark problem of a flexible structure is used as an example for the feedback sliding mode controller design with bounded control inputs and robustness to parameter variations is investigated.
Tang, Xiaoming; Qu, Hongchun; Wang, Ping; Zhao, Meng
2015-03-01
This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S-A) and controller to actuator (C-A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Neural network L1 adaptive control of MIMO systems with nonlinear uncertainty.
Zhen, Hong-tao; Qi, Xiao-hui; Li, Jie; Tian, Qing-min
2014-01-01
An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of an L 1 adaptive controller and an auxiliary neural network (NN) compensation controller. The L 1 adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.
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.
Quantized Synchronization of Chaotic Neural Networks With Scheduled Output Feedback Control.
Wan, Ying; Cao, Jinde; Wen, Guanghui
In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.In this paper, the synchronization problem of master-slave chaotic neural networks with remote sensors, quantization process, and communication time delays is investigated. The information communication channel between the master chaotic neural network and slave chaotic neural network consists of several remote sensors, with each sensor able to access only partial knowledge of output information of the master neural network. At each sampling instants, each sensor updates its own measurement and only one sensor is scheduled to transmit its latest information to the controller's side in order to update the control inputs for the slave neural network. Thus, such communication process and control strategy are much more energy-saving comparing with the traditional point-to-point scheme. Sufficient conditions for output feedback control gain matrix, allowable length of sampling intervals, and upper bound of network-induced delays are derived to ensure the quantized synchronization of master-slave chaotic neural networks. Lastly, Chua's circuit system and 4-D Hopfield neural network are simulated to validate the effectiveness of the main results.
Tabuchi, Masashi; Sakurai, Takeshi; Mitsuno, Hidefumi; Namiki, Shigehiro; Minegishi, Ryo; Shiotsuki, Takahiro; Uchino, Keiro; Sezutsu, Hideki; Tamura, Toshiki; Haupt, Stephan Shuichi; Nakatani, Kei; Kanzaki, Ryohei
2013-01-01
The olfactory system of male moths has an extreme sensitivity with the capability to detect and recognize conspecific pheromones dispersed and greatly diluted in the air. Just 170 molecules of the silkmoth (Bombyx mori) sex pheromone bombykol are sufficient to induce sexual behavior in the male. However, it is still unclear how the sensitivity of olfactory receptor neurons (ORNs) is relayed through the brain to generate high behavioral responsiveness. Here, we show that ORN activity that is subthreshold in terms of behavior can be amplified to suprathreshold levels by temporal integration in antennal lobe projection neurons (PNs) if occurring within a specific time window. To control ORN inputs with high temporal resolution, channelrhodopsin-2 was genetically introduced into bombykol-responsive ORNs. Temporal integration in PNs was only observed for weak inputs, but not for strong inputs. Pharmacological dissection revealed that GABAergic mechanisms inhibit temporal integration of strong inputs, showing that GABA signaling regulates PN responses in a stimulus-dependent fashion. Our results show that boosting of the PNs’ responses by temporal integration of olfactory information occurs specifically near the behavioral threshold, effectively defining the lower bound for behavioral responsiveness. PMID:24006366
Development of An Intelligent Flight Propulsion Control System
NASA Technical Reports Server (NTRS)
Calise, A. J.; Rysdyk, R. T.; Leonhardt, B. K.
1999-01-01
The initial design and demonstration of an Intelligent Flight Propulsion and Control System (IFPCS) is documented. The design is based on the implementation of a nonlinear adaptive flight control architecture. This initial design of the IFPCS enhances flight safety by using propulsion sources to provide redundancy in flight control. The IFPCS enhances the conventional gain scheduled approach in significant ways: (1) The IFPCS provides a back up flight control system that results in consistent responses over a wide range of unanticipated failures. (2) The IFPCS is applicable to a variety of aircraft models without redesign and,(3) significantly reduces the laborious research and design necessary in a gain scheduled approach. The control augmentation is detailed within an approximate Input-Output Linearization setting. The availability of propulsion only provides two control inputs, symmetric and differential thrust. Earlier Propulsion Control Augmentation (PCA) work performed by NASA provided for a trajectory controller with pilot command input of glidepath and heading. This work is aimed at demonstrating the flexibility of the IFPCS in providing consistency in flying qualities under a variety of failure scenarios. This report documents the initial design phase where propulsion only is used. Results confirm that the engine dynamics and associated hard nonlineaaities result in poor handling qualities at best. However, as demonstrated in simulation, the IFPCS is capable of results similar to the gain scheduled designs of the NASA PCA work. The IFPCS design uses crude estimates of aircraft behaviour. The adaptive control architecture demonstrates robust stability and provides robust performance. In this work, robust stability means that all states, errors, and adaptive parameters remain bounded under a wide class of uncertainties and input and output disturbances. Robust performance is measured in the quality of the tracking. The results demonstrate the flexibility of the IFPCS architecture and the ability to provide robust performance under a broad range of uncertainty. Robust stability is proved using Lyapunov like analysis. Future development of the IFPCS will include integration of conventional control surfaces with the use of propulsion augmentation, and utilization of available lift and drag devices, to demonstrate adaptive control capability under a greater variety of failure scenarios. Further work will specifically address the effects of actuator saturation.
Differential-damper topologies for actuators in rehabilitation robotics.
Tucker, Michael R; Gassert, Roger
2012-01-01
Differential-damper (DD) elements can provide a high bandwidth means for decoupling a high inertia, high friction, non-backdrivable actuator from its output and can enable high fidelity force control. In this paper, a port-based decomposition is used to analyze the energetic behavior of such actuators in various physical domains. The general concepts are then applied to a prototype DD actuator for illustration and discussion. It is shown that, within physical bounds, the output torque from a DD actuator can be controlled independently from the input speed. This concept holds the potential to be scaled up and integrated in a compact and lightweight package powerful enough for incorporation with a portable lower limb orthotic or prosthetic device.
Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.
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.
Upper bounds on sequential decoding performance parameters
NASA Technical Reports Server (NTRS)
Jelinek, F.
1974-01-01
This paper presents the best obtainable random coding and expurgated upper bounds on the probabilities of undetectable error, of t-order failure (advance to depth t into an incorrect subset), and of likelihood rise in the incorrect subset, applicable to sequential decoding when the metric bias G is arbitrary. Upper bounds on the Pareto exponent are also presented. The G-values optimizing each of the parameters of interest are determined, and are shown to lie in intervals that in general have nonzero widths. The G-optimal expurgated bound on undetectable error is shown to agree with that for maximum likelihood decoding of convolutional codes, and that on failure agrees with the block code expurgated bound. Included are curves evaluating the bounds for interesting choices of G and SNR for a binary-input quantized-output Gaussian additive noise channel.
Wang, Yujuan; Song, Yongduan; Ren, Wei
2017-07-06
This paper presents a distributed adaptive finite-time control solution to the formation-containment problem for multiple networked systems with uncertain nonlinear dynamics and directed communication constraints. By integrating the special topology feature of the new constructed symmetrical matrix, the technical difficulty in finite-time formation-containment control arising from the asymmetrical Laplacian matrix under single-way directed communication is circumvented. Based upon fractional power feedback of the local error, an adaptive distributed control scheme is established to drive the leaders into the prespecified formation configuration in finite time. Meanwhile, a distributed adaptive control scheme, independent of the unavailable inputs of the leaders, is designed to keep the followers within a bounded distance from the moving leaders and then to make the followers enter the convex hull shaped by the formation of the leaders in finite time. The effectiveness of the proposed control scheme is confirmed by the simulation.
Directionality compensation for linear multivariable anti-windup synthesis
NASA Astrophysics Data System (ADS)
Adegbege, Ambrose A.; Heath, William P.
2015-11-01
We develop new synthesis procedures for optimising anti-windup control applicable to open-loop exponentially stable multivariable plants subject to hard bounds on the inputs. The optimising anti-windup control falls into a class of compensator commonly termed directionality compensation. The computation of the control involves the online solution of a low-order quadratic programme in place of simple saturation. We exploit the structure of the quadratic programme to incorporate directionality information into the offline anti-windup synthesis using a decoupled architecture similar to that proposed in the literature for anti-windup schemes with simple saturation. We demonstrate the effectiveness of the design compared to several schemes using a simulated example. Preliminary results of this work have been published in the proceedings of the IEEE Conference on Decision and Control, Orlando, 2011 (Adegbege & Heath, 2011a).
NASA Astrophysics Data System (ADS)
Shanahan, P. E.; Thomas, A. W.; Young, R. D.
2011-08-01
Recent lattice QCD calculations have reported evidence for the existence of a bound state with strangeness -2 and baryon number 2 at quark masses somewhat higher than the physical values. By developing a description of the dependence of this binding energy on the up, down and strange quark masses that allows a controlled chiral extrapolation, we explore the hypothesis that this state is to be identified with the H dibaryon. Taking as input the recent results of the HAL and NPLQCD Collaborations, we show that the H dibaryon is likely to be unbound by 13±14MeV at the physical point.
A new variant of Petri net controlled grammars
NASA Astrophysics Data System (ADS)
Jan, Nurhidaya Mohamad; Turaev, Sherzod; Fong, Wan Heng; Sarmin, Nor Haniza
2015-10-01
A Petri net controlled grammar is a Petri net with respect to a context-free grammar where the successful derivations of the grammar can be simulated using the occurrence sequences of the net. In this paper, we introduce a new variant of Petri net controlled grammars, called a place-labeled Petri net controlled grammar, which is a context-free grammar equipped with a Petri net and a function which maps places of the net to productions of the grammar. The language consists of all terminal strings that can be obtained by parallelly applying multisets of the rules which are the images of the sets of the input places of transitions in a successful occurrence sequence of the Petri net. We study the effect of the different labeling strategies to the computational power and establish lower and upper bounds for the generative capacity of place-labeled Petri net controlled grammars.
Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang
2017-05-18
This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.
Bounding the errors for convex dynamics on one or more polytopes.
Tresser, Charles
2007-09-01
We discuss the greedy algorithm for approximating a sequence of inputs in a family of polytopes lying in affine spaces by an output sequence made of vertices of the respective polytopes. More precisely, we consider here the case when the greed of the algorithm is dictated by the Euclidean norms of the successive cumulative errors. This algorithm can be interpreted as a time-dependent dynamical system in the vector space, where the errors live, or as a time-dependent dynamical system in an affine space containing copies of all the original polytopes. This affine space contains the inputs, as well as the inputs modified by adding the respective former errors; it is the evolution of these modified inputs that the dynamical system in affine space describes. Scheduling problems with many polytopes arise naturally, for instance, when the inputs are from a single polytope P, but one imposes the constraint that whenever the input belongs to a codimension n face, the output has to be in the same codimension n face (as when scheduling drivers among participants of a carpool). It has been previously shown that the error is bounded in the case of a single polytope by proving the existence of an arbitrary large convex invariant region for the dynamics in affine space: A region that is simultaneously invariant for several polytopes, each considered separately, was also constructed. It was then shown that there cannot be an invariant region in affine space in the general case of a family of polytopes. Here we prove the existence of an arbitrary large convex invariant set for the dynamics in the vector space in the case when the sizes of the polytopes in the family are bounded and the set of all the outgoing normals to all the faces of all the polytopes is finite. It was also previously known that starting from zero as the initial error set, the error set could not be saturated in finitely many steps in some cases with several polytopes: Contradicting a former conjecture, we show that the same happens for some single quadrilaterals and for a single pentagon with an axial symmetry. The disproof of that conjecture is the new piece of information that leads us to expect, and then to verify, as we recount here, that the proof that the errors are bounded in the general case could be a small step beyond the proof of the same statement for the single polytope case.
Bounding the errors for convex dynamics on one or more polytopes
NASA Astrophysics Data System (ADS)
Tresser, Charles
2007-09-01
We discuss the greedy algorithm for approximating a sequence of inputs in a family of polytopes lying in affine spaces by an output sequence made of vertices of the respective polytopes. More precisely, we consider here the case when the greed of the algorithm is dictated by the Euclidean norms of the successive cumulative errors. This algorithm can be interpreted as a time-dependent dynamical system in the vector space, where the errors live, or as a time-dependent dynamical system in an affine space containing copies of all the original polytopes. This affine space contains the inputs, as well as the inputs modified by adding the respective former errors; it is the evolution of these modified inputs that the dynamical system in affine space describes. Scheduling problems with many polytopes arise naturally, for instance, when the inputs are from a single polytope P, but one imposes the constraint that whenever the input belongs to a codimension n face, the output has to be in the same codimension n face (as when scheduling drivers among participants of a carpool). It has been previously shown that the error is bounded in the case of a single polytope by proving the existence of an arbitrary large convex invariant region for the dynamics in affine space: A region that is simultaneously invariant for several polytopes, each considered separately, was also constructed. It was then shown that there cannot be an invariant region in affine space in the general case of a family of polytopes. Here we prove the existence of an arbitrary large convex invariant set for the dynamics in the vector space in the case when the sizes of the polytopes in the family are bounded and the set of all the outgoing normals to all the faces of all the polytopes is finite. It was also previously known that starting from zero as the initial error set, the error set could not be saturated in finitely many steps in some cases with several polytopes: Contradicting a former conjecture, we show that the same happens for some single quadrilaterals and for a single pentagon with an axial symmetry. The disproof of that conjecture is the new piece of information that leads us to expect, and then to verify, as we recount here, that the proof that the errors are bounded in the general case could be a small step beyond the proof of the same statement for the single polytope case.
Farinella, Matteo; Ruedt, Daniel T.; Gleeson, Padraig; Lanore, Frederic; Silver, R. Angus
2014-01-01
In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such ‘background’ synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a ‘balanced’ background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales. PMID:24763087
Flight-determined stability analysis of multiple-input-multiple-output control systems
NASA Technical Reports Server (NTRS)
Burken, John J.
1992-01-01
Singular value analysis can give conservative stability margin results. Applying structure to the uncertainty can reduce this conservatism. This paper presents flight-determined stability margins for the X-29A lateral-directional, multiloop control system. These margins are compared with the predicted unscaled singular values and scaled structured singular values. The algorithm was further evaluated with flight data by changing the roll-rate-to-aileron command-feedback gain by +/- 20 percent. Minimum eigenvalues of the return difference matrix which bound the singular values are also presented. Extracting multiloop singular values from flight data and analyzing the feedback gain variations validates this technique as a measure of robustness. This analysis can be used for near-real-time flight monitoring and safety testing.
Flight-determined stability analysis of multiple-input-multiple-output control systems
NASA Technical Reports Server (NTRS)
Burken, John J.
1992-01-01
Singular value analysis can give conservative stability margin results. Applying structure to the uncertainty can reduce this conservatism. This paper presents flight-determined stability margins for the X-29A lateral-directional, multiloop control system. These margins are compared with the predicted unscaled singular values and scaled structured singular values. The algorithm was further evaluated with flight data by changing the roll-rate-to-aileron-command-feedback gain by +/- 20 percent. Also presented are the minimum eigenvalues of the return difference matrix which bound the singular values. Extracting multiloop singular values from flight data and analyzing the feedback gain variations validates this technique as a measure of robustness. This analysis can be used for near-real-time flight monitoring and safety testing.
Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hampton, Jerrad; Doostan, Alireza, E-mail: alireza.doostan@colorado.edu
2015-01-01
Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ{sub 1}-minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence onmore » the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy.« less
Application of neural models as controllers in mobile robot velocity control loop
NASA Astrophysics Data System (ADS)
Cerkala, Jakub; Jadlovska, Anna
2017-01-01
This paper presents the application of an inverse neural models used as controllers in comparison to classical PI controllers for velocity tracking control task used in two-wheel, differentially driven mobile robot. The PI controller synthesis is based on linear approximation of actuators with equivalent load. In order to obtain relevant datasets for training of feed-forward multi-layer perceptron based neural network used as neural model, the mathematical model of mobile robot, that combines its kinematic and dynamic properties such as chassis dimensions, center of gravity offset, friction and actuator parameters is used. Neural models are trained off-line to act as an inverse dynamics of DC motors with particular load using data collected in simulation experiment for motor input voltage step changes within bounded operating area. The performances of PI controllers versus inverse neural models in mobile robot internal velocity control loops are demonstrated and compared in simulation experiment of navigation control task for line segment motion in plane.
Extending Landauer's bound from bit erasure to arbitrary computation
NASA Astrophysics Data System (ADS)
Wolpert, David
The minimal thermodynamic work required to erase a bit, known as Landauer's bound, has been extensively investigated both theoretically and experimentally. However, when viewed as a computation that maps inputs to outputs, bit erasure has a very special property: the output does not depend on the input. Existing analyses of thermodynamics of bit erasure implicitly exploit this property, and thus cannot be directly extended to analyze the computation of arbitrary input-output maps. Here we show how to extend these earlier analyses of bit erasure to analyze the thermodynamics of arbitrary computations. Doing this establishes a formal connection between the thermodynamics of computers and much of theoretical computer science. We use this extension to analyze the thermodynamics of the canonical ``general purpose computer'' considered in computer science theory: a universal Turing machine (UTM). We consider a UTM which maps input programs to output strings, where inputs are drawn from an ensemble of random binary sequences, and prove: i) The minimal work needed by a UTM to run some particular input program X and produce output Y is the Kolmogorov complexity of Y minus the log of the ``algorithmic probability'' of Y. This minimal amount of thermodynamic work has a finite upper bound, which is independent of the output Y, depending only on the details of the UTM. ii) The expected work needed by a UTM to compute some given output Y is infinite. As a corollary, the overall expected work to run a UTM is infinite. iii) The expected work needed by an arbitrary Turing machine T (not necessarily universal) to compute some given output Y can either be infinite or finite, depending on Y and the details of T. To derive these results we must combine ideas from nonequilibrium statistical physics with fundamental results from computer science, such as Levin's coding theorem and other theorems about universal computation. I would like to ackowledge the Santa Fe Institute, Grant No. TWCF0079/AB47 from the Templeton World Charity Foundation, Grant No. FQXi-RHl3-1349 from the FQXi foundation, and Grant No. CHE-1648973 from the U.S. National Science Foundation.
Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets
NASA Astrophysics Data System (ADS)
Kim, S. K.; Prabhat, M.; Williams, D. N.
2017-12-01
Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.
Chen, Zhenfeng; Ge, Shuzhi Sam; Zhang, Yun; Li, Yanan
2014-11-01
This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. All subsystems within these MIMO nonlinear systems are of completely nonaffine pure-feedback form and allowed to have different orders. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. Such a design procedure can remove the couplings among subsystems and hence avoids the possible circular control construction problem. As a consequence, all the signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Moreover, the outputs of the systems are ensured to converge to a small neighborhood of the desired trajectories. Simulation studies verify the theoretical findings revealed in this paper.
De Nobili, M; Contin, M; Mahieu, N; Randall, E W; Brookes, P C
2008-01-01
Biological and chemical stabilization of organic C was assessed in soils sampled from the long-term experiments at Rothamsted (UK), representing a wide range of carbon inputs and managements by extracting labile, non-humified organic matter (NH) and humic substances (HS). Four sequentially extracted humic substances fractions of soil organic matter (SOM) were extracted and characterized before and after a 215-day laboratory incubation at 25 degrees C from two arable soils, a woodland soil and an occasionally stubbed soil. The fractions corresponded to biochemically stabilised SOM extracted in 0.5M NaOH (free fulvic acids (FA) and humic acids (HA)) and chemically plus biochemically stabilised SOM extracted from the residue with 0.1M Na4P2O7 plus 0.1M NaOH (bound FA and HA). Our aim was to investigate the effects of chemical and biochemical stabilization on carbon sequestration. The non-humic to humic (NH/H) C ratio separated the soils into two distinct groups: arable soils (unless fertilised with farmyard manure) had an NH/H C ratio between 1.05 and 0.71, about twice that of the other soils (0.51-0.26). During incubation a slow, but detectable, decrease in the NH/H C ratio occurred in soils of C input equivalent or lower to 4Mgha(-1)y(-1), whereas the ratio remained practically constant in the other soils. Before incubation the free to bound humic C ratio increased linearly (R2=0.91) with C inputs in the soils from the Broadbalk experiment and decreased during incubation, showing that biochemical stabilization is less effective than chemical stabilization in preserving humic C. Changes in delta13C and delta15N after incubation were confined to the free FA fractions. The delta13C of free FA increased by 1.48 and 0.80 per thousand, respectively, in the stubbed and woodland soils, indicating a progressive biological transformation. On the contrary, a decrease was observed for the bound FA of both soils. Concomitantly, a Deltadelta15N of up to +3.52 per thousand was measured after incubation in the free FA fraction and a -2.58 Deltadelta15N in the bound FA. These changes, which occurred during soil incubation in the absence of C inputs, indicate that free FA fractions were utilised by soil microorganisms, and bound FA were decomposed and replaced, in part, by newly synthesized FA. The 13CPMAS-TOSS NMR spectra of free HA extracted before and after 215 days of incubation were mostly unchanged. In contrast, changes were evident in bound HA and showed an increase in aromatic C after incubation.
Variational bounds on the temperature distribution
NASA Astrophysics Data System (ADS)
Kalikstein, Kalman; Spruch, Larry; Baider, Alberto
1984-02-01
Upper and lower stationary or variational bounds are obtained for functions which satisfy parabolic linear differential equations. (The error in the bound, that is, the difference between the bound on the function and the function itself, is of second order in the error in the input function, and the error is of known sign.) The method is applicable to a range of functions associated with equalization processes, including heat conduction, mass diffusion, electric conduction, fluid friction, the slowing down of neutrons, and certain limiting forms of the random walk problem, under conditions which are not unduly restrictive: in heat conduction, for example, we do not allow the thermal coefficients or the boundary conditions to depend upon the temperature, but the thermal coefficients can be functions of space and time and the geometry is unrestricted. The variational bounds follow from a maximum principle obeyed by the solutions of these equations.
Safa, Alireza; Abdolmalaki, Reza Yazdanpanah; Shafiee, Saeed; Sadeghi, Behzad
2018-06-01
In the field of nanotechnology, there is a growing demand to provide precision control and manipulation of devices with the ability to interact with complex and unstructured environments at micro/nano-scale. As a result, ultrahigh-precision positioning stages have been turned into a key requirement of nanotechnology. In this paper, linear piezoelectric ceramic motors (LPCMs) are adopted to drive micro/nanopositioning stages since they have the ability to achieve high precision in addition to being versatile to be implemented over a wide range of applications. In the establishment of a control scheme for such manipulation systems, the presence of friction, parameter uncertainties, and external disturbances prevent the systems from providing the desired positioning accuracy. The work in this paper focuses on the development of a control framework that addresses these issues as it uses the nonsingular terminal sliding mode technique for the precise position tracking problem of an LPCM-driven positioning stage with friction, uncertain parameters, and external disturbances. The developed control algorithm exhibits the following two attractive features. First, upper bounds of system uncertainties/perturbations are adaptively estimated in the proposed controller; thus, prior knowledge about uncertainty/disturbance bounds is not necessary. Second, the discontinuous signum function is transferred to the time derivative of the control input and the continuous control signal is obtained after integration; consequently, the chattering phenomenon, which presents a major handicap to the implementation of conventional sliding mode control in real applications, is alleviated without deteriorating the robustness of the system. The stability of the controlled system is analyzed, and the convergence of the position tracking error to zero is analytically proven. The proposed control strategy is experimentally validated and compared to the existing control approaches. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
John L. Campbell; James W. Hornbeck; Myron J. Mitchell; Mary Beth Adams; Mark S. Castro; Charles T. Driscoll; Jeffrey S. Kahl; James N. Kochenderfer; Gene E. Likens; James A. Lynch; Peter S. Murdoch; Sarah J. Nelson; James B. Shanley
2004-01-01
Input-output budgets for dissolved inorganic nitrogen (DIN) are summarized for 24 small watersheds at 15 locations in the northeastern United States. The study watersheds are completely forested, free of recent physical disturbances, and span a geographical region bounded by West Virginia on the south and west, and Maine on the north and east. Total N budgets are not...
The dynamic behaviour of data-driven Δ-M and ΔΣ-M in sliding mode control
NASA Astrophysics Data System (ADS)
Almakhles, Dhafer; Swain, Akshya K.; Nasiri, Alireza
2017-11-01
In recent years, delta (Δ-M) and delta-sigma modulators (ΔΣ-M) are increasingly being used as efficient data converters due to numerous advantages they offer. This paper investigates various dynamical features of these modulators/systems (both in continuous and discrete time domain) and derives their stability conditions using the theory of sliding mode. The upper bound of the hitting time (step) has been estimated. The equivalent mode conditions, i.e. where the outputs of the modulators are equivalent to the inputs, are established. The results of the analysis are validated through simulations considering a numerical example.
Scalable L-infinite coding of meshes.
Munteanu, Adrian; Cernea, Dan C; Alecu, Alin; Cornelis, Jan; Schelkens, Peter
2010-01-01
The paper investigates the novel concept of local-error control in mesh geometry encoding. In contrast to traditional mesh-coding systems that use the mean-square error as target distortion metric, this paper proposes a new L-infinite mesh-coding approach, for which the target distortion metric is the L-infinite distortion. In this context, a novel wavelet-based L-infinite-constrained coding approach for meshes is proposed, which ensures that the maximum error between the vertex positions in the original and decoded meshes is lower than a given upper bound. Furthermore, the proposed system achieves scalability in L-infinite sense, that is, any decoding of the input stream will correspond to a perfectly predictable L-infinite distortion upper bound. An instantiation of the proposed L-infinite-coding approach is demonstrated for MESHGRID, which is a scalable 3D object encoding system, part of MPEG-4 AFX. In this context, the advantages of scalable L-infinite coding over L-2-oriented coding are experimentally demonstrated. One concludes that the proposed L-infinite mesh-coding approach guarantees an upper bound on the local error in the decoded mesh, it enables a fast real-time implementation of the rate allocation, and it preserves all the scalability features and animation capabilities of the employed scalable mesh codec.
Control allocation-based adaptive control for greenhouse climate
NASA Astrophysics Data System (ADS)
Su, Yuanping; Xu, Lihong; Goodman, Erik D.
2018-04-01
This paper presents an adaptive approach to greenhouse climate control, as part of an integrated control and management system for greenhouse production. In this approach, an adaptive control algorithm is first derived to guarantee the asymptotic convergence of the closed system with uncertainty, then using that control algorithm, a controller is designed to satisfy the demands for heat and mass fluxes to maintain inside temperature, humidity and CO2 concentration at their desired values. Instead of applying the original adaptive control inputs directly, second, a control allocation technique is applied to distribute the demands of the heat and mass fluxes to the actuators by minimising tracking errors and energy consumption. To find an energy-saving solution, both single-objective optimisation (SOO) and multiobjective optimisation (MOO) in the control allocation structure are considered. The advantage of the proposed approach is that it does not require any a priori knowledge of the uncertainty bounds, and the simulation results illustrate the effectiveness of the proposed control scheme. It also indicates that MOO saves more energy in the control process.
Momentum distributions for H 2 ( e , e ' p )
Ford, William P.; Jeschonnek, Sabine; Van Orden, J. W.
2014-12-29
[Background] A primary goal of deuteron electrodisintegration is the possibility of extracting the deuteron momentum distribution. This extraction is inherently fraught with difficulty, as the momentum distribution is not an observable and the extraction relies on theoretical models dependent on other models as input. [Purpose] We present a new method for extracting the momentum distribution which takes into account a wide variety of model inputs thus providing a theoretical uncertainty due to the various model constituents. [Method] The calculations presented here are using a Bethe-Salpeter like formalism with a wide variety of bound state wave functions, form factors, and finalmore » state interactions. We present a method to extract the momentum distributions from experimental cross sections, which takes into account the theoretical uncertainty from the various model constituents entering the calculation. [Results] In order to test the extraction pseudo-data was generated, and the extracted "experimental'' distribution, which has theoretical uncertainty from the various model inputs, was compared with the theoretical distribution used to generate the pseudo-data. [Conclusions] In the examples we compared the original distribution was typically within the error band of the extracted distribution. The input wave functions do contain some outliers which are discussed in the text, but at least this process can provide an upper bound on the deuteron momentum distribution. Due to the reliance on the theoretical calculation to obtain this quantity any extraction method should account for the theoretical error inherent in these calculations due to model inputs.« less
Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.
Heydari, Ali; Balakrishnan, Sivasubramanya N
2013-01-01
To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.
Bagherpoor, H M; Salmasi, Farzad R
2015-07-01
In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan
2015-01-01
Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.
Regularized maximum pure-state input-output fidelity of a quantum channel
NASA Astrophysics Data System (ADS)
Ernst, Moritz F.; Klesse, Rochus
2017-12-01
As a toy model for the capacity problem in quantum information theory we investigate finite and asymptotic regularizations of the maximum pure-state input-output fidelity F (N ) of a general quantum channel N . We show that the asymptotic regularization F ˜(N ) is lower bounded by the maximum output ∞ -norm ν∞(N ) of the channel. For N being a Pauli channel, we find that both quantities are equal.
Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics
NASA Technical Reports Server (NTRS)
Rohrs, C. E.; Valavani, L.; Athans, M.; Stein, G.
1985-01-01
This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.
Lower bound for LCD image quality
NASA Astrophysics Data System (ADS)
Olson, William P.; Balram, Nikhil
1996-03-01
The paper presents an objective lower bound for the discrimination of patterns and fine detail in images on a monochrome LCD. In applications such as medical imaging and military avionics the information of interest is often at the highest frequencies in the image. Since LCDs are sampled data systems, their output modulation is dependent on the phase between the input signal and the sampling points. This phase dependence becomes particularly significant at high spatial frequencies. In order to use an LCD for applications such as those mentioned above it is essential to have a lower (worst case) bound on the performance of the display. We address this problem by providing a mathematical model for the worst case output modulation of an LCD in response to a sine wave input. This function can be interpreted as a worst case modulation transfer function (MTF). The intersection of the worst case MTF with the contrast threshold function (CTF) of the human visual system defines the highest spatial frequency that will always be detectable. In addition to providing the worst case limiting resolution, this MTF is combined with the CTF to produce objective worst case image quality values using the modulation transfer function area (MTFA) metric.
ERIC Educational Resources Information Center
Davis, Junius A.; Kenyon, Cynthia A.
In this volume is reported the review of related literature that was conducted during the design phase of the study (July 1973 through January 1974). Its purpose was to provide input for the study design. Chapter 1 is a summary of the findings judged most relevant to three basic questions: (1) Who are the disadvantaged, how are they defined, and…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Graham, Emily B.; Tfaily, Malak M.; Crump, Alex R.
In light of increasing terrestrial carbon (C) transport across aquatic boundaries, the mechanisms governing organic carbon (OC) oxidation along terrestrial-aquatic interfaces are crucial to future climate predictions. Here, we investigate biochemistry, metabolic pathways, and thermodynamics corresponding to OC oxidation in the Columbia River corridor. We leverage natural vegetative differences to encompass variation in terrestrial C inputs. Our results suggest that decreases in terrestrial C deposition associated with diminished riparian vegetation induce oxidation of physically-bound (i.e., mineral and microbial) OC at terrestrial-aquatic interfaces. We also find that contrasting metabolic pathways oxidize OC in the presence and absence of vegetation and—in directmore » conflict with the concept of ‘priming’—that inputs of water-soluble and thermodynamically-favorable terrestrial OC protects bound-OC from oxidation. Based on our results, we propose a mechanistic conceptualization of OC oxidation along terrestrial-aquatic interfaces that can be used to model heterogeneous patterns of OC loss under changing land cover distributions.« less
Fundamental bounds on the operation of Fano nonlinear isolators
NASA Astrophysics Data System (ADS)
Sounas, Dimitrios L.; Alù, Andrea
2018-03-01
Nonlinear isolators have attracted significant attention for their ability to break reciprocity and provide isolation without the need of an external bias. A popular approach for the design of such devices is based on Fano resonators, which, due to their sharp frequency response, can lead to very large isolation for moderate input intensities. Here, we show that, independent of their specific implementation, these devices are subject to fundamental bounds on the transmission coefficient in the forward direction versus their quality factor, input power, and nonreciprocal intensity range. Our analysis quantifies a general tradeoff between forward transmission and these metrics, stemming directly from time-reversal symmetry, and that unitary transmission is only possible for vanishing nonreciprocity. Our results also shed light on the operation of resonant nonlinear isolators, reveal their fundamental limitations, and provide indications on how it is possible to design nonlinear isolators with optimal performance.
Postselection technique for quantum channels with applications to quantum cryptography.
Christandl, Matthias; König, Robert; Renner, Renato
2009-01-16
We propose a general method for studying properties of quantum channels acting on an n-partite system, whose action is invariant under permutations of the subsystems. Our main result is that, in order to prove that a certain property holds for an arbitrary input, it is sufficient to consider the case where the input is a particular de Finetti-type state, i.e., a state which consists of n identical and independent copies of an (unknown) state on a single subsystem. Our technique can be applied to the analysis of information-theoretic problems. For example, in quantum cryptography, we get a simple proof for the fact that security of a discrete-variable quantum key distribution protocol against collective attacks implies security of the protocol against the most general attacks. The resulting security bounds are tighter than previously known bounds obtained with help of the exponential de Finetti theorem.
NASA Astrophysics Data System (ADS)
Alvarez, Diego A.; Uribe, Felipe; Hurtado, Jorge E.
2018-02-01
Random set theory is a general framework which comprises uncertainty in the form of probability boxes, possibility distributions, cumulative distribution functions, Dempster-Shafer structures or intervals; in addition, the dependence between the input variables can be expressed using copulas. In this paper, the lower and upper bounds on the probability of failure are calculated by means of random set theory. In order to accelerate the calculation, a well-known and efficient probability-based reliability method known as subset simulation is employed. This method is especially useful for finding small failure probabilities in both low- and high-dimensional spaces, disjoint failure domains and nonlinear limit state functions. The proposed methodology represents a drastic reduction of the computational labor implied by plain Monte Carlo simulation for problems defined with a mixture of representations for the input variables, while delivering similar results. Numerical examples illustrate the efficiency of the proposed approach.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nair, Ranjith
2011-09-15
We consider the problem of distinguishing, with minimum probability of error, two optical beam-splitter channels with unequal complex-valued reflectivities using general quantum probe states entangled over M signal and M' idler mode pairs of which the signal modes are bounced off the beam splitter while the idler modes are retained losslessly. We obtain a lower bound on the output state fidelity valid for any pure input state. We define number-diagonal signal (NDS) states to be input states whose density operator in the signal modes is diagonal in the multimode number basis. For such input states, we derive series formulas formore » the optimal error probability, the output state fidelity, and the Chernoff-type upper bounds on the error probability. For the special cases of quantum reading of a classical digital memory and target detection (for which the reflectivities are real valued), we show that for a given input signal photon probability distribution, the fidelity is minimized by the NDS states with that distribution and that for a given average total signal energy N{sub s}, the fidelity is minimized by any multimode Fock state with N{sub s} total signal photons. For reading of an ideal memory, it is shown that Fock state inputs minimize the Chernoff bound. For target detection under high-loss conditions, a no-go result showing the lack of appreciable quantum advantage over coherent state transmitters is derived. A comparison of the error probability performance for quantum reading of number state and two-mode squeezed vacuum state (or EPR state) transmitters relative to coherent state transmitters is presented for various values of the reflectances. While the nonclassical states in general perform better than the coherent state, the quantitative performance gains differ depending on the values of the reflectances. The experimental outlook for realizing nonclassical gains from number state transmitters with current technology at moderate to high values of the reflectances is argued to be good.« less
NASA Technical Reports Server (NTRS)
Glover, R. M.; Weinhold, F.
1977-01-01
Variational functionals of Braunn and Rebane (1972) for the imagery-frequency polarizability (IFP) have been generalized by the method of Gramian inequalities to give rigorous upper and lower bounds, valid even when the true (but unknown) unperturbed wavefunction must be represented by a variational approximation. Using these formulas in conjunction with flexible variational trial functions, tight error bounds are computed for the IFP and the associated two- and three-body van der Waals interaction constants of the ground 1(1S) and metastable 2(1,3S) states of He and Li(+). These bounds generally establish the ground-state properties to within a fraction of a per cent and metastable properties to within a few per cent, permitting a comparative assessment of competing theoretical methods at this level of accuracy. Unlike previous 'error bounds' for these properties, the present results have a completely a priori theoretical character, with no empirical input data.
Hybrid feedback feedforward: An efficient design of adaptive neural network control.
Pan, Yongping; Liu, Yiqi; Xu, Bin; Yu, Haoyong
2016-04-01
This paper presents an efficient hybrid feedback feedforward (HFF) adaptive approximation-based control (AAC) strategy for a class of uncertain Euler-Lagrange systems. The control structure includes a proportional-derivative (PD) control term in the feedback loop and a radial-basis-function (RBF) neural network (NN) in the feedforward loop, which mimics the human motor learning control mechanism. At the presence of discontinuous friction, a sigmoid-jump-function NN is incorporated to improve control performance. The major difference of the proposed HFF-AAC design from the traditional feedback AAC (FB-AAC) design is that only desired outputs, rather than both tracking errors and desired outputs, are applied as RBF-NN inputs. Yet, such a slight modification leads to several attractive properties of HFF-AAC, including the convenient choice of an approximation domain, the decrease of the number of RBF-NN inputs, and semiglobal practical asymptotic stability dominated by control gains. Compared with previous HFF-AAC approaches, the proposed approach possesses the following two distinctive features: (i) all above attractive properties are achieved by a much simpler control scheme; (ii) the bounds of plant uncertainties are not required to be known. Consequently, the proposed approach guarantees a minimum configuration of the control structure and a minimum requirement of plant knowledge for the AAC design, which leads to a sharp decrease of implementation cost in terms of hardware selection, algorithm realization and system debugging. Simulation results have demonstrated that the proposed HFF-AAC can perform as good as or even better than the traditional FB-AAC under much simpler control synthesis and much lower computational cost. Copyright © 2015 Elsevier Ltd. All rights reserved.
Multirate parallel distributed compensation of a cluster in wireless sensor and actor networks
NASA Astrophysics Data System (ADS)
Yang, Chun-xi; Huang, Ling-yun; Zhang, Hao; Hua, Wang
2016-01-01
The stabilisation problem for one of the clusters with bounded multiple random time delays and packet dropouts in wireless sensor and actor networks is investigated in this paper. A new multirate switching model is constructed to describe the feature of this single input multiple output linear system. According to the difficulty of controller design under multi-constraints in multirate switching model, this model can be converted to a Takagi-Sugeno fuzzy model. By designing a multirate parallel distributed compensation, a sufficient condition is established to ensure this closed-loop fuzzy control system to be globally exponentially stable. The solution of the multirate parallel distributed compensation gains can be obtained by solving an auxiliary convex optimisation problem. Finally, two numerical examples are given to show, compared with solving switching controller, multirate parallel distributed compensation can be obtained easily. Furthermore, it has stronger robust stability than arbitrary switching controller and single-rate parallel distributed compensation under the same conditions.
NASA Astrophysics Data System (ADS)
Lin, Tsung-Chih
2010-12-01
In this paper, a novel direct adaptive interval type-2 fuzzy-neural tracking control equipped with sliding mode and Lyapunov synthesis approach is proposed to handle the training data corrupted by noise or rule uncertainties for nonlinear SISO nonlinear systems involving external disturbances. By employing adaptive fuzzy-neural control theory, the update laws will be derived for approximating the uncertain nonlinear dynamical system. In the meantime, the sliding mode control method and the Lyapunov stability criterion are incorporated into the adaptive fuzzy-neural control scheme such that the derived controller is robust with respect to unmodeled dynamics, external disturbance and approximation errors. In comparison with conventional methods, the advocated approach not only guarantees closed-loop stability but also the output tracking error of the overall system will converge to zero asymptotically without prior knowledge on the upper bound of the lumped uncertainty. Furthermore, chattering effect of the control input will be substantially reduced by the proposed technique. To illustrate the performance of the proposed method, finally simulation example will be given.
Wei, Jianming; Zhang, Youan; Sun, Meimei; Geng, Baoliang
2017-09-01
This paper presents an adaptive iterative learning control scheme for a class of nonlinear systems with unknown time-varying delays and control direction preceded by unknown nonlinear backlash-like hysteresis. Boundary layer function is introduced to construct an auxiliary error variable, which relaxes the identical initial condition assumption of iterative learning control. For the controller design, integral Lyapunov function candidate is used, which avoids the possible singularity problem by introducing hyperbolic tangent funciton. After compensating for uncertainties with time-varying delays by combining appropriate Lyapunov-Krasovskii function with Young's inequality, an adaptive iterative learning control scheme is designed through neural approximation technique and Nussbaum function method. On the basis of the hyperbolic tangent function's characteristics, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function (CEF) in two cases, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Nonlinear control of linear parameter varying systems with applications to hypersonic vehicles
NASA Astrophysics Data System (ADS)
Wilcox, Zachary Donald
The focus of this dissertation is to design a controller for linear parameter varying (LPV) systems, apply it specifically to air-breathing hypersonic vehicles, and examine the interplay between control performance and the structural dynamics design. Specifically a Lyapunov-based continuous robust controller is developed that yields exponential tracking of a reference model, despite the presence of bounded, nonvanishing disturbances. The hypersonic vehicle has time varying parameters, specifically temperature profiles, and its dynamics can be reduced to an LPV system with additive disturbances. Since the HSV can be modeled as an LPV system the proposed control design is directly applicable. The control performance is directly examined through simulations. A wide variety of applications exist that can be effectively modeled as LPV systems. In particular, flight systems have historically been modeled as LPV systems and associated control tools have been applied such as gain-scheduling, linear matrix inequalities (LMIs), linear fractional transformations (LFT), and mu-types. However, as the type of flight environments and trajectories become more demanding, the traditional LPV controllers may no longer be sufficient. In particular, hypersonic flight vehicles (HSVs) present an inherently difficult problem because of the nonlinear aerothermoelastic coupling effects in the dynamics. HSV flight conditions produce temperature variations that can alter both the structural dynamics and flight dynamics. Starting with the full nonlinear dynamics, the aerothermoelastic effects are modeled by a temperature dependent, parameter varying state-space representation with added disturbances. The model includes an uncertain parameter varying state matrix, an uncertain parameter varying non-square (column deficient) input matrix, and an additive bounded disturbance. In this dissertation, a robust dynamic controller is formulated for a uncertain and disturbed LPV system. The developed controller is then applied to a HSV model, and a Lyapunov analysis is used to prove global exponential reference model tracking in the presence of uncertainty in the state and input matrices and exogenous disturbances. Simulations with a spectrum of gains and temperature profiles on the full nonlinear dynamic model of the HSV is used to illustrate the performance and robustness of the developed controller. In addition, this work considers how the performance of the developed controller varies over a wide variety of control gains and temperature profiles and are optimized with respect to different performance metrics. Specifically, various temperature profile models and related nonlinear temperature dependent disturbances are used to characterize the relative control performance and effort for each model. Examining such metrics as a function of temperature provides a potential inroad to examine the interplay between structural/thermal protection design and control development and has application for future HSV design and control implementation.
Thermodynamics of Computational Copying in Biochemical Systems
NASA Astrophysics Data System (ADS)
Ouldridge, Thomas E.; Govern, Christopher C.; ten Wolde, Pieter Rein
2017-04-01
Living cells use readout molecules to record the state of receptor proteins, similar to measurements or copies in typical computational devices. But is this analogy rigorous? Can cells be optimally efficient, and if not, why? We show that, as in computation, a canonical biochemical readout network generates correlations; extracting no work from these correlations sets a lower bound on dissipation. For general input, the biochemical network cannot reach this bound, even with arbitrarily slow reactions or weak thermodynamic driving. It faces an accuracy-dissipation trade-off that is qualitatively distinct from and worse than implied by the bound, and more complex steady-state copy processes cannot perform better. Nonetheless, the cost remains close to the thermodynamic bound unless accuracy is extremely high. Additionally, we show that biomolecular reactions could be used in thermodynamically optimal devices under exogenous manipulation of chemical fuels, suggesting an experimental system for testing computational thermodynamics.
NASA Astrophysics Data System (ADS)
Park, Jisang
In this dissertation, we investigate MIMO stability margin inference of a large number of controllers using pre-established stability margins of a small number of nu-gap-wise adjacent controllers. The generalized stability margin and the nu-gap metric are inherently able to handle MIMO system analysis without the necessity of repeating multiple channel-by-channel SISO analyses. This research consists of three parts: (i) development of a decision support tool for inference of the stability margin, (ii) computational considerations for yielding the maximal stability margin with the minimal nu-gap metric in a less conservative manner, and (iii) experiment design for estimating the generalized stability margin with an assured error bound. A modern problem from aerospace control involves the certification of a large set of potential controllers with either a single plant or a fleet of potential plant systems, with both plants and controllers being MIMO and, for the moment, linear. Experiments on a limited number of controller/plant pairs should establish the stability and a certain level of margin of the complete set. We consider this certification problem for a set of controllers and provide algorithms for selecting an efficient subset for testing. This is done for a finite set of candidate controllers and, at least for SISO plants, for an infinite set. In doing this, the nu-gap metric will be the main tool. We provide a theorem restricting a radius of a ball in the parameter space so that the controller can guarantee a prescribed level of stability and performance if parameters of the controllers are contained in the ball. Computational examples are given, including one of certification of an aircraft engine controller. The overarching aim is to introduce truly MIMO margin calculations and to understand their efficacy in certifying stability over a set of controllers and in replacing legacy single-loop gain and phase margin calculations. We consider methods for the computation of; maximal MIMO stability margins bP̂,C, minimal nu-gap metrics deltanu , and the maximal difference between these two values, through the use of scaling and weighting functions. We propose simultaneous scaling selections that attempt to maximize the generalized stability margin and minimize the nu-gap. The minimization of the nu-gap by scaling involves a non-convex optimization. We modify the XY-centering algorithm to handle this non-convexity. This is done for applications in controller certification. Estimating the generalized stability margin with an accurate error bound has significant impact on controller certification. We analyze an error bound of the generalized stability margin as the infinity norm of the MIMO empirical transfer function estimate (ETFE). Input signal design to reduce the error on the estimate is also studied. We suggest running the system for a certain amount of time prior to recording of each output data set. The assured upper bound of estimation error can be tuned by the amount of the pre-experiment.
Nowicki, Dimitri; Siegelmann, Hava
2010-01-01
This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces. PMID:20552013
Negative input for grammatical errors: effects after a lag of 12 weeks.
Saxton, Matthew; Backley, Phillip; Gallaway, Clare
2005-08-01
Effects of negative input for 13 categories of grammatical error were assessed in a longitudinal study of naturalistic adult-child discourse. Two-hour samples of conversational interaction were obtained at two points in time, separated by a lag of 12 weeks, for 12 children (mean age 2;0 at the start). The data were interpreted within the framework offered by Saxton's (1997, 2000) contrast theory of negative input. Corrective input was associated with subsequent improvements in the grammaticality of child speech for three of the target structures. No effects were found for two forms of positive input: non-contingent models, where the adult produces target structures in non-error-contingent contexts; and contingent models, where grammatical forms follow grammatical child usages. The findings lend support to the view that, in some cases at least, the structure of adult-child discourse yields information on the bounds of grammaticality for the language-learning child.
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.
Ni, Zhaokui; Wang, Shengrui
2015-12-01
China has been confronted with serious water quality deterioration concurrent with rapid socioeconomic progress during the past 40 years. Consequently, knowledge about economic growth and lake water quality dynamics is important to understand eutrophication processes. Objectives were to (i) reconstruct historical nutrient accumulation and the basin economic progress on burial flux (BF); (ii) determine forms and structures of nitrogen (N) and phosphorus (P) in sediment and water using six cores in three of the most severely eutrophic lake areas in China (i.e., Eastern Plain, Yunnan-Guizhou Plain, and Inner Mongolia-Xinjiang regions). Results suggest that BFs of total nitrogen (TN) continued to increase in sediment, whereas total phosphorus (TP) levels were consistent or only slightly increased, except in highly polluted lakes during the past decades. Similar results were observed for concentrations of nutrients in water (i.e., increased N/P). This historical distribution pattern was correlated to long-term fertilization practices of farmers in the watershed (N fertilization exceeds that of P) and was contingent upon pollution control policies (e.g., emphasized P whereas N was ignored). Vertical profiles of BFs indicated that lake nutrient accumulation included three stages in China. Nutrient accumulation started in the 1980s, accelerated from the 1990s, and then declined after 2000. Before the 1980s, nutrients were relatively low and stable, with nutrient inputs being controlled by natural processes. Thereafter, N- and P-bound sediments dramatically increased due to the increasing influence of anthropogenic processes. Nutrients were primarily derived from industries and domestic sewage. After 2000, BFs of nutrients were steady and even decreased, owing to implementation of watershed load reduction policies. The decreasing NaOH-extracted P (Fe/Al-P) and increasing organic phosphorus (OP) indicated that the source of exogenous pollution underwent a shift. Inputs of nutrients were predominantly from agricultural and domestic sewage, whereas industrial pollution has been gradually controlled in most of the watersheds. Historical nutrient dynamics suggest that the economy of China is growing at the expense of its aquatic ecological environments. Therefore, more attention to nutrient export to groundwater resulting from economic development is important for further aquatic ecosystem deterioration and eutrophication in China.
NASA Astrophysics Data System (ADS)
Beckwith, A. W.
2008-01-01
Sean Carroll's pre-inflation state of low temperature-low entropy provides a bridge between two models with different predictions. The Wheeler-de Witt equation provides thermal input into today's universe for graviton production. Also, brane world models by Sundrum allow low entropy conditions, as given by Carroll & Chen (2005). Moreover, this paper answers the question of how to go from a brane world model to the 10 to the 32 power Kelvin conditions stated by Weinberg in 1972 as necessary for the initiation of quantum gravity processes. This is a way of getting around the fact CMBR is cut off at a red shift of z = 1100. This paper discusses the difference in values of the upper bound of the cosmological constant between a large upper bound predicated for a temperature dependent vacuum energy predicted by Park (2002), and the much lower bound predicted by Barvinsky (2006). with the difference in values in vacuum energy contributing to relic graviton production. This paper claims that this large thermal influx, with a high initial cosmological constant and a large region of space for relic gravitons interacting with space-time up to the z = 1100 CMBR observational limit are interlinked processes delineated in the Lloyd (2002) analogy of the universe as a quantum computing system. Finally, the paper claims that linking a shrinking prior universe via a worm hole solution for a pseudo time dependent Wheeler-De Witt equation permits graviton generation as thermal input from the prior universe, transferred instantaneously to relic inflationary conditions today. The existence of a wormhole is presented as a necessary condition for relic gravitons. Proving the sufficiency of the existence of a worm hole for relic gravitons is a future project.
NASA Astrophysics Data System (ADS)
Zhou, Nanrun; Zhang, Aidi; Zheng, Fen; Gong, Lihua
2014-10-01
The existing ways to encrypt images based on compressive sensing usually treat the whole measurement matrix as the key, which renders the key too large to distribute and memorize or store. To solve this problem, a new image compression-encryption hybrid algorithm is proposed to realize compression and encryption simultaneously, where the key is easily distributed, stored or memorized. The input image is divided into 4 blocks to compress and encrypt, then the pixels of the two adjacent blocks are exchanged randomly by random matrices. The measurement matrices in compressive sensing are constructed by utilizing the circulant matrices and controlling the original row vectors of the circulant matrices with logistic map. And the random matrices used in random pixel exchanging are bound with the measurement matrices. Simulation results verify the effectiveness, security of the proposed algorithm and the acceptable compression performance.
NASA Technical Reports Server (NTRS)
Migneault, Gerard E.
1987-01-01
Emulation techniques can be a solution to a difficulty that arises in the analysis of the reliability of guidance and control computer systems for future commercial aircraft. Described here is the difficulty, the lack of credibility of reliability estimates obtained by analytical modeling techniques. The difficulty is an unavoidable consequence of the following: (1) a reliability requirement so demanding as to make system evaluation by use testing infeasible; (2) a complex system design technique, fault tolerance; (3) system reliability dominated by errors due to flaws in the system definition; and (4) elaborate analytical modeling techniques whose precision outputs are quite sensitive to errors of approximation in their input data. Use of emulation techniques for pseudo-testing systems to evaluate bounds on the parameter values needed for the analytical techniques is then discussed. Finally several examples of the application of emulation techniques are described.
Single-axis gyroscopic motion with uncertain angular velocity about spin axis
NASA Technical Reports Server (NTRS)
Singh, S. N.
1977-01-01
A differential game approach is presented for studying the response of a gyro by treating the controlled angular velocity about the input axis as the evader, and the bounded but uncertain angular velocity about the spin axis as the pursuer. When the uncertain angular velocity about the spin axis desires to force the gyro to saturation a differential game problem with two terminal surfaces results, whereas when the evader desires to attain the equilibrium state the usual game with single terminal manifold arises. A barrier, delineating the capture zone (CZ) in which the gyro can attain saturation and the escape zone (EZ) in which the evader avoids saturation is obtained. The CZ is further delineated into two subregions such that the states in each subregion can be forced on a definite target manifold. The application of the game theoretic approach to Control Moment Gyro is briefly discussed.
[Challenges and inputs of the gender perspective to the study of vector borne diseases].
Arenas-Monreal, Luz; Piña-Pozas, Maricela; Gómez-Dantés, Héctor
2015-01-01
The analysis of social determinants and gender within the health-disease-care process is an imperative to understand the variables that define the vulnerability of populations, their exposure risks, the determinants of their care, and the organization and participation in prevention and control programs. Ecohealth incorporates the study of the social determinants and gender perspectives because the emergency of dengue, malaria and Chagas disease are bound to unplanned urbanization, deficient sanitary infrastructure, and poor housing conditions. Gender emerges as an explanatory element of the roles played by men and women in the different scenarios (domestic, communitarian and social) that shape exposure risks to vectors and offer a better perspective of success for the prevention, control and care strategies. The objective is to contribute to the understanding on the gender perspective in the analysis of health risks through a conceptual framework.
TREATMENT OF HEAVY METALS IN STORMWATER RUNOFF USING WET POND AND WETLAND MESOCOSMS
Urban stormwater runoff is being recognized as a major source of pollutants to receiving waters and a number of recent investigations have evaluated stormwater runoff quality and best management practices to minimize pollutant input to receiving waters. Particle-bound contaminant...
NASA Technical Reports Server (NTRS)
Gaebler, John A.; Tolson, Robert H.
2010-01-01
In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.
Computing row and column counts for sparse QR and LU factorization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gilbert, John R.; Li, Xiaoye S.; Ng, Esmond G.
2001-01-01
We present algorithms to determine the number of nonzeros in each row and column of the factors of a sparse matrix, for both the QR factorization and the LU factorization with partial pivoting. The algorithms use only the nonzero structure of the input matrix, and run in time nearly linear in the number of nonzeros in that matrix. They may be used to set up data structures or schedule parallel operations in advance of the numerical factorization. The row and column counts we compute are upper bounds on the actual counts. If the input matrix is strong Hall and theremore » is no coincidental numerical cancellation, the counts are exact for QR factorization and are the tightest bounds possible for LU factorization. These algorithms are based on our earlier work on computing row and column counts for sparse Cholesky factorization, plus an efficient method to compute the column elimination tree of a sparse matrix without explicitly forming the product of the matrix and its transpose.« less
Bagheri, Pedram; Sun, Qiao
2016-07-01
In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
An adaptive learning control system for large flexible structures
NASA Technical Reports Server (NTRS)
Thau, F. E.
1985-01-01
The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.
Yan-Jun Liu; Shu Li; Shaocheng Tong; Chen, C L Philip
2017-07-01
In this paper, an adaptive control approach-based neural approximation is developed for a class of uncertain nonlinear discrete-time (DT) systems. The main characteristic of the considered systems is that they can be viewed as a class of multi-input multioutput systems in the nonstrict feedback structure. The similar control problem of this class of systems has been addressed in the past, but it focused on the continuous-time systems. Due to the complicacies of the system structure, it will become more difficult for the controller design and the stability analysis. To stabilize this class of systems, a new recursive procedure is developed, and the effect caused by the noncausal problem in the nonstrict feedback DT structure can be solved using a semirecurrent neural approximation. Based on the Lyapunov difference approach, it is proved that all the signals of the closed-loop system are semiglobal, ultimately uniformly bounded, and a good tracking performance can be guaranteed. The feasibility of the proposed controllers can be validated by setting a simulation example.
Reliable computation from contextual correlations
NASA Astrophysics Data System (ADS)
Oestereich, André L.; Galvão, Ernesto F.
2017-12-01
An operational approach to the study of computation based on correlations considers black boxes with one-bit inputs and outputs, controlled by a limited classical computer capable only of performing sums modulo-two. In this setting, it was shown that noncontextual correlations do not provide any extra computational power, while contextual correlations were found to be necessary for the deterministic evaluation of nonlinear Boolean functions. Here we investigate the requirements for reliable computation in this setting; that is, the evaluation of any Boolean function with success probability bounded away from 1 /2 . We show that bipartite CHSH quantum correlations suffice for reliable computation. We also prove that an arbitrarily small violation of a multipartite Greenberger-Horne-Zeilinger noncontextuality inequality also suffices for reliable computation.
Real-Time Parameter Estimation in the Frequency Domain
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
2000-01-01
A method for real-time estimation of parameters in a linear dynamic state-space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than one cycle of the dominant dynamic mode, using no a priori information, with control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements and could be implemented
NASA Astrophysics Data System (ADS)
Rivera, Diego; Rivas, Yessica; Godoy, Alex
2015-02-01
Hydrological models are simplified representations of natural processes and subject to errors. Uncertainty bounds are a commonly used way to assess the impact of an input or model architecture uncertainty in model outputs. Different sets of parameters could have equally robust goodness-of-fit indicators, which is known as Equifinality. We assessed the outputs from a lumped conceptual hydrological model to an agricultural watershed in central Chile under strong interannual variability (coefficient of variability of 25%) by using the Equifinality concept and uncertainty bounds. The simulation period ran from January 1999 to December 2006. Equifinality and uncertainty bounds from GLUE methodology (Generalized Likelihood Uncertainty Estimation) were used to identify parameter sets as potential representations of the system. The aim of this paper is to exploit the use of uncertainty bounds to differentiate behavioural parameter sets in a simple hydrological model. Then, we analyze the presence of equifinality in order to improve the identification of relevant hydrological processes. The water balance model for Chillan River exhibits, at a first stage, equifinality. However, it was possible to narrow the range for the parameters and eventually identify a set of parameters representing the behaviour of the watershed (a behavioural model) in agreement with observational and soft data (calculation of areal precipitation over the watershed using an isohyetal map). The mean width of the uncertainty bound around the predicted runoff for the simulation period decreased from 50 to 20 m3s-1 after fixing the parameter controlling the areal precipitation over the watershed. This decrement is equivalent to decreasing the ratio between simulated and observed discharge from 5.2 to 2.5. Despite the criticisms against the GLUE methodology, such as the lack of statistical formality, it is identified as a useful tool assisting the modeller with the identification of critical parameters.
NASA Astrophysics Data System (ADS)
Iyyappan, I.; Ponmurugan, M.
2018-03-01
A trade of figure of merit (\\dotΩ ) criterion accounts the best compromise between the useful input energy and the lost input energy of the heat devices. When the heat engine is working at maximum \\dotΩ criterion its efficiency increases significantly from the efficiency at maximum power. We derive the general relations between the power, efficiency at maximum \\dotΩ criterion and minimum dissipation for the linear irreversible heat engine. The efficiency at maximum \\dotΩ criterion has the lower bound \
NASA Astrophysics Data System (ADS)
Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping
2018-05-01
In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.
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New Hardness Results for Diophantine Approximation
NASA Astrophysics Data System (ADS)
Eisenbrand, Friedrich; Rothvoß, Thomas
We revisit simultaneous Diophantine approximation, a classical problem from the geometry of numbers which has many applications in algorithms and complexity. The input to the decision version of this problem consists of a rational vector α ∈ ℚ n , an error bound ɛ and a denominator bound N ∈ ℕ + . One has to decide whether there exists an integer, called the denominator Q with 1 ≤ Q ≤ N such that the distance of each number Q ·α i to its nearest integer is bounded by ɛ. Lagarias has shown that this problem is NP-complete and optimization versions have been shown to be hard to approximate within a factor n c/ loglogn for some constant c > 0. We strengthen the existing hardness results and show that the optimization problem of finding the smallest denominator Q ∈ ℕ + such that the distances of Q·α i to the nearest integer are bounded by ɛ is hard to approximate within a factor 2 n unless {textrm{P}} = NP.
Wang, Yan-Wu; Bian, Tao; Xiao, Jiang-Wen; Wen, Changyun
2015-10-01
This paper studies the global synchronization of complex dynamical network (CDN) under digital communication with limited bandwidth. To realize the digital communication, the so-called uniform-quantizer-sets are introduced to quantize the states of nodes, which are then encoded and decoded by newly designed encoders and decoders. To meet the requirement of the bandwidth constraint, a scaling function is utilized to guarantee the quantizers having bounded inputs and thus achieving bounded real-time quantization levels. Moreover, a new type of vector norm is introduced to simplify the expression of the bandwidth limit. Through mathematical induction, a sufficient condition is derived to ensure global synchronization of the CDNs. The lower bound on the sum of the real-time quantization levels is analyzed for different cases. Optimization method is employed to relax the requirements on the network topology and to determine the minimum of such lower bound for each case, respectively. Simulation examples are also presented to illustrate the established results.
Pre-Test Assessment of the Upper Bound of the Drag Coefficient Repeatability of a Wind Tunnel Model
NASA Technical Reports Server (NTRS)
Ulbrich, N.; L'Esperance, A.
2017-01-01
A new method is presented that computes a pre{test estimate of the upper bound of the drag coefficient repeatability of a wind tunnel model. This upper bound is a conservative estimate of the precision error of the drag coefficient. For clarity, precision error contributions associated with the measurement of the dynamic pressure are analyzed separately from those that are associated with the measurement of the aerodynamic loads. The upper bound is computed by using information about the model, the tunnel conditions, and the balance in combination with an estimate of the expected output variations as input. The model information consists of the reference area and an assumed angle of attack. The tunnel conditions are described by the Mach number and the total pressure or unit Reynolds number. The balance inputs are the partial derivatives of the axial and normal force with respect to all balance outputs. Finally, an empirical output variation of 1.0 microV/V is used to relate both random instrumentation and angle measurement errors to the precision error of the drag coefficient. Results of the analysis are reported by plotting the upper bound of the precision error versus the tunnel conditions. The analysis shows that the influence of the dynamic pressure measurement error on the precision error of the drag coefficient is often small when compared with the influence of errors that are associated with the load measurements. Consequently, the sensitivities of the axial and normal force gages of the balance have a significant influence on the overall magnitude of the drag coefficient's precision error. Therefore, results of the error analysis can be used for balance selection purposes as the drag prediction characteristics of balances of similar size and capacities can objectively be compared. Data from two wind tunnel models and three balances are used to illustrate the assessment of the precision error of the drag coefficient.
Revenue Windfalls and School Input Choices.
ERIC Educational Resources Information Center
Fleeter, Howard B.; Marvel, Mary K.
1997-01-01
Revenue generated by nonresidential property sources poses a different set of constraints on school expenditures than does revenue generated by residential property sources. The fortunes of an Ohio school system seem bound up with Honda's local success. Marysville's total spending per pupil continues to lag behind that in comparable districts,…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Host, Ole; Lahav, Ofer; Abdalla, Filipe B.
We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological observations. We compare the frequentist and Bayesian bounds on the effective electron neutrino mass m{sub {beta}} which the KATRIN neutrino mass experiment is expected to obtain, using both an analytical likelihood function and Monte Carlo simulations of KATRIN. Assuming a uniform prior in m{sub {beta}}, we find that a null result yields an upper bound of about 0.17 eV at 90% confidence in the Bayesian analysis, to be compared with the frequentist KATRIN reference value of 0.20 eV. This is a significant difference whenmore » judged relative to the systematic and statistical uncertainties of the experiment. On the other hand, an input m{sub {beta}}=0.35 eV, which is the KATRIN 5{sigma} detection threshold, would be detected at virtually the same level. Finally, we combine the simulated KATRIN results with cosmological data in the form of present (post-WMAP) and future (simulated Planck) observations. If an input of m{sub {beta}}=0.2 eV is assumed in our simulations, KATRIN alone excludes a zero neutrino mass at 2.2{sigma}. Adding Planck data increases the probability of detection to a median 2.7{sigma}. The analysis highlights the importance of combining cosmological and laboratory data on an equal footing.« less
Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip
2017-10-01
This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.
Eckley, Chris S; Branfireun, Brian
2009-08-01
This research focuses on mercury (Hg) mobilization in stormwater runoff from an urban roadway. The objectives were to determine: how the transport of surface-derived Hg changes during an event hydrograph; the influence of antecedent dry days on the runoff Hg load; the relationship between total suspended sediments (TSS) and Hg transport, and; the fate of new Hg input in rain and its relative importance to the runoff Hg load. Simulated rain events were used to control variables to elucidate transport processes and a Hg stable isotope was used to trace the fate of Hg inputs in rain. The results showed that Hg concentrations were highest at the beginning of the hydrograph and were predominantly particulate bound (HgP). On average, almost 50% of the total Hg load was transported during the first minutes of runoff, underscoring the importance of the initial runoff on load calculations. Hg accumulated on the road surface during dry periods resulting in the Hg runoff load increasing with antecedent dry days. The Hg concentrations in runoff were significantly correlated with TSS concentrations (mean r(2)=0.94+/-0.09). The results from the isotope experiments showed that the new Hg inputs quickly become associated with the surface particles and that the majority of Hg in runoff is derived from non-event surface-derived sources.
Reaching the Quantum Cramér-Rao Bound for Transmission Measurements
NASA Astrophysics Data System (ADS)
Woodworth, Timothy; Chan, Kam Wai Clifford; Marino, Alberto
2017-04-01
The quantum Cramér-Rao bound (QCRB) is commonly used to quantify the lower bound for the uncertainty in the estimation of a given parameter. Here, we calculate the QCRB for transmission measurements of an optical system probed by a beam of light. Estimating the transmission of an optical element is important as it is required for the calibration of optimal states for interferometers, characterization of high efficiency photodetectors, or as part of other measurements, such as those in plasmonic sensors or in ellipsometry. We use a beam splitter model for the losses introduced by the optical system to calculate the QCRB for different input states. We compare the bound for a coherent state, a two-mode squeezed-state (TMSS), a single-mode squeezed-state (SMSS), and a Fock state and show that it is possible to obtain an ultimate lower bound, regardless of the state used to probe the system. We prove that the Fock state gives the lowest possible uncertainty in estimating the transmission for any state and demonstrate that the TMSS and SMSS approach this ultimate bound for large levels of squeezing. Finally, we show that a simple measurement strategy for the TMSS, namely an intensity difference measurement, is able to saturate the QCRB. Work supported by the W.M. Keck Foundation.
Neural networks with local receptive fields and superlinear VC dimension.
Schmitt, Michael
2002-04-01
Local receptive field neurons comprise such well-known and widely used unit types as radial basis function (RBF) neurons and neurons with center-surround receptive field. We study the Vapnik-Chervonenkis (VC) dimension of feedforward neural networks with one hidden layer of these units. For several variants of local receptive field neurons, we show that the VC dimension of these networks is superlinear. In particular, we establish the bound Omega(W log k) for any reasonably sized network with W parameters and k hidden nodes. This bound is shown to hold for discrete center-surround receptive field neurons, which are physiologically relevant models of cells in the mammalian visual system, for neurons computing a difference of gaussians, which are popular in computational vision, and for standard RBF neurons, a major alternative to sigmoidal neurons in artificial neural networks. The result for RBF neural networks is of particular interest since it answers a question that has been open for several years. The results also give rise to lower bounds for networks with fixed input dimension. Regarding constants, all bounds are larger than those known thus far for similar architectures with sigmoidal neurons. The superlinear lower bounds contrast with linear upper bounds for single local receptive field neurons also derived here.
From attentional gating in macaque primary visual cortex to dyslexia in humans.
Vidyasagar, T R
2001-01-01
Selective attention is an important aspect of brain function that we need in coping with the immense and constant barrage of sensory information. One model of attention (Feature Integration Theory) that suggests an early selection of spatial locations of objects via an attentional spotlight would also solve the 'binding problem' (that is how do different attributes of each object get correctly bound together?). Our experiments have demonstrated modulation of specific locations of interest at the level of the primary visual cortex both in visual discrimination and memory tasks, where the actual locations of the targets was also important in being able to perform the task. It is suggested that the feedback mediating the modulation arises from the posterior parietal cortex, which would also be consistent with its known role in attentional control. In primates, the magnocellular (M) and parvocellular (P) pathways are the two major streams of inputs from the retina, carrying distinctly different types of information and they remain fairly segregated in their projections to the primary visual cortex and further into the extra-striate regions. The P inputs go mainly into the ventral (temporal) stream, while the dorsal (parietal) stream is dominated by M inputs. A theory of attentional gating is proposed here where the M dominated dorsal stream gates the P inputs into the ventral stream. This framework is used to provide a neural explanation of the processes involved in reading and in learning to read. This scheme also explains how a magnocellular deficit could cause the common reading impairment, dyslexia.
NASA Astrophysics Data System (ADS)
Efrain Humpire-Mamani, Gabriel; Arindra Adiyoso Setio, Arnaud; van Ginneken, Bram; Jacobs, Colin
2018-04-01
Automatic localization of organs and other structures in medical images is an important preprocessing step that can improve and speed up other algorithms such as organ segmentation, lesion detection, and registration. This work presents an efficient method for simultaneous localization of multiple structures in 3D thorax-abdomen CT scans. Our approach predicts the location of multiple structures using a single multi-label convolutional neural network for each orthogonal view. Each network takes extra slices around the current slice as input to provide extra context. A sigmoid layer is used to perform multi-label classification. The output of the three networks is subsequently combined to compute a 3D bounding box for each structure. We used our approach to locate 11 structures of interest. The neural network was trained and evaluated on a large set of 1884 thorax-abdomen CT scans from patients undergoing oncological workup. Reference bounding boxes were annotated by human observers. The performance of our method was evaluated by computing the wall distance to the reference bounding boxes. The bounding boxes annotated by the first human observer were used as the reference standard for the test set. Using the best configuration, we obtained an average wall distance of 3.20~+/-~7.33 mm in the test set. The second human observer achieved 1.23~+/-~3.39 mm. For all structures, the results were better than those reported in previously published studies. In conclusion, we proposed an efficient method for the accurate localization of multiple organs. Our method uses multiple slices as input to provide more context around the slice under analysis, and we have shown that this improves performance. This method can easily be adapted to handle more organs.
Functional Adaptation of the Calcaneus in Historical Foot Binding
Reznikov, Natalie; Phillips, Carina; Cooke, Martyn; Garbout, Amin; Ahmed, Farah
2017-01-01
ABSTRACT The normal structure of human feet is optimized for shock dampening during walking and running. Foot binding was a historical practice in China aimed at restricting the growth of female feet for aesthetic reasons. In a bound foot the shock‐dampening function normally facilitated by the foot arches is withdrawn, resulting in the foot functioning as a rigid extension of the lower leg. An interesting question inspiring this study regards the nature of adaptation of the heel bone to this nonphysiological function using the parameters of cancellous bone anisotropy and 3D fabric topology and a novel intertrabecular angle (ITA) analysis. We found that the trabecular microarchitecture of the normal heel bone, but not of the bound foot, adapts to function by increased anisotropy and preferred orientation of trabeculae. The anisotropic texture in the normal heel bone consistently follows the physiological stress trajectories. However, in the bound foot heel bone the characteristic anisotropy pattern fails to develop, reflecting the lack of a normal biomechanical input. Moreover, the basic topological blueprint of cancellous bone investigated by the ITA method is nearly invariant in both normal and bound foot. These findings suggest that the anisotropic cancellous bone texture is an acquired characteristic that reflects recurrent loading conditions; conversely, an inadequate biomechanical input precludes the formation of anisotropic texture. This opens a long‐sought‐after possibility to reconstruct bone function from its form. The conserved topological parameters characterize the generic 3D fabric of cancellous bone, which is to a large extent independent of its adaptation to recurrent loading and perhaps determines the mechanical competence of trabecular bone regardless of its functional adaptation. © 2017 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals Inc. PMID:28561380
Functional Adaptation of the Calcaneus in Historical Foot Binding.
Reznikov, Natalie; Phillips, Carina; Cooke, Martyn; Garbout, Amin; Ahmed, Farah; Stevens, Molly M
2017-09-01
The normal structure of human feet is optimized for shock dampening during walking and running. Foot binding was a historical practice in China aimed at restricting the growth of female feet for aesthetic reasons. In a bound foot the shock-dampening function normally facilitated by the foot arches is withdrawn, resulting in the foot functioning as a rigid extension of the lower leg. An interesting question inspiring this study regards the nature of adaptation of the heel bone to this nonphysiological function using the parameters of cancellous bone anisotropy and 3D fabric topology and a novel intertrabecular angle (ITA) analysis. We found that the trabecular microarchitecture of the normal heel bone, but not of the bound foot, adapts to function by increased anisotropy and preferred orientation of trabeculae. The anisotropic texture in the normal heel bone consistently follows the physiological stress trajectories. However, in the bound foot heel bone the characteristic anisotropy pattern fails to develop, reflecting the lack of a normal biomechanical input. Moreover, the basic topological blueprint of cancellous bone investigated by the ITA method is nearly invariant in both normal and bound foot. These findings suggest that the anisotropic cancellous bone texture is an acquired characteristic that reflects recurrent loading conditions; conversely, an inadequate biomechanical input precludes the formation of anisotropic texture. This opens a long-sought-after possibility to reconstruct bone function from its form. The conserved topological parameters characterize the generic 3D fabric of cancellous bone, which is to a large extent independent of its adaptation to recurrent loading and perhaps determines the mechanical competence of trabecular bone regardless of its functional adaptation. © 2017 American Society for Bone and Mineral Research. © 2017 American Society for Bone and Mineral Research.
Liu, Lei; Wang, Zhanshan; Zhang, Huaguang
2018-04-01
This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.
He, Pingan; Jagannathan, S
2007-04-01
A novel adaptive-critic-based neural network (NN) controller in discrete time is designed to deliver a desired tracking performance for a class of nonlinear systems in the presence of actuator constraints. The constraints of the actuator are treated in the controller design as the saturation nonlinearity. The adaptive critic NN controller architecture based on state feedback includes two NNs: the critic NN is used to approximate the "strategic" utility function, whereas the action NN is employed to minimize both the strategic utility function and the unknown nonlinear dynamic estimation errors. The critic and action NN weight updates are derived by minimizing certain quadratic performance indexes. Using the Lyapunov approach and with novel weight updates, the uniformly ultimate boundedness of the closed-loop tracking error and weight estimates is shown in the presence of NN approximation errors and bounded unknown disturbances. The proposed NN controller works in the presence of multiple nonlinearities, unlike other schemes that normally approximate one nonlinearity. Moreover, the adaptive critic NN controller does not require an explicit offline training phase, and the NN weights can be initialized at zero or random. Simulation results justify the theoretical analysis.
Automatic Estimation of Verified Floating-Point Round-Off Errors via Static Analysis
NASA Technical Reports Server (NTRS)
Moscato, Mariano; Titolo, Laura; Dutle, Aaron; Munoz, Cesar A.
2017-01-01
This paper introduces a static analysis technique for computing formally verified round-off error bounds of floating-point functional expressions. The technique is based on a denotational semantics that computes a symbolic estimation of floating-point round-o errors along with a proof certificate that ensures its correctness. The symbolic estimation can be evaluated on concrete inputs using rigorous enclosure methods to produce formally verified numerical error bounds. The proposed technique is implemented in the prototype research tool PRECiSA (Program Round-o Error Certifier via Static Analysis) and used in the verification of floating-point programs of interest to NASA.
Some Factor Analytic Approximations to Latent Class Structure.
ERIC Educational Resources Information Center
Dziuban, Charles D.; Denton, William T.
Three procedures, alpha, image, and uniqueness rescaling, were applied to a joint occurrence probability matrix. That matrix was the basis of a well-known latent class structure. The values of the recurring subscript elements were varied as follows: Case 1 - The known elements were input; Case 2 - The upper bounds to the recurring subscript…
Systematics of intermediate-energy single-nucleon removal cross sections
NASA Astrophysics Data System (ADS)
Tostevin, J. A.; Gade, A.
2014-11-01
There is now a large and increasing body of experimental data and theoretical analyses for reactions that remove a single nucleon from an intermediate-energy beam of neutron- or proton-rich nuclei. In each such measurement, one obtains the inclusive cross section for the population of all bound final states of the mass A -1 reaction residue. These data, from different regions of the nuclear chart, and that involve weakly and strongly bound nucleons, are compared with theoretical expectations. These calculations include an approximate treatment of the reaction dynamics and shell-model descriptions of the projectile initial state, the bound final states of the residues, and the single-particle strengths computed from their overlap functions. The results are discussed in the light of recent data, more exclusive tests of the eikonal dynamical description, and calculations that take input from more microscopic nuclear structure models.
Constraining astrophysical neutrino flavor composition from leptonic unitarity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Xun-Jie; He, Hong-Jian; Rodejohann, Werner, E-mail: xunjie.xu@gmail.com, E-mail: hjhe@tsinghua.edu.cn, E-mail: werner.rodejohann@mpi-hd.mpg.de
2014-12-01
The recent IceCube observation of ultra-high-energy astrophysical neutrinos has begun the era of neutrino astronomy. In this work, using the unitarity of leptonic mixing matrix, we derive nontrivial unitarity constraints on the flavor composition of astrophysical neutrinos detected by IceCube. Applying leptonic unitarity triangles, we deduce these unitarity bounds from geometrical conditions, such as triangular inequalities. These new bounds generally hold for three flavor neutrinos, and are independent of any experimental input or the pattern of lepton mixing. We apply our unitarity bounds to derive general constraints on the flavor compositions for three types of astrophysical neutrino sources (and theirmore » general mixture), and compare them with the IceCube measurements. Furthermore, we prove that for any sources without ν{sub τ} neutrinos, a detected ν{sub μ} flux ratio < 1/4 will require the initial flavor composition with more ν{sub e} neutrinos than ν{sub μ} neutrinos.« less
Asymmetric effects of luminance and chrominance in the watercolor illusion
Coia, Andrew J.; Crognale, Michael A.
2014-01-01
When bounded by a line of sufficient contrast, the desaturated hue of a colored line will spread over an enclosed area, an effect known as the watercolor illusion. The contrast of the two lines can be in luminance, chromaticity, or a combination of both. The effect is most salient when the enclosing line has greater contrast with the background than the line that induces the spreading color. In most prior experiments with watercolor spreading, the luminance of both lines has been lower than the background. An achromatic version of the illusion exists where a dark line will spread while being bounded by either a darker or brighter line. In a previous study we measured the strength of the watercolor effect in which the colored inducing line was isoluminant to the background, and found an illusion for both brighter and darker achromatic outer contours. We also found the strength of spreading is stronger for bluish (+S cone input) colors compared to yellowish (−S cone input) ones, when bounded by a dark line. The current study set out to measure the hue dependence of the watercolor illusion when inducing colors are flanked with brighter (increment) as opposed to darker outer lines. The asymmetry in the watercolor effect with S cone input was enhanced when the inducing contrast was an increment rather than a decrement. Further experiments explored the relationship between the perceived contrast of these chromatic lines when paired with luminance increments and decrements and revealed that the perceived contrast of luminance increments and decrements is dependent on which isoluminant color they are paired with. In addition to known hue asymmetries in the watercolor illusion there are asymmetries between luminance increments and decrements that are also hue dependent. These latter asymmetries may be related to the perceived contrast of the hue/luminance parings. PMID:25309396
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.
Deepika; Kaur, Sandeep; Narayan, Shiv
2018-06-01
This paper proposes a novel fractional order sliding mode control approach to address the issues of stabilization as well as tracking of an N-dimensional extended chained form of fractional order non-holonomic system. Firstly, the hierarchical fractional order terminal sliding manifolds are selected to procure the desired objectives in finite time. Then, a sliding mode control law is formulated which provides robustness against various system uncertainties or external disturbances. In addition, a novel fractional order uncertainty estimator is deduced mathematically to estimate and mitigate the effects of uncertainties, which also excludes the requirement of their upper bounds. Due to the omission of discontinuous control action, the proposed algorithm ensures a chatter-free control input. Moreover, the finite time stability of the closed loop system has been proved analytically through well known Mittag-Leffler and Fractional Lyapunov theorems. Finally, the proposed methodology is validated with MATLAB simulations on two examples including an application of fractional order non-holonomic wheeled mobile robot and its performances are also compared with the existing control approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Luy, N. T.
2018-04-01
The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harmon, Brooke; Chylek, Lily A.; Liu, Yanli
The high-affinity receptor for IgE expressed on the surface of mast cells and basophils interacts with antigens, via bound IgE antibody, and triggers secretion of inflammatory mediators that contribute to allergic reactions. To understand how past inputs (memory) influence future inflammatory responses in mast cells, a microfluidic device was used to precisely control exposure of cells to alternating stimulatory and non-stimulatory inputs. We determined that the response to subsequent stimulation depends on the interval of signaling quiescence. For shorter intervals of signaling quiescence, the second response is blunted relative to the first response, whereas longer intervals of quiescence induce anmore » enhanced second response. Through an iterative process of computational modeling and experimental tests, we found that these memory-like phenomena arise from a confluence of rapid, short-lived positive signals driven by the protein tyrosine kinase Syk; slow, long-lived negative signals driven by the lipid phosphatase Ship1; and slower degradation of Ship1 co-factors. This work advances our understanding of mast cell signaling and represents a generalizable approach for investigating the dynamics of signaling systems.« less
Voluntary and Involuntary Movements Widen the Window of Subjective Simultaneity.
Arikan, B Ezgi; van Kemenade, Bianca M; Straube, Benjamin; Harris, Laurence R; Kircher, Tilo
2017-01-01
Forming a coherent percept of an event requires different sensory inputs originating from the event to be bound. Perceiving synchrony aids in binding of these inputs. In two experiments, we investigated how voluntary movements influence the perception of simultaneity, by measuring simultaneity judgments (SJs) for an audiovisual (AV) stimulus pair triggered by a voluntary button press. In Experiment 1, we manipulated contiguity between the action and its consequences by introducing delays between the button press and the AV stimulus pair. We found a widened window of subjective simultaneity (WSS) when the action-feedback relationship was time contiguous. Introducing a delay narrowed the WSS, suggesting that the wider WSS around the time of an action might facilitate perception of simultaneity. In Experiment 2, we introduced an involuntary condition using an externally controlled button to assess the influence of action-related predictive processes on SJs. We found a widened WSS around the action time, regardless of movement type, supporting the influence of causal relations in the perception of synchrony. Interestingly, the slopes of the psychometric functions in the voluntary condition were significantly steeper than the slopes in the involuntary condition, suggesting a role of action-related predictive mechanisms in making SJs more precise.
Voluntary and Involuntary Movements Widen the Window of Subjective Simultaneity
Arikan, B. Ezgi; van Kemenade, Bianca M.; Straube, Benjamin; Harris, Laurence R.; Kircher, Tilo
2017-01-01
Forming a coherent percept of an event requires different sensory inputs originating from the event to be bound. Perceiving synchrony aids in binding of these inputs. In two experiments, we investigated how voluntary movements influence the perception of simultaneity, by measuring simultaneity judgments (SJs) for an audiovisual (AV) stimulus pair triggered by a voluntary button press. In Experiment 1, we manipulated contiguity between the action and its consequences by introducing delays between the button press and the AV stimulus pair. We found a widened window of subjective simultaneity (WSS) when the action-feedback relationship was time contiguous. Introducing a delay narrowed the WSS, suggesting that the wider WSS around the time of an action might facilitate perception of simultaneity. In Experiment 2, we introduced an involuntary condition using an externally controlled button to assess the influence of action-related predictive processes on SJs. We found a widened WSS around the action time, regardless of movement type, supporting the influence of causal relations in the perception of synchrony. Interestingly, the slopes of the psychometric functions in the voluntary condition were significantly steeper than the slopes in the involuntary condition, suggesting a role of action-related predictive mechanisms in making SJs more precise. PMID:28835813
Ye, Linqi; Zong, Qun; Tian, Bailing; Zhang, Xiuyun; Wang, Fang
2017-09-01
In this paper, the nonminimum phase problem of a flexible hypersonic vehicle is investigated. The main challenge of nonminimum phase is the prevention of dynamic inversion methods to nonlinear control design. To solve this problem, we make research on the relationship between nonminimum phase and backstepping control, finding that a stable nonlinear controller can be obtained by changing the control loop on the basis of backstepping control. By extending the control loop to cover the internal dynamics in it, the internal states are directly controlled by the inputs and simultaneously serve as virtual control for the external states, making it possible to guarantee output tracking as well as internal stability. Then, based on the extended control loop, a simplified control-oriented model is developed to enable the applicability of adaptive backstepping method. It simplifies the design process and releases some limitations caused by direct use of the no simplified control-oriented model. Next, under proper assumptions, asymptotic stability is proved for constant commands, while bounded stability is proved for varying commands. The proposed method is compared with approximate backstepping control and dynamic surface control and is shown to have superior tracking accuracy as well as robustness from the simulation results. This paper may also provide a beneficial guidance for control design of other complex systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Jia, Zi-Jun; Song, Yong-Duan
2017-06-01
This paper presents a new approach to construct neural adaptive control for uncertain nonaffine systems. By integrating locally weighted learning with barrier Lyapunov function (BLF), a novel control design method is presented to systematically address the two critical issues in neural network (NN) control field: one is how to fulfill the compact set precondition for NN approximation, and the other is how to use varying rather than a fixed NN structure to improve the functionality of NN control. A BLF is exploited to ensure the NN inputs to remain bounded during the entire system operation. To account for system nonlinearities, a neuron self-growing strategy is proposed to guide the process for adding new neurons to the system, resulting in a self-adjustable NN structure for better learning capabilities. It is shown that the number of neurons needed to accomplish the control task is finite, and better performance can be obtained with less number of neurons as compared with traditional methods. The salient feature of the proposed method also lies in the continuity of the control action everywhere. Furthermore, the resulting control action is smooth almost everywhere except for a few time instants at which new neurons are added. Numerical example illustrates the effectiveness of the proposed approach.
Trajectory Control of Rendezvous with Maneuver Target Spacecraft
NASA Technical Reports Server (NTRS)
Zhou, Zhinqiang
2012-01-01
In this paper, a nonlinear trajectory control algorithm of rendezvous with maneuvering target spacecraft is presented. The disturbance forces on the chaser and target spacecraft and the thrust forces on the chaser spacecraft are considered in the analysis. The control algorithm developed in this paper uses the relative distance and relative velocity between the target and chaser spacecraft as the inputs. A general formula of reference relative trajectory of the chaser spacecraft to the target spacecraft is developed and applied to four different proximity maneuvers, which are in-track circling, cross-track circling, in-track spiral rendezvous and cross-track spiral rendezvous. The closed-loop differential equations of the proximity relative motion with the control algorithm are derived. It is proven in the paper that the tracking errors between the commanded relative trajectory and the actual relative trajectory are bounded within a constant region determined by the control gains. The prediction of the tracking errors is obtained. Design examples are provided to show the implementation of the control algorithm. The simulation results show that the actual relative trajectory tracks the commanded relative trajectory tightly. The predicted tracking errors match those calculated in the simulation results. The control algorithm developed in this paper can also be applied to interception of maneuver target spacecraft and relative trajectory control of spacecraft formation flying.
Cocking, Edward C; Stone, Philip J; Davey, Michael R
2005-12-01
It has been forecast that the challenge of meeting increased food demand and protecting environmental quality will be won or lost in maize, rice and wheat cropping systems, and that the problem of environmental nitrogen enrichment is most likely to be solved by substituting synthetic nitrogen fertilizers by the creation of cereal crops that are able to fix nitrogen symbiotically as legumes do. In legumes, rhizobia present intracellularly in membrane-bound vesicular compartments in the cytoplasm of nodule cells fix nitrogen endosymbiotically. Within these symbiosomes, membrane-bound vesicular compartments, rhizobia are supplied with energy derived from plant photosynthates and in return supply the plant with biologically fixed nitrogen, usually as ammonia. This minimizes or eliminates the need for inputs of synthetic nitrogen fertilizers. Recently we have demonstrated, using novel inoculation conditions with very low numbers of bacteria, that cells of root meristems of maize, rice, wheat and other major non-legume crops, such as oilseed rape and tomato, can be intracellularly colonized by the non-rhizobial, non-nodulating, nitrogen fixing bacterium, Gluconacetobacter diazotrophicus that naturally occurs in sugarcane. G. diazotrophicus expressing nitrogen fixing (nifH) genes is present in symbiosome-like compartments in the cytoplasm of cells of the root meristems of the target cereals and non-legume crop species, somewhat similar to the intracellular symbiosome colonization of legume nodule cells by rhizobia. To obtain an indication of the likelihood of adequate growth and yield, of maize for example, with reduced inputs of synthetic nitrogen fertilizers, we are currently determining the extent to which nitrogen fixation, as assessed using various methods, is correlated with the extent of systemic intracellular colonization by G. diazotrophicus, with minimal or zero inputs.
Cocking, Edward C; Stone, Philip J; Davey, Michael R
2005-09-01
It has been forecast that the challenge of meeting increased food demand and protecting environmental quality will be won or lost in maize, rice and wheat cropping systems, and that the problem of environmental nitrogen enrichment is most likely to be solved by substituting synthetic nitrogen fertilizers by the creation of cereal crops that are able to fix nitrogen symbiotically as legumes do. In legumes, rhizobia present intracellularly in membrane-bound vesicular compartments in the cytoplasm of nodule cells fix nitrogen endosymbiotically. Within these symbiosomes, membrane-bound vesicular compartments, rhizobia are supplied with energy derived from plant photosynthates and in return supply the plant with biologically fixed nitrogen, usually as ammonia. This minimizes or eliminates the need for inputs of synthetic nitrogen fertilizers. Recently we have demonstrated, using novel inoculation conditions with very low numbers of bacteria, that cells of root meristems of maize, rice, wheat and other major non-legume crops, such as oilseed rape and tomato, can be intracellularly colonized by the non-rhizobial, non-nodulating, nitrogen fixing bacterium,Gluconacetobacter diazotrophicus that naturally occurs in sugarcane.G. diazotrophicus expressing nitrogen fixing (nifH) genes is present in symbiosome-like compartments in the cytoplasm of cells of the root meristems of the target cereals and non-legume crop species, somewhat similar to the intracellular symbiosome colonization of legume nodule cells by rhizobia. To obtain an indication of the likelihood of adequate growth and yield, of maize for example, with reduced inputs of synthetic nitrogen fertilizers, we are currently determining the extent to which nitrogen fixation, as assessed using various methods, is correlated with the extent of systemic intracellular colonization byG. diazotrophicus, with minimal or zero inputs.
Mercury in coal and the impact of coal quality on mercury emissions from combustion systems
Kolker, A.; Senior, C.L.; Quick, J.C.
2006-01-01
The proportion of Hg in coal feedstock that is emitted by stack gases of utility power stations is a complex function of coal chemistry and properties, combustion conditions, and the positioning and type of air pollution control devices employed. Mercury in bituminous coal is found primarily within Fe-sulfides, whereas lower rank coal tends to have a greater proportion of organic-bound Hg. Preparation of bituminous coal to reduce S generally reduces input Hg relative to in-ground concentrations, but the amount of this reduction varies according to the fraction of Hg in sulfides and the efficiency of sulfide removal. The mode of occurrence of Hg in coal does not directly affect the speciation of Hg in the combustion flue gas. However, other constituents in the coal, notably Cl and S, and the combustion characteristics of the coal, influence the species of Hg that are formed in the flue gas and enter air pollution control devices. The formation of gaseous oxidized Hg or particulate-bound Hg occurs post-combustion; these forms of Hg can be in part captured in the air pollution control devices that exist on coal-fired boilers, without modification. For a given coal type, the capture efficiency of Hg by pollution control systems varies according to type of device and the conditions of its deployment. For bituminous coal, on average, more than 60% of Hg in flue gas is captured by fabric filter (FF) and flue-gas desulfurization (FGD) systems. Key variables affecting performance for Hg control include Cl and S content of the coal, the positioning (hot side vs. cold side) of the system, and the amount of unburned C in coal ash. Knowledge of coal quality parameters and their effect on the performance of air pollution control devices allows optimization of Hg capture co-benefit. ?? 2006 Elsevier Ltd. All rights reserved.
Matrix algorithms for solving (in)homogeneous bound state equations
Blank, M.; Krassnigg, A.
2011-01-01
In the functional approach to quantum chromodynamics, the properties of hadronic bound states are accessible via covariant integral equations, e.g. the Bethe–Salpeter equation for mesons. In particular, one has to deal with linear, homogeneous integral equations which, in sophisticated model setups, use numerical representations of the solutions of other integral equations as part of their input. Analogously, inhomogeneous equations can be constructed to obtain off-shell information in addition to bound-state masses and other properties obtained from the covariant analogue to a wave function of the bound state. These can be solved very efficiently using well-known matrix algorithms for eigenvalues (in the homogeneous case) and the solution of linear systems (in the inhomogeneous case). We demonstrate this by solving the homogeneous and inhomogeneous Bethe–Salpeter equations and find, e.g. that for the calculation of the mass spectrum it is as efficient or even advantageous to use the inhomogeneous equation as compared to the homogeneous. This is valuable insight, in particular for the study of baryons in a three-quark setup and more involved systems. PMID:21760640
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.
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.
Development of the functional simulator for the Galileo attitude and articulation control system
NASA Technical Reports Server (NTRS)
Namiri, M. K.
1983-01-01
A simulation program for verifying and checking the performance of the Galileo Spacecraft's Attitude and Articulation Control Subsystem's (AACS) flight software is discussed. The program, which is called Functional Simulator (FUNSIM), provides a simple method of interfacing user-supplied mathematical models coded in FORTRAN which describes spacecraft dynamics, sensors, and actuators; this is done with the AACS flight software, coded in HAL/S (High-level Advanced Language/Shuttle). It is thus able to simulate the AACS flight software accurately to the HAL/S statement level in the environment of a mainframe computer system. FUNSIM also has a command and data subsystem (CDS) simulator. It is noted that the input/output data and timing are simulated with the same precision as the flight microprocessor. FUNSIM uses a variable stepsize numerical integration algorithm complete with individual error bound control on the state variable to solve the equations of motion. The program has been designed to provide both line printer and matrix dot plotting of the variables requested in the run section and to provide error diagnostics.
Unraveling the CHIP:Hsp70 complex as an information processor for protein quality control.
VanPelt, Jamie; Page, Richard C
2017-02-01
The CHIP:Hsp70 complex stands at the crossroads of the cellular protein quality control system. Hsp70 facilitates active refolding of misfolded client proteins, while CHIP directs ubiquitination of misfolded client proteins bound to Hsp70. The direct competition between CHIP and Hsp70 for the fate of misfolded proteins leads to the question: how does the CHIP:Hsp70 complex execute triage decisions that direct misfolded proteins for either refolding or degradation? The current body of literature points toward action of the CHIP:Hsp70 complex as an information processor that takes inputs in the form of client folding state, dynamics, and posttranslational modifications, then outputs either refolded or ubiquitinated client proteins. Herein we examine the CHIP:Hsp70 complex beginning with the structure and function of CHIP and Hsp70, followed by an examination of recent studies of the interactions and dynamics of the CHIP:Hsp70 complex. Copyright © 2016 Elsevier B.V. All rights reserved.
Robust dynamic inversion controller design and analysis (using the X-38 vehicle as a case study)
NASA Astrophysics Data System (ADS)
Ito, Daigoro
A new way to approach robust Dynamic Inversion controller synthesis is addressed in this paper. A Linear Quadratic Gaussian outer-loop controller improves the robustness of a Dynamic Inversion inner-loop controller in the presence of uncertainties. Desired dynamics are given by the dynamic compensator, which shapes the loop. The selected dynamics are based on both performance and stability robustness requirements. These requirements are straightforwardly formulated as frequency-dependent singular value bounds during synthesis of the controller. Performance and robustness of the designed controller is tested using a worst case time domain quadratic index, which is a simple but effective way to measure robustness due to parameter variation. Using this approach, a lateral-directional controller for the X-38 vehicle is designed and its robustness to parameter variations and disturbances is analyzed. It is found that if full state measurements are available, the performance of the designed lateral-directional control system, measured by the chosen cost function, improves by approximately a factor of four. Also, it is found that the designed system is stable up to a parametric variation of 1.65 standard deviation with the set of uncertainty considered. The system robustness is determined to be highly sensitive to the dihedral derivative and the roll damping coefficients. The controller analysis is extended to the nonlinear system where both control input displacements and rates are bounded. In this case, the considered nonlinear system is stable up to 48.1° in bank angle and 1.59° in sideslip angle variations, indicating it is more sensitive to variations in sideslip angle than in bank angle. This nonlinear approach is further extended for the actuator failure mode analysis. The results suggest that the designed system maintains a high level of stability in the event of aileron failure. However, only 35% or less of the original stability range is maintained for the rudder failure case. Overall, this combination of controller synthesis and robustness criteria compares well with the mu-synthesis technique. It also is readily accessible to the practicing engineer, in terms of understanding and use.
NASA Astrophysics Data System (ADS)
Wu, Qingru; Gao, Wei; Wang, Shuxiao; Hao, Jiming
2017-09-01
Iron and steel production (ISP) is one of the significant atmospheric Hg emission sources in China. Atmospheric mercury (Hg) emissions from ISP during 2000-2015 were estimated by using a technology-based emission factor method. To support the application of this method, databases of Hg concentrations in raw materials, technology development trends, and Hg removal efficiencies of air pollution control devices (APCDs) were constructed through national sampling and literature review. Hg input to ISP increased from 21.6 t in 2000 to 94.5 t in 2015. In the various types of raw materials, coking coal and iron concentrates contributed 35-46 and 25-32 % of the total Hg input. Atmospheric Hg emissions from ISP increased from 11.5 t in 2000 to 32.7 t in 2015 with a peak of 35.6 t in 2013. Pollution control promoted the increase in average Hg removal efficiency, from 47 % in 2000 to 65 % in 2015. During the study period, sinter/pellet plants and blast furnaces were the largest two emission processes. However, emissions from roasting plants and coke ovens cannot be ignored, which accounted for 22-34 % of ISP's emissions. Overall, Hg speciation shifted from 50/44/6 (gaseous elemental Hg (Hg0)/gaseous oxidized Hg (HgII)/particulate-bound Hg (Hgp)) in 2000 to 40/59/1 in 2015, which indicated a higher proportion of Hg deposition around the emission points. Future emissions of ISP were expected to decrease based on the comprehensive consideration crude-steel production, steel scrap utilization, energy saving, and pollution control measures.
Simulation Framework for Teaching in Modeling and Simulation Areas
ERIC Educational Resources Information Center
De Giusti, Marisa Raquel; Lira, Ariel Jorge; Villarreal, Gonzalo Lujan
2008-01-01
Simulation is the process of executing a model that describes a system with enough detail; this model has its entities, an internal state, some input and output variables and a list of processes bound to these variables. Teaching a simulation language such as general purpose simulation system (GPSS) is always a challenge, because of the way it…
Robust control of seismically excited cable stayed bridges with MR dampers
NASA Astrophysics Data System (ADS)
YeganehFallah, Arash; Khajeh Ahamd Attari, Nader
2017-03-01
In recent decades active and semi-active structural control are becoming attractive alternatives for enhancing performance of civil infrastructures subjected to seismic and winds loads. However, in order to have reliable active and semi-active control, there is a need to include information of uncertainties in design of the controller. In real world for civil structures, parameters such as loading places, stiffness, mass and damping are time variant and uncertain. These uncertainties in many cases model as parametric uncertainties. The motivation of this research is to design a robust controller for attenuating the vibrational responses of civil infrastructures, regarding their dynamical uncertainties. Uncertainties in structural dynamic’s parameters are modeled as affine uncertainties in state space modeling. These uncertainties are decoupled from the system through Linear Fractional Transformation (LFT) and are assumed to be unknown input to the system but norm bounded. The robust H ∞ controller is designed for the decoupled system to regulate the evaluation outputs and it is robust to effects of uncertainties, disturbance and sensors noise. The cable stayed bridge benchmark which is equipped with MR damper is considered for the numerical simulation. The simulated results show that the proposed robust controller can effectively mitigate undesired uncertainties effects on systems’ responds under seismic loading.
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.
Thermodynamic efficiency of learning a rule in neural networks
NASA Astrophysics Data System (ADS)
Goldt, Sebastian; Seifert, Udo
2017-11-01
Biological systems have to build models from their sensory input data that allow them to efficiently process previously unseen inputs. Here, we study a neural network learning a binary classification rule for these inputs from examples provided by a teacher. We analyse the ability of the network to apply the rule to new inputs, that is to generalise from past experience. Using stochastic thermodynamics, we show that the thermodynamic costs of the learning process provide an upper bound on the amount of information that the network is able to learn from its teacher for both batch and online learning. This allows us to introduce a thermodynamic efficiency of learning. We analytically compute the dynamics and the efficiency of a noisy neural network performing online learning in the thermodynamic limit. In particular, we analyse three popular learning algorithms, namely Hebbian, Perceptron and AdaTron learning. Our work extends the methods of stochastic thermodynamics to a new type of learning problem and might form a suitable basis for investigating the thermodynamics of decision-making.
Simple modification of Oja rule limits L1-norm of weight vector and leads to sparse connectivity.
Aparin, Vladimir
2012-03-01
This letter describes a simple modification of the Oja learning rule, which asymptotically constrains the L1-norm of an input weight vector instead of the L2-norm as in the original rule. This constraining is local as opposed to commonly used instant normalizations, which require the knowledge of all input weights of a neuron to update each one of them individually. The proposed rule converges to a weight vector that is sparser (has more zero weights) than the vector learned by the original Oja rule with or without the zero bound, which could explain the developmental synaptic pruning.
Alternative to Ritt's pseudodivision for finding the input-output equations of multi-output models.
Meshkat, Nicolette; Anderson, Chris; DiStefano, Joseph J
2012-09-01
Differential algebra approaches to structural identifiability analysis of a dynamic system model in many instances heavily depend upon Ritt's pseudodivision at an early step in analysis. The pseudodivision algorithm is used to find the characteristic set, of which a subset, the input-output equations, is used for identifiability analysis. A simpler algorithm is proposed for this step, using Gröbner Bases, along with a proof of the method that includes a reduced upper bound on derivative requirements. Efficacy of the new algorithm is illustrated with several biosystem model examples. Copyright © 2012 Elsevier Inc. All rights reserved.
Veligdan, James T.
1997-01-01
An optical display includes a plurality of stacked optical waveguides having first and second opposite ends collectively defining an image input face and an image screen, respectively, with the screen being oblique to the input face. Each of the waveguides includes a transparent core bound by a cladding layer having a lower index of refraction for effecting internal reflection of image light transmitted into the input face to project an image on the screen, with each of the cladding layers including a cladding cap integrally joined thereto at the waveguide second ends. Each of the cores is beveled at the waveguide second end so that the cladding cap is viewable through the transparent core. Each of the cladding caps is black for absorbing external ambient light incident upon the screen for improving contrast of the image projected internally on the screen.
Bionic Control of Cheetah Bounding with a Segmented Spine.
Wang, Chunlei; Wang, Shigang
2016-01-01
A cheetah model is built to mimic real cheetah and its mechanical and dimensional parameters are derived from the real cheetah. In particular, two joints in spine and four joints in a leg are used to realize the motion of segmented spine and segmented legs which are the key properties of the cheetah bounding. For actuating and stabilizing the bounding gait of cheetah, we present a bioinspired controller based on the state-machine. The controller mainly mimics the function of the cerebellum to plan the locomotion and keep the body balance. The haptic sensor and proprioception system are used to detect the trigger of the phase transition. Besides, the vestibular modulation could perceive the pitching angle of the trunk. At last, the cerebellum acts as the CPU to operate the information from the biological sensors. In addition, the calculated results are transmitted to the low-level controller to actuate and stabilize the cheetah bounding. Moreover, the delay feedback control method is employed to plan the motion of the leg joints to stabilize the pitching motion of trunk with the stability criterion. Finally, the cyclic cheetah bounding with biological properties is realized. Meanwhile, the stability and dynamic properties of the cheetah bounding gait are analyzed elaborately.
Neurotoxic flying foxes as dietary items for the Chamorro people, Marianas Islands.
Banack, Sandra Anne; Murch, Susan J; Cox, Paul Alan
2006-06-15
Fanihi -- flying foxes (Pteropus mariannus mariannus, Pteropodidae) -- are a highly salient component of the traditional Chamorro diet. A neurotoxic, non-protein amino acid, beta-methylamino-l-alanine (BMAA) accumulates in flying foxes, which forage on the seeds of Cycas micronesica (Cycadaceae) in Guam's forests. BMAA occurs throughout flying fox tissues both as a free amino acid and in a protein-bound form. It is not destroyed by cooking. Protein-bound BMAA also remains in cycad flour which has been washed and prepared by the Chamorro people as tortillas, dumplings, and thickened soups. Other animals that forage on cycad seeds may also provide BMAA inputs into the traditional Chamorro diet.
SURE reliability analysis: Program and mathematics
NASA Technical Reports Server (NTRS)
Butler, Ricky W.; White, Allan L.
1988-01-01
The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The computational methods on which the program is based provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.
Spike Train Auto-Structure Impacts Post-Synaptic Firing and Timing-Based Plasticity
Scheller, Bertram; Castellano, Marta; Vicente, Raul; Pipa, Gordon
2011-01-01
Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal structure of pre-synaptic inhibitory and excitatory inputs impact the post-synaptic firing of a conductance-based integrate and fire neuron. Both the excitatory and inhibitory input was modeled by renewal gamma processes with varying shape factors for modeling regular and temporally random Poisson activity. We demonstrate that the temporal structure of mutually independent inputs affects the post-synaptic firing, while the strength of the effect depends on the firing rates of both the excitatory and inhibitory inputs. In a second step, we explore the effect of temporal structure of mutually independent inputs on a simple version of Hebbian learning, i.e., hard bound spike-timing-dependent plasticity. We explore both the equilibrium weight distribution and the speed of the transient weight dynamics for different mutually independent gamma processes. We find that both the equilibrium distribution of the synaptic weights and the speed of synaptic changes are modulated by the temporal structure of the input. Finally, we highlight that the sensitivity of both the post-synaptic firing as well as the spike-timing-dependent plasticity on the auto-structure of the input of a neuron could be used to modulate the learning rate of synaptic modification. PMID:22203800
NASA Technical Reports Server (NTRS)
Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas
2009-01-01
This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.
Cockpit automation - In need of a philosophy
NASA Technical Reports Server (NTRS)
Wiener, E. L.
1985-01-01
Concern has been expressed over the rapid development and deployment of automatic devices in transport aircraft, due mainly to the human interface and particularly the role of automation in inducing human error. The paper discusses the need for coherent philosophies of automation, and proposes several approaches: (1) flight management by exception, which states that as long as a crew stays within the bounds of regulations, air traffic control and flight safety, it may fly as it sees fit; (2) exceptions by forecasting, where the use of forecasting models would predict boundary penetration, rather than waiting for it to happen; (3) goal-sharing, where a computer is informed of overall goals, and subsequently has the capability of checking inputs and aircraft position for consistency with the overall goal or intentions; and (4) artificial intelligence and expert systems, where intelligent machines could mimic human reason.
A Data Envelopment Analysis Model for Selecting Material Handling System Designs
NASA Astrophysics Data System (ADS)
Liu, Fuh-Hwa Franklin; Kuo, Wan-Ting
The material handling system under design is an unmanned job shop with an automated guided vehicle that transport loads within the processing machines. The engineering task is to select the design alternatives that are the combinations of the four design factors: the ratio of production time to transportation time, mean job arrival rate to the system, input/output buffer capacities at each processing machine, and the vehicle control strategies. Each of the design alternatives is simulated to collect the upper and lower bounds of the five performance indices. We develop a Data Envelopment Analysis (DEA) model to assess the 180 designs with imprecise data of the five indices. The three-ways factorial experiment analysis for the assessment results indicates the buffer capacity and the interaction of job arrival rate and buffer capacity affect the performance significantly.
NASA Astrophysics Data System (ADS)
Brunetti, Matthew N.; Berman, Oleg L.; Kezerashvili, Roman Ya
2018-06-01
We study optical transitions in spatially indirect excitons in transition metal dichalcogenide (TMDC) heterostructures separated by an integer number of hexagonal boron nitride (h-BN) monolayers. By solving the Schrödinger equation with the Keldysh potential for a spatially indirect exciton, we obtain eigenfunctions and eigenenergies for the ground and excited states and study their dependence on the interlayer separation, controlled by varying the number of h-BN monolayers. The oscillator strength, optical absorption coefficient, and optical absorption factor, the fraction of incoming photons absorbed in the TMDC/h-BN/TMDC heterostructure, are evaluated and studied as a function of the interlayer separation. Using input parameters from the existing literature which give the largest and the smallest spatially indirect exciton binding energy, we provide upper and lower bounds on all quantities presented.
Flight control application of new stability robustness bounds for linear uncertain systems
NASA Technical Reports Server (NTRS)
Yedavalli, Rama K.
1993-01-01
This paper addresses the issue of obtaining bounds on the real parameter perturbations of a linear state-space model for robust stability. Based on Kronecker algebra, new, easily computable sufficient bounds are derived that are much less conservative than the existing bounds since the technique is meant for only real parameter perturbations (in contrast to specializing complex variation case to real parameter case). The proposed theory is illustrated with application to several flight control examples.
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.
Narayanan, Vignesh; Jagannathan, Sarangapani
2017-09-07
In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.
The role of endocytic pathways in cellular uptake of plasma non-transferrin iron
Sohn, Yang-Sung; Ghoti, Hussam; Breuer, William; Rachmilewitz, Eliezer; Attar, Samah; Weiss, Guenter; Cabantchik, Z. Ioav
2012-01-01
Background In transfusional siderosis, the iron binding capacity of plasma transferrin is often surpassed, with concomitant generation of non-transferrin-bound iron. Although implicated in tissue siderosis, non-transferrin-bound iron modes of cell ingress remain undefined, largely because of its variable composition and association with macromolecules. Using fluorescent tracing of labile iron in endosomal vesicles and cytosol, we examined the hypothesis that non-transferrin-bound iron fractions detected in iron overloaded patients enter cells via bulk endocytosis. Design and Methods Fluorescence microscopy and flow cytometry served as analytical tools for tracing non-transferrin-bound iron entry into endosomes with the redox-reactive macromolecular probe Oxyburst-Green and into the cytosol with cell-laden calcein green and calcein blue. Non-transferrin-bound iron-containing media were from sera of polytransfused thalassemia major patients and model iron substances detected in thalassemia major sera; cell models were cultured macrophages, and cardiac myoblasts and myocytes. Results Exposure of cells to ferric citrate together with albumin, or to non-transferrin-bound iron-containing sera from thalassemia major patients caused an increase in labile iron content of endosomes and cytosol in macrophages and cardiac cells. This increase was more striking in macrophages, but in both cell types was largely reduced by co-exposure to non-transferrin-bound iron-containing media with non-penetrating iron chelators or apo-transferrin, or by treatment with inhibitors of endocytosis. Endosomal iron accumulation traced with calcein-green was proportional to input non-transferrin-bound iron levels (r2=0.61) and also preventable by pre-chelation. Conclusions Our studies indicate that macromolecule-associated non-transferrin-bound iron can initially gain access into various cells via endocytic pathways, followed by iron translocation to the cytosol. Endocytic uptake of plasma non-transferrin-bound iron is a possible mechanism that can contribute to iron loading of cell types engaged in bulk/adsorptive endocytosis, highlighting the importance of its prevention by iron chelation. PMID:22180428
A Convex Approach to Fault Tolerant Control
NASA Technical Reports Server (NTRS)
Maghami, Peiman G.; Cox, David E.; Bauer, Frank (Technical Monitor)
2002-01-01
The design of control laws for dynamic systems with the potential for actuator failures is considered in this work. The use of Linear Matrix Inequalities allows more freedom in controller design criteria than typically available with robust control. This work proposes an extension of fault-scheduled control design techniques that can find a fixed controller with provable performance over a set of plants. Through convexity of the objective function, performance bounds on this set of plants implies performance bounds on a range of systems defined by a convex hull. This is used to incorporate performance bounds for a variety of soft and hard failures into the control design problem.
Lin, Faa-Jeng; Lee, Shih-Yang; Chou, Po-Huan
2012-12-01
The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS.
Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control
NASA Technical Reports Server (NTRS)
Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje
2009-01-01
This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.
GTP- and GDP-Dependent Rab27a Effectors in Pancreatic Beta-Cells.
Yamaoka, Mami; Ishizaki, Toshimasa; Kimura, Toshihide
2015-01-01
Small guanosine triphosphatases (GTPases) participate in a wide variety of cellular functions including proliferation, differentiation, adhesion, and intracellular transport. Conventionally, only the guanosine 5'-triphosphate (GTP)-bound small GTPase interacts with effector proteins, and the resulting downstream signals control specific cellular functions. Therefore, the GTP-bound form is regarded as active, and the focus has been on searching for proteins that bind the GTP form to look for their effectors. The Rab family small GTPase Rab27a is highly expressed in some secretory cells and is involved in the control of membrane traffic. The present study reviews recent progress in our understanding of the roles of Rab27a and its effectors in pancreatic beta-cells. In the basal state, GTP-bound Rab27a controls insulin secretion at pre-exocytic stages via its GTP-dependent effectors. We previously identified novel guanosine 5'-diphosphate (GDP)-bound Rab27-interacting proteins. Interestingly, GDP-bound Rab27a controls endocytosis of the secretory membrane via its interaction with these proteins. We also demonstrated that the insulin secretagogue glucose converts Rab27a from its GTP- to GDP-bound forms. Thus, GTP- and GDP-bound Rab27a regulate pre-exocytic and endocytic stages in membrane traffic, respectively. Since the physiological importance of GDP-bound GTPases has been largely overlooked, we consider that the investigation of GDP-dependent effectors for other GTPases is necessary for further understanding of cellular function.
Dependence of the quantum speed limit on system size and control complexity
NASA Astrophysics Data System (ADS)
Lee, Juneseo; Arenz, Christian; Rabitz, Herschel; Russell, Benjamin
2018-06-01
We extend the work in 2017 New J. Phys. 19 103015 by deriving a lower bound for the minimum time necessary to implement a unitary transformation on a generic, closed quantum system with an arbitrary number of classical control fields. This bound is explicitly analyzed for a specific N-level system similar to those used to represent simple models of an atom, or the first excitation sector of a Heisenberg spin chain, both of which are of interest in quantum control for quantum computation. Specifically, it is shown that the resultant bound depends on the dimension of the system, and on the number of controls used to implement a specific target unitary operation. The value of the bound determined numerically, and an estimate of the true minimum gate time are systematically compared for a range of system dimension and number of controls; special attention is drawn to the relationship between these two variables. It is seen that the bound captures the scaling of the minimum time well for the systems studied, and quantitatively is correct in the order of magnitude.
Position-based coding and convex splitting for private communication over quantum channels
NASA Astrophysics Data System (ADS)
Wilde, Mark M.
2017-10-01
The classical-input quantum-output (cq) wiretap channel is a communication model involving a classical sender X, a legitimate quantum receiver B, and a quantum eavesdropper E. The goal of a private communication protocol that uses such a channel is for the sender X to transmit a message in such a way that the legitimate receiver B can decode it reliably, while the eavesdropper E learns essentially nothing about which message was transmitted. The ɛ -one-shot private capacity of a cq wiretap channel is equal to the maximum number of bits that can be transmitted over the channel, such that the privacy error is no larger than ɛ \\in (0,1). The present paper provides a lower bound on the ɛ -one-shot private classical capacity, by exploiting the recently developed techniques of Anshu, Devabathini, Jain, and Warsi, called position-based coding and convex splitting. The lower bound is equal to a difference of the hypothesis testing mutual information between X and B and the "alternate" smooth max-information between X and E. The one-shot lower bound then leads to a non-trivial lower bound on the second-order coding rate for private classical communication over a memoryless cq wiretap channel.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Guha, Saikat; Shapiro, Jeffrey H.; Erkmen, Baris I.
Previous work on the classical information capacities of bosonic channels has established the capacity of the single-user pure-loss channel, bounded the capacity of the single-user thermal-noise channel, and bounded the capacity region of the multiple-access channel. The latter is a multiple-user scenario in which several transmitters seek to simultaneously and independently communicate to a single receiver. We study the capacity region of the bosonic broadcast channel, in which a single transmitter seeks to simultaneously and independently communicate to two different receivers. It is known that the tightest available lower bound on the capacity of the single-user thermal-noise channel is thatmore » channel's capacity if, as conjectured, the minimum von Neumann entropy at the output of a bosonic channel with additive thermal noise occurs for coherent-state inputs. Evidence in support of this minimum output entropy conjecture has been accumulated, but a rigorous proof has not been obtained. We propose a minimum output entropy conjecture that, if proved to be correct, will establish that the capacity region of the bosonic broadcast channel equals the inner bound achieved using a coherent-state encoding and optimum detection. We provide some evidence that supports this conjecture, but again a full proof is not available.« less
Hydraulic actuator mechanism to control aircraft spoiler movements through dual input commands
NASA Technical Reports Server (NTRS)
Irick, S. C. (Inventor)
1981-01-01
An aircraft flight spoiler control mechanism is described. The invention enables the conventional, primary spoiler control system to retain its operational characteristics while accommodating a secondary input controlled by a conventional computer system to supplement the settings made by the primary input. This is achieved by interposing springs between the primary input and the spoiler control unit. The springs are selected to have a stiffness intermediate to the greater force applied by the primary control linkage and the lesser resistance offered by the spoiler control unit. Thus, operation of the primary input causes the control unit to yield before the springs, yet, operation of the secondary input, acting directly on the control unit, causes the springs to yield and absorb adjustments before they are transmitted into the primary control system.
Neural field model of memory-guided search.
Kilpatrick, Zachary P; Poll, Daniel B
2017-12-01
Many organisms can remember locations they have previously visited during a search. Visual search experiments have shown exploration is guided away from these locations, reducing redundancies in the search path before finding a hidden target. We develop and analyze a two-layer neural field model that encodes positional information during a search task. A position-encoding layer sustains a bump attractor corresponding to the searching agent's current location, and search is modeled by velocity input that propagates the bump. A memory layer sustains persistent activity bounded by a wave front, whose edges expand in response to excitatory input from the position layer. Search can then be biased in response to remembered locations, influencing velocity inputs to the position layer. Asymptotic techniques are used to reduce the dynamics of our model to a low-dimensional system of equations that track the bump position and front boundary. Performance is compared for different target-finding tasks.
21st Century Rise in Anthropogenic Nitrogen Deposition on a Remote Coral Reef
NASA Astrophysics Data System (ADS)
Ren, H. A.; Chen, Y. C.; Wang, X. T.; Wong, G. T. F.; Cohen, A. L.; DeCarlo, T. M.; Weigand, M. A.; Mii, H. S.; Sigman, D. M.
2017-12-01
With the rapid rise in pollution-associated nitrogen inputs to the western Pacific, it has been suggested that even the open ocean has been impacted through atmospheric deposition. In a coral core from Dongsha Atoll, a coral reef ecosystem 340 km from the nearest continent, we observe a decline in the 15N/14N of coral skeleton-bound organic matter, signaling increased deposition of anthropogenic atmospheric N on the open ocean and its incorporation into plankton and in turn the corals living on the atoll. The decrease began just several years before 2000 CE, decades later than predicted by other work, and the amplitude of decline suggests that anthropogenic atmospheric N input is now 20±5% of the annual N input to the surface ocean in this region, less than two-thirds of that estimated by models and analyses of nutrient ratio changes.
Neural field model of memory-guided search
NASA Astrophysics Data System (ADS)
Kilpatrick, Zachary P.; Poll, Daniel B.
2017-12-01
Many organisms can remember locations they have previously visited during a search. Visual search experiments have shown exploration is guided away from these locations, reducing redundancies in the search path before finding a hidden target. We develop and analyze a two-layer neural field model that encodes positional information during a search task. A position-encoding layer sustains a bump attractor corresponding to the searching agent's current location, and search is modeled by velocity input that propagates the bump. A memory layer sustains persistent activity bounded by a wave front, whose edges expand in response to excitatory input from the position layer. Search can then be biased in response to remembered locations, influencing velocity inputs to the position layer. Asymptotic techniques are used to reduce the dynamics of our model to a low-dimensional system of equations that track the bump position and front boundary. Performance is compared for different target-finding tasks.
Stochastic analysis of three-dimensional flow in a bounded domain
Naff, R.L.; Vecchia, A.V.
1986-01-01
A commonly accepted first-order approximation of the equation for steady state flow in a fully saturated spatially random medium has the form of Poisson's equation. This form allows for the advantageous use of Green's functions to solve for the random output (hydraulic heads) in terms of a convolution over the random input (the logarithm of hydraulic conductivity). A solution for steady state three- dimensional flow in an aquifer bounded above and below is presented; consideration of these boundaries is made possible by use of Green's functions to solve Poisson's equation. Within the bounded domain the medium hydraulic conductivity is assumed to be a second-order stationary random process as represented by a simple three-dimensional covariance function. Upper and lower boundaries are taken to be no-flow boundaries; the mean flow vector lies entirely in the horizontal dimensions. The resulting hydraulic head covariance function exhibits nonstationary effects resulting from the imposition of boundary conditions. Comparisons are made with existing infinite domain solutions.
Bounded state variables and the calculus of variations
NASA Technical Reports Server (NTRS)
Hanafy, L. M.
1972-01-01
An optimal control problem with bounded state variables is transformed into a Lagrange problem by means of differentiable mappings which take some Euclidean space onto the control and state regions. Whereas all such mappings lead to a Lagrange problem, it is shown that only those which are defined as acceptable pairs of transformations are suitable in the sense that solutions to the transformed Lagrange problem will lead to solutions to the original bounded state problem and vice versa. In particular, an acceptable pair of transformations is exhibited for the case when the control and state regions are right parallelepipeds. Finally, a description of the necessary conditions for the bounded state problem which were obtained by this method is given.
Estimates of Storage Capacity of Multilayer Perceptron with Threshold Logic Hidden Units.
Kowalczyk, Adam
1997-11-01
We estimate the storage capacity of multilayer perceptron with n inputs, h(1) threshold logic units in the first hidden layer and 1 output. We show that if the network can memorize 50% of all dichotomies of a randomly selected N-tuple of points of R(n) with probability 1, then N=2(nh(1)+1), while at 100% memorization N=nh(1)+1. Furthermore, if the bounds are reached, then the first hidden layer must be fully connected to the input. It is shown that such a network has memory capacity (in the sense of Cover) between nh(1)+1 and 2(nh(1)+1) input patterns and for the most efficient networks in this class between 1 and 2 input patterns per connection. Comparing these results with the recent estimates of VC-dimension we find that in contrast to a single neuron case, the VC-dimension exceeds the capacity for a sufficiently large n and h(1). The results are based on the derivation of an explicit expression for the number of dichotomies which can be implemented by such a network for a special class of N-tuples of input patterns which has a positive probability of being randomly chosen.
Liu, Derong; Li, Hongliang; Wang, Ding
2015-06-01
In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.
Stabilization of a three-dimensional limit cycle walking model through step-to-step ankle control.
Kim, Myunghee; Collins, Steven H
2013-06-01
Unilateral, below-knee amputation is associated with an increased risk of falls, which may be partially related to a loss of active ankle control. If ankle control can contribute significantly to maintaining balance, even in the presence of active foot placement, this might provide an opportunity to improve balance using robotic ankle-foot prostheses. We investigated ankle- and hip-based walking stabilization methods in a three-dimensional model of human gait that included ankle plantarflexion, ankle inversion-eversion, hip flexion-extension, and hip ad/abduction. We generated discrete feedback control laws (linear quadratic regulators) that altered nominal actuation parameters once per step. We used ankle push-off, lateral ankle stiffness and damping, fore-aft foot placement, lateral foot placement, or all of these as control inputs. We modeled environmental disturbances as random, bounded, unexpected changes in floor height, and defined balance performance as the maximum allowable disturbance value for which the model walked 500 steps without falling. Nominal walking motions were unstable, but were stabilized by all of the step-to-step control laws we tested. Surprisingly, step-by-step modulation of ankle push-off alone led to better balance performance (3.2% leg length) than lateral foot placement (1.2% leg length) for these control laws. These results suggest that appropriate control of robotic ankle-foot prosthesis push-off could make balancing during walking easier for individuals with amputation.
Application of Contraction Mappings to the Control of Nonlinear Systems. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Killingsworth, W. R., Jr.
1972-01-01
The theoretical and applied aspects of successive approximation techniques are considered for the determination of controls for nonlinear dynamical systems. Particular emphasis is placed upon the methods of contraction mappings and modified contraction mappings. It is shown that application of the Pontryagin principle to the optimal nonlinear regulator problem results in necessary conditions for optimality in the form of a two point boundary value problem (TPBVP). The TPBVP is represented by an operator equation and functional analytic results on the iterative solution of operator equations are applied. The general convergence theorems are translated and applied to those operators arising from the optimal regulation of nonlinear systems. It is shown that simply structured matrices and similarity transformations may be used to facilitate the calculation of the matrix Green functions and the evaluation of the convergence criteria. A controllability theory based on the integral representation of TPBVP's, the implicit function theorem, and contraction mappings is developed for nonlinear dynamical systems. Contraction mappings are theoretically and practically applied to a nonlinear control problem with bounded input control and the Lipschitz norm is used to prove convergence for the nondifferentiable operator. A dynamic model representing community drug usage is developed and the contraction mappings method is used to study the optimal regulation of the nonlinear system.
Robust adaptive control for a hybrid solid oxide fuel cell system
NASA Astrophysics Data System (ADS)
Snyder, Steven
2011-12-01
Solid oxide fuel cells (SOFCs) are electrochemical energy conversion devices. They offer a number of advantages beyond those of most other fuel cells due to their high operating temperature (800-1000°C), such as internal reforming, heat as a byproduct, and faster reaction kinetics without precious metal catalysts. Mitigating fuel starvation and improving load-following capabilities of SOFC systems are conflicting control objectives. However, this can be resolved by the hybridization of the system with an energy storage device, such as an ultra-capacitor. In this thesis, a steady-state property of the SOFC is combined with an input-shaping method in order to address the issue of fuel starvation. Simultaneously, an overall adaptive system control strategy is employed to manage the energy sharing between the elements as well as to maintain the state-of-charge of the energy storage device. The adaptive control method is robust to errors in the fuel cell's fuel supply system and guarantees that the fuel cell current and ultra-capacitor state-of-charge approach their target values and remain uniformly, ultimately bounded about these target values. Parameter saturation is employed to guarantee boundedness of the parameters. The controller is validated through hardware-in-the-loop experiments as well as computer simulations.
The SURE reliability analysis program
NASA Technical Reports Server (NTRS)
Butler, R. W.
1986-01-01
The SURE program is a new reliability tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.
The SURE Reliability Analysis Program
NASA Technical Reports Server (NTRS)
Butler, R. W.
1986-01-01
The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.
Benzi, Roberto; De Angelis, Elisabetta; L'vov, Victor S; Procaccia, Itamar
2005-11-04
Drag reduction by polymers in wall turbulence is bounded from above by a universal maximal drag reduction (MDR) velocity profile that is a log law, estimated experimentally by Virk as V+(y+) approximately 11.7logy+ - 17. Here V+(y+) and y+ are the mean streamwise velocity and the distance from the wall in "wall" units. In this Letter we propose that this MDR profile is an edge solution of the Navier-Stokes equations (with an effective viscosity profile) beyond which no turbulent solutions exist. This insight rationalizes the universality of the MDR and provides a maximum principle which allows an ab initio calculation of the parameters in this law without any viscoelastic experimental input.
A simple method to derive bounds on the size and to train multilayer neural networks
NASA Technical Reports Server (NTRS)
Sartori, Michael A.; Antsaklis, Panos J.
1991-01-01
A new derivation is presented for the bounds on the size of a multilayer neural network to exactly implement an arbitrary training set; namely, the training set can be implemented with zero error with two layers and with the number of the hidden-layer neurons equal to no.1 is greater than p - 1. The derivation does not require the separation of the input space by particular hyperplanes, as in previous derivations. The weights for the hidden layer can be chosen almost arbitrarily, and the weights for the output layer can be found by solving no.1 + 1 linear equations. The method presented exactly solves (M), the multilayer neural network training problem, for any arbitrary training set.
Contagious error sources would need time travel to prevent quantum computation
NASA Astrophysics Data System (ADS)
Kalai, Gil; Kuperberg, Greg
2015-08-01
We consider an error model for quantum computing that consists of "contagious quantum germs" that can infect every output qubit when at least one input qubit is infected. Once a germ actively causes error, it continues to cause error indefinitely for every qubit it infects, with arbitrary quantum entanglement and correlation. Although this error model looks much worse than quasi-independent error, we show that it reduces to quasi-independent error with the technique of quantum teleportation. The construction, which was previously described by Knill, is that every quantum circuit can be converted to a mixed circuit with bounded quantum depth. We also consider the restriction of bounded quantum depth from the point of view of quantum complexity classes.
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.
NASA Astrophysics Data System (ADS)
Mikeš, Daniel
2010-05-01
Theoretical geology Present day geology is mostly empirical of nature. I claim that geology is by nature complex and that the empirical approach is bound to fail. Let's consider the input to be the set of ambient conditions and the output to be the sedimentary rock record. I claim that the output can only be deduced from the input if the relation from input to output be known. The fundamental question is therefore the following: Can one predict the output from the input or can one predict the behaviour of a sedimentary system? If one can, than the empirical/deductive method has changes, if one can't than that method is bound to fail. The fundamental problem to solve is therefore the following: How to predict the behaviour of a sedimentary system? It is interesting to observe that this question is never asked and many a study is conducted by the empirical/deductive method; it seems that the empirical method has been accepted as being appropriate without question. It is, however, easy to argument that a sedimentary system is by nature complex and that several input parameters vary at the same time and that they can create similar output in the rock record. It follows trivially from these first principles that in such a case the deductive solution cannot be unique. At the same time several geological methods depart precisely from the assumption, that one particular variable is the dictator/driver and that the others are constant, even though the data do not support such an assumption. The method of "sequence stratigraphy" is a typical example of such a dogma. It can be easily argued that all the interpretation resulting from a method that is built on uncertain or wrong assumptions is erroneous. Still, this method has survived for many years, nonwithstanding all the critics it has received. This is just one example of the present day geological world and is not unique. Even the alternative methods criticising sequence stratigraphy actually depart from the same erroneous assumptions and do not solve the very fundamental issue that lies at the base of the problem. This problem is straighforward and obvious: a sedimentary system is inherently four-dimensional (3 spatial dimensions + 1 temporal dimension). Any method using an inferior number or dimensions is bound to fail to describe the evolution of a sedimentary system. It is indicative of the present day geological world that such fundamental issues be overlooked. The only reason for which one can appoint the socalled "rationality" in todays society. Simple "common sense" leads us to the conclusion that in this case the empirical method is bound to fail and the only method that can solve the problem is the theoretical approach. Reasoning that is completely trivial for the traditional exact sciences like physics and mathematics and applied sciences like engineering. However, not for geology, a science that was traditionally descriptive and jumped to empirical science, skipping the stage of theoretical science. I argue that the gap of theoretical geology is left open and needs to be filled. Every discipline in geology lacks a theoretical base. This base can only be filled by the theoretical/inductive approach and can impossibly be filled by the empirical/deductive approach. Once a critical mass of geologists realises this flaw in todays geology, we can start solving the fundamental problems in geology.
Four-dimensional guidance algorithms for aircraft in an air traffic control environment
NASA Technical Reports Server (NTRS)
Pecsvaradi, T.
1975-01-01
Theoretical development and computer implementation of three guidance algorithms are presented. From a small set of input parameters the algorithms generate the ground track, altitude profile, and speed profile required to implement an experimental 4-D guidance system. Given a sequence of waypoints that define a nominal flight path, the first algorithm generates a realistic, flyable ground track consisting of a sequence of straight line segments and circular arcs. Each circular turn is constrained by the minimum turning radius of the aircraft. The ground track and the specified waypoint altitudes are used as inputs to the second algorithm which generates the altitude profile. The altitude profile consists of piecewise constant flight path angle segments, each segment lying within specified upper and lower bounds. The third algorithm generates a feasible speed profile subject to constraints on the rate of change in speed, permissible speed ranges, and effects of wind. Flight path parameters are then combined into a chronological sequence to form the 4-D guidance vectors. These vectors can be used to drive the autopilot/autothrottle of the aircraft so that a 4-D flight path could be tracked completely automatically; or these vectors may be used to drive the flight director and other cockpit displays, thereby enabling the pilot to track a 4-D flight path manually.
Sainz de Murieta, Iñaki; Rodríguez-Patón, Alfonso
2012-08-01
Despite the many designs of devices operating with the DNA strand displacement, surprisingly none is explicitly devoted to the implementation of logical deductions. The present article introduces a new model of biosensor device that uses nucleic acid strands to encode simple rules such as "IF DNA_strand(1) is present THEN disease(A)" or "IF DNA_strand(1) AND DNA_strand(2) are present THEN disease(B)". Taking advantage of the strand displacement operation, our model makes these simple rules interact with input signals (either DNA or any type of RNA) to generate an output signal (in the form of nucleotide strands). This output signal represents a diagnosis, which either can be measured using FRET techniques, cascaded as the input of another logical deduction with different rules, or even be a drug that is administered in response to a set of symptoms. The encoding introduces an implicit error cancellation mechanism, which increases the system scalability enabling longer inference cascades with a bounded and controllable signal-noise relation. It also allows the same rule to be used in forward inference or backward inference, providing the option of validly outputting negated propositions (e.g. "diagnosis A excluded"). The models presented in this paper can be used to implement smart logical DNA devices that perform genetic diagnosis in vitro. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
ERIC Educational Resources Information Center
Creed, Peter A.; Patton, Wendy; Hood, Michelle
2010-01-01
We surveyed 506 Australian high school students on career development (exploration, planning, job-knowledge, decision-making, indecision), personal functioning (well-being, self-esteem, life satisfaction, school satisfaction) and control variables (parent education, school achievement), and tested differences among work-bound, college-bound and…
Control and optimization system
Xinsheng, Lou
2013-02-12
A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Fano Bounds for Compact Antennas. Phase I
2007-10-01
Transimpedance Amplifiers IEEE Journal of Solid-State Circuits, 39(8), pages 1263–1270. [3] Baher, H. [1984] Synthesis of Electrical Networks, John Wiley...band PHEMTMMIC Low Noise Amplifier with Minimum Input Match- ing Network, Electronics Letters, 36, pages 1627–1629. [7] Edminister, Joseph A. [1965...pages 1328–1331. [11] Gonzalez, Guillermo [1997] Microwave Transistor Amplifiers , Second Edition, Prentice Hall, Upper Saddle River, NJ. 68 [12
Identification of observer/Kalman filter Markov parameters: Theory and experiments
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh; Horta, Lucas G.; Longman, Richard W.
1991-01-01
An algorithm to compute Markov parameters of an observer or Kalman filter from experimental input and output data is discussed. The Markov parameters can then be used for identification of a state space representation, with associated Kalman gain or observer gain, for the purpose of controller design. The algorithm is a non-recursive matrix version of two recursive algorithms developed in previous works for different purposes. The relationship between these other algorithms is developed. The new matrix formulation here gives insight into the existence and uniqueness of solutions of certain equations and gives bounds on the proper choice of observer order. It is shown that if one uses data containing noise, and seeks the fastest possible deterministic observer, the deadbeat observer, one instead obtains the Kalman filter, which is the fastest possible observer in the stochastic environment. Results are demonstrated in numerical studies and in experiments on an ten-bay truss structure.
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.
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.
A dimension-wise analysis method for the structural-acoustic system with interval parameters
NASA Astrophysics Data System (ADS)
Xu, Menghui; Du, Jianke; Wang, Chong; Li, Yunlong
2017-04-01
The interval structural-acoustic analysis is mainly accomplished by interval and subinterval perturbation methods. Potential limitations for these intrusive methods include overestimation or interval translation effect for the former and prohibitive computational cost for the latter. In this paper, a dimension-wise analysis method is thus proposed to overcome these potential limitations. In this method, a sectional curve of the system response surface along each input dimensionality is firstly extracted, the minimal and maximal points of which are identified based on its Legendre polynomial approximation. And two input vectors, i.e. the minimal and maximal input vectors, are dimension-wisely assembled by the minimal and maximal points of all sectional curves. Finally, the lower and upper bounds of system response are computed by deterministic finite element analysis at the two input vectors. Two numerical examples are studied to demonstrate the effectiveness of the proposed method and show that, compared to the interval and subinterval perturbation method, a better accuracy is achieved without much compromise on efficiency by the proposed method, especially for nonlinear problems with large interval parameters.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-09-04
... Upward Bound Math Science Annual Performance Report AGENCY: Office of Postsecondary Education (OPE... Upward Bound Math Science Annual Performance Report. OMB Control Number: 1840-NEW. Type of Review: New... Upward Bound (UB) and Upward Bound Math and Science (UBMS) Programs. The Department is requesting a new...
AIRCRAFT REACTOR CONTROL SYSTEM APPLICABLE TO TURBOJET AND TURBOPROP POWER PLANTS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gorker, G.E.
1955-07-19
Control systems proposed for direct cycle nuclear powered aircraft commonly involve control of engine speed, nuclear energy input, and chcmical energy input. A system in which these parameters are controlled by controlling the total energy input, the ratio of nuclear and chemical energy input, and the engine speed is proposed. The system is equally applicable to turbojet or turboprop applications. (auth)
Systems and methods for compensating for electrical converter nonlinearities
Perisic, Milun; Ransom, Ray M.; Kajouke, Lateef A.
2013-06-18
Systems and methods are provided for delivering energy from an input interface to an output interface. An electrical system includes an input interface, an output interface, an energy conversion module coupled between the input interface and the output interface, and a control module. The control module determines a duty cycle control value for operating the energy conversion module to produce a desired voltage at the output interface. The control module determines an input power error at the input interface and adjusts the duty cycle control value in a manner that is influenced by the input power error, resulting in a compensated duty cycle control value. The control module operates switching elements of the energy conversion module to deliver energy to the output interface with a duty cycle that is influenced by the compensated duty cycle control value.
Fuzzy logic control and optimization system
Lou, Xinsheng [West Hartford, CT
2012-04-17
A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
High-frequency matrix converter with square wave input
Carr, Joseph Alexander; Balda, Juan Carlos
2015-03-31
A device for producing an alternating current output voltage from a high-frequency, square-wave input voltage comprising, high-frequency, square-wave input a matrix converter and a control system. The matrix converter comprises a plurality of electrical switches. The high-frequency input and the matrix converter are electrically connected to each other. The control system is connected to each switch of the matrix converter. The control system is electrically connected to the input of the matrix converter. The control system is configured to operate each electrical switch of the matrix converter converting a high-frequency, square-wave input voltage across the first input port of the matrix converter and the second input port of the matrix converter to an alternating current output voltage at the output of the matrix converter.
Energy-constrained two-way assisted private and quantum capacities of quantum channels
NASA Astrophysics Data System (ADS)
Davis, Noah; Shirokov, Maksim E.; Wilde, Mark M.
2018-06-01
With the rapid growth of quantum technologies, knowing the fundamental characteristics of quantum systems and protocols is essential for their effective implementation. A particular communication setting that has received increased focus is related to quantum key distribution and distributed quantum computation. In this setting, a quantum channel connects a sender to a receiver, and their goal is to distill either a secret key or entanglement, along with the help of arbitrary local operations and classical communication (LOCC). In this work, we establish a general theory of energy-constrained, LOCC-assisted private and quantum capacities of quantum channels, which are the maximum rates at which an LOCC-assisted quantum channel can reliably establish a secret key or entanglement, respectively, subject to an energy constraint on the channel input states. We prove that the energy-constrained squashed entanglement of a channel is an upper bound on these capacities. We also explicitly prove that a thermal state maximizes a relaxation of the squashed entanglement of all phase-insensitive, single-mode input bosonic Gaussian channels, generalizing results from prior work. After doing so, we prove that a variation of the method introduced by Goodenough et al. [New J. Phys. 18, 063005 (2016), 10.1088/1367-2630/18/6/063005] leads to improved upper bounds on the energy-constrained secret-key-agreement capacity of a bosonic thermal channel. We then consider a multipartite setting and prove that two known multipartite generalizations of the squashed entanglement are in fact equal. We finally show that the energy-constrained, multipartite squashed entanglement plays a role in bounding the energy-constrained LOCC-assisted private and quantum capacity regions of quantum broadcast channels.
Strong and uniform convergence in the teleportation simulation of bosonic Gaussian channels
NASA Astrophysics Data System (ADS)
Wilde, Mark M.
2018-06-01
In the literature on the continuous-variable bosonic teleportation protocol due to Braunstein and Kimble [Phys. Rev. Lett. 80, 869 (1998), 10.1103/PhysRevLett.80.869], it is often loosely stated that this protocol converges to a perfect teleportation of an input state in the limit of ideal squeezing and ideal detection, but the exact form of this convergence is typically not clarified. In this paper, I explicitly clarify that the convergence is in the strong sense, and not the uniform sense, and furthermore that the convergence occurs for any input state to the protocol, including the infinite-energy Basel states defined and discussed here. I also prove, in contrast to the above result, that the teleportation simulations of pure-loss, thermal, pure-amplifier, amplifier, and additive-noise channels converge both strongly and uniformly to the original channels, in the limit of ideal squeezing and detection for the simulations. For these channels, I give explicit uniform bounds on the accuracy of their teleportation simulations. I then extend these uniform convergence results to particular multimode bosonic Gaussian channels. These convergence statements have important implications for mathematical proofs that make use of the teleportation simulation of bosonic Gaussian channels, some of which have to do with bounding their nonasymptotic secret-key-agreement capacities. As a by-product of the discussion given here, I confirm the correctness of the proof of such bounds from my joint work with Berta and Tomamichel from [Wilde, Tomamichel, and Berta, IEEE Trans. Inf. Theory 63, 1792 (2017), 10.1109/TIT.2017.2648825]. Furthermore, I show that it is not necessary to invoke the energy-constrained diamond distance in order to confirm the correctness of this proof.
Mapping Computation with No Memory
NASA Astrophysics Data System (ADS)
Burckel, Serge; Gioan, Emeric; Thomé, Emmanuel
We investigate the computation of mappings from a set S n to itself with in situ programs, that is using no extra variables than the input, and performing modifications of one component at a time. We consider several types of mappings and obtain effective computation and decomposition methods, together with upper bounds on the program length (number of assignments). Our technique is combinatorial and algebraic (graph coloration, partition ordering, modular arithmetics).
Memory Reconsolidation and Computational Learning
2010-03-01
Cooper and H.T. Siegelmann, "Memory Reconsolidation for Natural Language Processing," Cognitive Neurodynamics , 3, 2009: 365-372. M.M. Olsen, N...computerized memories and other state of the art cognitive architectures, our memory system has the ability to process on-line and in real-time as...on both continuous and binary inputs, unlike state of the art methods in case based reasoning and in cognitive architectures, which are bound to
NASA Astrophysics Data System (ADS)
Touhidul Mustafa, Syed Md.; Nossent, Jiri; Ghysels, Gert; Huysmans, Marijke
2017-04-01
Transient numerical groundwater flow models have been used to understand and forecast groundwater flow systems under anthropogenic and climatic effects, but the reliability of the predictions is strongly influenced by different sources of uncertainty. Hence, researchers in hydrological sciences are developing and applying methods for uncertainty quantification. Nevertheless, spatially distributed flow models pose significant challenges for parameter and spatially distributed input estimation and uncertainty quantification. In this study, we present a general and flexible approach for input and parameter estimation and uncertainty analysis of groundwater models. The proposed approach combines a fully distributed groundwater flow model (MODFLOW) with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. To avoid over-parameterization, the uncertainty of the spatially distributed model input has been represented by multipliers. The posterior distributions of these multipliers and the regular model parameters were estimated using DREAM. The proposed methodology has been applied in an overexploited aquifer in Bangladesh where groundwater pumping and recharge data are highly uncertain. The results confirm that input uncertainty does have a considerable effect on the model predictions and parameter distributions. Additionally, our approach also provides a new way to optimize the spatially distributed recharge and pumping data along with the parameter values under uncertain input conditions. It can be concluded from our approach that considering model input uncertainty along with parameter uncertainty is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.
Analysis and Simple Circuit Design of Double Differential EMG Active Electrode.
Guerrero, Federico Nicolás; Spinelli, Enrique Mario; Haberman, Marcelo Alejandro
2016-06-01
In this paper we present an analysis of the voltage amplifier needed for double differential (DD) sEMG measurements and a novel, very simple circuit for implementing DD active electrodes. The three-input amplifier that standalone DD active electrodes require is inherently different from a differential amplifier, and general knowledge about its design is scarce in the literature. First, the figures of merit of the amplifier are defined through a decomposition of its input signal into three orthogonal modes. This analysis reveals a mode containing EMG crosstalk components that the DD electrode should reject. Then, the effect of finite input impedance is analyzed. Because there are three terminals, minimum bounds for interference rejection ratios due to electrode and input impedance unbalances with two degrees of freedom are obtained. Finally, a novel circuit design is presented, including only a quadruple operational amplifier and a few passive components. This design is nearly as simple as the branched electrode and much simpler than the three instrumentation amplifier design, while providing robust EMG crosstalk rejection and better input impedance using unity gain buffers for each electrode input. The interference rejection limits of this input stage are analyzed. An easily replicable implementation of the proposed circuit is described, together with a parameter design guideline to adjust it to specific needs. The electrode is compared with the established alternatives, and sample sEMG signals are obtained, acquired on different body locations with dry contacts, successfully rejecting interference sources.
Human middle-ear model with compound eardrum and airway branching in mastoid air cells
Keefe, Douglas H.
2015-01-01
An acoustical/mechanical model of normal adult human middle-ear function is described for forward and reverse transmission. The eardrum model included one component bound along the manubrium and another bound by the tympanic cleft. Eardrum components were coupled by a time-delayed impedance. The acoustics of the middle-ear cleft was represented by an acoustical transmission-line model for the tympanic cavity, aditus, antrum, and mastoid air cell system with variable amounts of excess viscothermal loss. Model parameters were fitted to published measurements of energy reflectance (0.25–13 kHz), equivalent input impedance at the eardrum (0.25–11 kHz), temporal-bone pressure in scala vestibuli and scala tympani (0.1–11 kHz), and reverse middle-ear impedance (0.25–8 kHz). Inner-ear fluid motion included cochlear and physiological third-window pathways. The two-component eardrum with time delay helped fit intracochlear pressure responses. A multi-modal representation of the eardrum and high-frequency modeling of the middle-ear cleft helped fit ear-canal responses. Input reactance at the eardrum was small at high frequencies due to multiple modal resonances. The model predicted the middle-ear efficiency between ear canal and cochlea, and the cochlear pressures at threshold. PMID:25994701
Human middle-ear model with compound eardrum and airway branching in mastoid air cells.
Keefe, Douglas H
2015-05-01
An acoustical/mechanical model of normal adult human middle-ear function is described for forward and reverse transmission. The eardrum model included one component bound along the manubrium and another bound by the tympanic cleft. Eardrum components were coupled by a time-delayed impedance. The acoustics of the middle-ear cleft was represented by an acoustical transmission-line model for the tympanic cavity, aditus, antrum, and mastoid air cell system with variable amounts of excess viscothermal loss. Model parameters were fitted to published measurements of energy reflectance (0.25-13 kHz), equivalent input impedance at the eardrum (0.25-11 kHz), temporal-bone pressure in scala vestibuli and scala tympani (0.1-11 kHz), and reverse middle-ear impedance (0.25-8 kHz). Inner-ear fluid motion included cochlear and physiological third-window pathways. The two-component eardrum with time delay helped fit intracochlear pressure responses. A multi-modal representation of the eardrum and high-frequency modeling of the middle-ear cleft helped fit ear-canal responses. Input reactance at the eardrum was small at high frequencies due to multiple modal resonances. The model predicted the middle-ear efficiency between ear canal and cochlea, and the cochlear pressures at threshold.
Morgenstern, Hai; Rafaely, Boaz; Noisternig, Markus
2017-03-01
Spherical microphone arrays (SMAs) and spherical loudspeaker arrays (SLAs) facilitate the study of room acoustics due to the three-dimensional analysis they provide. More recently, systems that combine both arrays, referred to as multiple-input multiple-output (MIMO) systems, have been proposed due to the added spatial diversity they facilitate. The literature provides frameworks for designing SMAs and SLAs separately, including error analysis from which the operating frequency range (OFR) of an array is defined. However, such a framework does not exist for the joint design of a SMA and a SLA that comprise a MIMO system. This paper develops a design framework for MIMO systems based on a model that addresses errors and highlights the importance of a matched design. Expanding on a free-field assumption, errors are incorporated separately for each array and error bounds are defined, facilitating error analysis for the system. The dependency of the error bounds on the SLA and SMA parameters is studied and it is recommended that parameters should be chosen to assure matched OFRs of the arrays in MIMO system design. A design example is provided, demonstrating the superiority of a matched system over an unmatched system in the synthesis of directional room impulse responses.
NASA Astrophysics Data System (ADS)
Koo, Min-Sung; Choi, Ho-Lim
2018-01-01
In this paper, we consider a control problem for a class of uncertain nonlinear systems in which there exists an unknown time-varying delay in the input and lower triangular nonlinearities. Usually, in the existing results, input delays have been coupled with feedforward (or upper triangular) nonlinearities; in other words, the combination of lower triangular nonlinearities and input delay has been rare. Motivated by the existing controller for input-delayed chain of integrators with nonlinearity, we show that the control of input-delayed nonlinear systems with two particular types of lower triangular nonlinearities can be done. As a control solution, we propose a newly designed feedback controller whose main features are its dynamic gain and non-predictor approach. Three examples are given for illustration.
Probing New Long-Range Interactions by Isotope Shift Spectroscopy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berengut, Julian C.; Budker, Dmitry; Delaunay, Cédric
We explore a method to probe new long- and intermediate-range interactions using precision atomic isotope shift spectroscopy. We develop a formalism to interpret linear King plots as bounds on new physics with minimal theory inputs. We focus only on bounding the new physics contributions that can be calculated independently of the standard model nuclear effects. We apply our method to existing Ca + data and project its sensitivity to conjectured new bosons with spin-independent couplings to the electron and the neutron using narrow transitions in other atoms and ions, specifically, Sr and Yb. Future measurements are expected to improve themore » relative precision by 5 orders of magnitude, and they can potentially lead to an unprecedented sensitivity for bosons within the 0.3 to 10 MeV mass range.« less
Probing New Long-Range Interactions by Isotope Shift Spectroscopy.
Berengut, Julian C; Budker, Dmitry; Delaunay, Cédric; Flambaum, Victor V; Frugiuele, Claudia; Fuchs, Elina; Grojean, Christophe; Harnik, Roni; Ozeri, Roee; Perez, Gilad; Soreq, Yotam
2018-03-02
We explore a method to probe new long- and intermediate-range interactions using precision atomic isotope shift spectroscopy. We develop a formalism to interpret linear King plots as bounds on new physics with minimal theory inputs. We focus only on bounding the new physics contributions that can be calculated independently of the standard model nuclear effects. We apply our method to existing Ca^{+} data and project its sensitivity to conjectured new bosons with spin-independent couplings to the electron and the neutron using narrow transitions in other atoms and ions, specifically, Sr and Yb. Future measurements are expected to improve the relative precision by 5 orders of magnitude, and they can potentially lead to an unprecedented sensitivity for bosons within the 0.3 to 10 MeV mass range.
Probing New Long-Range Interactions by Isotope Shift Spectroscopy
Berengut, Julian C.; Budker, Dmitry; Delaunay, Cédric; ...
2018-02-26
We explore a method to probe new long- and intermediate-range interactions using precision atomic isotope shift spectroscopy. We develop a formalism to interpret linear King plots as bounds on new physics with minimal theory inputs. We focus only on bounding the new physics contributions that can be calculated independently of the standard model nuclear effects. We apply our method to existing Ca + data and project its sensitivity to conjectured new bosons with spin-independent couplings to the electron and the neutron using narrow transitions in other atoms and ions, specifically, Sr and Yb. Future measurements are expected to improve themore » relative precision by 5 orders of magnitude, and they can potentially lead to an unprecedented sensitivity for bosons within the 0.3 to 10 MeV mass range.« less
Experimental Detection of Quantum Channel Capacities.
Cuevas, Álvaro; Proietti, Massimiliano; Ciampini, Mario Arnolfo; Duranti, Stefano; Mataloni, Paolo; Sacchi, Massimiliano F; Macchiavello, Chiara
2017-09-08
We present an efficient experimental procedure that certifies nonvanishing quantum capacities for qubit noisy channels. Our method is based on the use of a fixed bipartite entangled state, where the system qubit is sent to the channel input. A particular set of local measurements is performed at the channel output and the ancilla qubit mode, obtaining lower bounds to the quantum capacities for any unknown channel with no need of quantum process tomography. The entangled qubits have a Bell state configuration and are encoded in photon polarization. The lower bounds are found by estimating the Shannon and von Neumann entropies at the output using an optimized basis, whose statistics is obtained by measuring only the three observables σ_{x}⊗σ_{x}, σ_{y}⊗σ_{y}, and σ_{z}⊗σ_{z}.
Engine control techniques to account for fuel effects
Kumar, Shankar; Frazier, Timothy R.; Stanton, Donald W.; Xu, Yi; Bunting, Bruce G.; Wolf, Leslie R.
2014-08-26
A technique for engine control to account for fuel effects including providing an internal combustion engine and a controller to regulate operation thereof, the engine being operable to combust a fuel to produce an exhaust gas; establishing a plurality of fuel property inputs; establishing a plurality of engine performance inputs; generating engine control information as a function of the fuel property inputs and the engine performance inputs; and accessing the engine control information with the controller to regulate at least one engine operating parameter.
Effects of Meteorological Data Quality on Snowpack Modeling
NASA Astrophysics Data System (ADS)
Havens, S.; Marks, D. G.; Robertson, M.; Hedrick, A. R.; Johnson, M.
2017-12-01
Detailed quality control of meteorological inputs is the most time-intensive component of running the distributed, physically-based iSnobal snow model, and the effect of data quality of the inputs on the model is unknown. The iSnobal model has been run operationally since WY2013, and is currently run in several basins in Idaho and California. The largest amount of user input during modeling is for the quality control of precipitation, temperature, relative humidity, solar radiation, wind speed and wind direction inputs. Precipitation inputs require detailed user input and are crucial to correctly model the snowpack mass. This research applies a range of quality control methods to meteorological input, from raw input with minimal cleaning, to complete user-applied quality control. The meteorological input cleaning generally falls into two categories. The first is global minimum/maximum and missing value correction that could be corrected and/or interpolated with automated processing. The second category is quality control for inputs that are not globally erroneous, yet are still unreasonable and generally indicate malfunctioning measurement equipment, such as temperature or relative humidity that remains constant, or does not correlate with daily trends observed at nearby stations. This research will determine how sensitive model outputs are to different levels of quality control and guide future operational applications.
Second law of thermodynamics and quantum feedback control: Maxwell's demon with weak measurements
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jacobs, Kurt
2009-07-15
Recently Sagawa and Ueda [Phys. Rev. Lett. 100, 080403 (2008)] derived a bound on the work that can be extracted from a quantum system with the use of feedback control. For many quantum measurements their bound was not tight. We show that a tight version of this bound follows straightforwardly from recent work on Maxwell's demon by Alicki et al. [Open Syst. Inf. Dyn. 11, 205 (2004)], for both discrete and continuous feedback control. Our analysis also shows that bare, efficient measurements always do non-negative work on a system in equilibrium, but do not add heat.
NASA Astrophysics Data System (ADS)
Chen, Zhixiang; Fu, Bin
This paper is our third step towards developing a theory of testing monomials in multivariate polynomials and concentrates on two problems: (1) How to compute the coefficients of multilinear monomials; and (2) how to find a maximum multilinear monomial when the input is a ΠΣΠ polynomial. We first prove that the first problem is #P-hard and then devise a O *(3 n s(n)) upper bound for this problem for any polynomial represented by an arithmetic circuit of size s(n). Later, this upper bound is improved to O *(2 n ) for ΠΣΠ polynomials. We then design fully polynomial-time randomized approximation schemes for this problem for ΠΣ polynomials. On the negative side, we prove that, even for ΠΣΠ polynomials with terms of degree ≤ 2, the first problem cannot be approximated at all for any approximation factor ≥ 1, nor "weakly approximated" in a much relaxed setting, unless P=NP. For the second problem, we first give a polynomial time λ-approximation algorithm for ΠΣΠ polynomials with terms of degrees no more a constant λ ≥ 2. On the inapproximability side, we give a n (1 - ɛ)/2 lower bound, for any ɛ> 0, on the approximation factor for ΠΣΠ polynomials. When the degrees of the terms in these polynomials are constrained as ≤ 2, we prove a 1.0476 lower bound, assuming Pnot=NP; and a higher 1.0604 lower bound, assuming the Unique Games Conjecture.
Methods, systems and apparatus for controlling operation of two alternating current (AC) machines
Gallegos-Lopez, Gabriel [Torrance, CA; Nagashima, James M [Cerritos, CA; Perisic, Milun [Torrance, CA; Hiti, Silva [Redondo Beach, CA
2012-02-14
A system is provided for controlling two AC machines. The system comprises a DC input voltage source that provides a DC input voltage, a voltage boost command control module (VBCCM), a five-phase PWM inverter module coupled to the two AC machines, and a boost converter coupled to the inverter module and the DC input voltage source. The boost converter is designed to supply a new DC input voltage to the inverter module having a value that is greater than or equal to a value of the DC input voltage. The VBCCM generates a boost command signal (BCS) based on modulation indexes from the two AC machines. The BCS controls the boost converter such that the boost converter generates the new DC input voltage in response to the BCS. When the two AC machines require additional voltage that exceeds the DC input voltage required to meet a combined target mechanical power required by the two AC machines, the BCS controls the boost converter to drive the new DC input voltage generated by the boost converter to a value greater than the DC input voltage.
A passivity criterion for sampled-data bilateral teleoperation systems.
Jazayeri, Ali; Tavakoli, Mahdi
2013-01-01
A teleoperation system consists of a teleoperator, a human operator, and a remote environment. Conditions involving system and controller parameters that ensure the teleoperator passivity can serve as control design guidelines to attain maximum teleoperation transparency while maintaining system stability. In this paper, sufficient conditions for teleoperator passivity are derived for when position error-based controllers are implemented in discrete-time. This new analysis is necessary because discretization causes energy leaks and does not necessarily preserve the passivity of the system. The proposed criterion for sampled-data teleoperator passivity imposes lower bounds on the teleoperator's robots dampings, an upper bound on the sampling time, and bounds on the control gains. The criterion is verified through simulations and experiments.
Eye-gaze and intent: Application in 3D interface control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schryver, J.C.; Goldberg, J.H.
1993-06-01
Computer interface control is typically accomplished with an input ``device`` such as keyboard, mouse, trackball, etc. An input device translates a users input actions, such as mouse clicks and key presses, into appropriate computer commands. To control the interface, the user must first convert intent into the syntax of the input device. A more natural means of computer control is possible when the computer can directly infer user intent, without need of intervening input devices. We describe an application of eye-gaze-contingent control of an interactive three-dimensional (3D) user interface. A salient feature of the user interface is natural input, withmore » a heightened impression of controlling the computer directly by the mind. With this interface, input of rotation and translation are intuitive, whereas other abstract features, such as zoom, are more problematic to match with user intent. This paper describes successes with implementation to date, and ongoing efforts to develop a more sophisticated intent inferencing methodology.« less
Eye-gaze and intent: Application in 3D interface control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schryver, J.C.; Goldberg, J.H.
1993-01-01
Computer interface control is typically accomplished with an input device'' such as keyboard, mouse, trackball, etc. An input device translates a users input actions, such as mouse clicks and key presses, into appropriate computer commands. To control the interface, the user must first convert intent into the syntax of the input device. A more natural means of computer control is possible when the computer can directly infer user intent, without need of intervening input devices. We describe an application of eye-gaze-contingent control of an interactive three-dimensional (3D) user interface. A salient feature of the user interface is natural input, withmore » a heightened impression of controlling the computer directly by the mind. With this interface, input of rotation and translation are intuitive, whereas other abstract features, such as zoom, are more problematic to match with user intent. This paper describes successes with implementation to date, and ongoing efforts to develop a more sophisticated intent inferencing methodology.« less
Topologically protected bound states in one-dimensional Floquet acoustic waveguide systems
NASA Astrophysics Data System (ADS)
Peng, Yu-Gui; Geng, Zhi-Guo; Zhu, Xue-Feng
2018-03-01
Topological manipulation of sound has recently been a hot spot in acoustics due to the fascinating property of defect immune transport. To the best of our knowledge, the studies on one-dimensional (1D) topological acoustic systems hitherto mainly focus on the case of the Su-Schrieffer-Heeger model. Here, we show that topologically protected bound states may also exist in 1D periodically modulated acoustic waveguide systems, viz., 1D Floquet topological insulators. The results show that tuning the coupling strength in a waveguide lattice could trigger topological phase transition, which gives rise to topologically protected interface states as we put together two waveguide lattices featured with different topological phases or winding numbers. However, for the combined lattice, input at the waveguides other than the interfacial ones will excite bulk states. We have further verified the robustness of interface bound states against the variation of coupling strengths between the two distinct waveguide lattices. This work extends the scope of topological acoustics and may promote potential applications for acoustic devices with topological functionalities.
Towards full band colorless reception with coherent balanced receivers.
Zhang, Bo; Malouin, Christian; Schmidt, Theodore J
2012-04-23
In addition to linear compensation of fiber channel impairments, coherent receivers also provide colorless selection of any desired data channel within multitude of incident wavelengths, without the need of a channel selecting filter. In this paper, we investigate the design requirements for colorless reception using a coherent balanced receiver, considering both the optical front end (OFE) and the transimpedance amplifier (TIA). We develop analytical models to predict the system performance as a function of receiver design parameters and show good agreement against numerical simulations. At low input signal power, an optimum local oscillator (LO) power is shown to exist where the thermal noise is balanced with the residual LO-RIN beat noise. At high input signal power, we show the dominant noise effect is the residual self-beat noise from the out of band (OOB) channels, which scales not only with the number of OOB channels and the common mode rejection ratio (CMRR) of the OFE, but also depends on the link residual chromatic dispersion (CD) and the orientation of the polarization tributaries relative to the receiver. This residual self-beat noise from OOB channels sets the lower bound for the LO power. We also investigate the limitations imposed by overload in the TIA, showing analytically that the DC current scales only with the number of OOB channels, while the differential AC current scales only with the link residual CD, which induces high peak-to-average power ratio (PAPR). Both DC and AC currents at the input to the TIA set the upper bounds for the LO power. Considering both the OFE noise limit and the TIA overload limit, we show that the receiver operating range is notably narrowed for dispersion unmanaged links, as compared to dispersion managed links. © 2012 Optical Society of America
Short-term memory capacity in networks via the restricted isometry property.
Charles, Adam S; Yap, Han Lun; Rozell, Christopher J
2014-06-01
Cortical networks are hypothesized to rely on transient network activity to support short-term memory (STM). In this letter, we study the capacity of randomly connected recurrent linear networks for performing STM when the input signals are approximately sparse in some basis. We leverage results from compressed sensing to provide rigorous nonasymptotic recovery guarantees, quantifying the impact of the input sparsity level, the input sparsity basis, and the network characteristics on the system capacity. Our analysis demonstrates that network memory capacities can scale superlinearly with the number of nodes and in some situations can achieve STM capacities that are much larger than the network size. We provide perfect recovery guarantees for finite sequences and recovery bounds for infinite sequences. The latter analysis predicts that network STM systems may have an optimal recovery length that balances errors due to omission and recall mistakes. Furthermore, we show that the conditions yielding optimal STM capacity can be embodied in several network topologies, including networks with sparse or dense connectivities.
Cortical systems mediating visual attention to both objects and spatial locations
Shomstein, Sarah; Behrmann, Marlene
2006-01-01
Natural visual scenes consist of many objects occupying a variety of spatial locations. Given that the plethora of information cannot be processed simultaneously, the multiplicity of inputs compete for representation. Using event-related functional MRI, we show that attention, the mechanism by which a subset of the input is selected, is mediated by the posterior parietal cortex (PPC). Of particular interest is that PPC activity is differentially sensitive to the object-based properties of the input, with enhanced activation for those locations bound by an attended object. Of great interest too is the ensuing modulation of activation in early cortical regions, reflected as differences in the temporal profile of the blood oxygenation level-dependent (BOLD) response for within-object versus between-object locations. These findings indicate that object-based selection results from an object-sensitive reorienting signal issued by the PPC. The dynamic circuit between the PPC and earlier sensory regions then enables observers to attend preferentially to objects of interest in complex scenes. PMID:16840559
Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Boskovic, Jovan D.
2008-01-01
This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.
iGen: An automated generator of simplified models with provable error bounds.
NASA Astrophysics Data System (ADS)
Tang, D.; Dobbie, S.
2009-04-01
Climate models employ various simplifying assumptions and parameterisations in order to increase execution speed. However, in order to draw conclusions about the Earths climate from the results of a climate simulation it is necessary to have information about the error that these assumptions and parameterisations introduce. A novel computer program, called iGen, is being developed which automatically generates fast, simplified models by analysing the source code of a slower, high resolution model. The resulting simplified models have provable bounds on error compared to the high resolution model and execute at speeds that are typically orders of magnitude faster. iGen's input is a definition of the prognostic variables of the simplified model, a set of bounds on acceptable error and the source code of a model that captures the behaviour of interest. In the case of an atmospheric model, for example, this would be a global cloud resolving model with very high resolution. Although such a model would execute far too slowly to be used directly in a climate model, iGen never executes it. Instead, it converts the code of the resolving model into a mathematical expression which is then symbolically manipulated and approximated to form a simplified expression. This expression is then converted back into a computer program and output as a simplified model. iGen also derives and reports formal bounds on the error of the simplified model compared to the resolving model. These error bounds are always maintained below the user-specified acceptable error. Results will be presented illustrating the success of iGen's analysis of a number of example models. These extremely encouraging results have lead on to work which is currently underway to analyse a cloud resolving model and so produce an efficient parameterisation of moist convection with formally bounded error.
Design, Fabrication, and Modeling of a Novel Dual-Axis Control Input PZT Gyroscope.
Chang, Cheng-Yang; Chen, Tsung-Lin
2017-10-31
Conventional gyroscopes are equipped with a single-axis control input, limiting their performance. Although researchers have proposed control algorithms with dual-axis control inputs to improve gyroscope performance, most have verified the control algorithms through numerical simulations because they lacked practical devices with dual-axis control inputs. The aim of this study was to design a piezoelectric gyroscope equipped with a dual-axis control input so that researchers may experimentally verify those control algorithms in future. Designing a piezoelectric gyroscope with a dual-axis control input is more difficult than designing a conventional gyroscope because the control input must be effective over a broad frequency range to compensate for imperfections, and the multiple mode shapes in flexural deformations complicate the relation between flexural deformation and the proof mass position. This study solved these problems by using a lead zirconate titanate (PZT) material, introducing additional electrodes for shielding, developing an optimal electrode pattern, and performing calibrations of undesired couplings. The results indicated that the fabricated device could be operated at 5.5±1 kHz to perform dual-axis actuations and position measurements. The calibration of the fabricated device was completed by system identifications of a new dynamic model including gyroscopic motions, electromechanical coupling, mechanical coupling, electrostatic coupling, and capacitive output impedance. Finally, without the assistance of control algorithms, the "open loop sensitivity" of the fabricated gyroscope was 1.82 μV/deg/s with a nonlinearity of 9.5% full-scale output. This sensitivity is comparable with those of other PZT gyroscopes with single-axis control inputs.
The Jet Propulsion Laboratory shared control architecture and implementation
NASA Technical Reports Server (NTRS)
Backes, Paul G.; Hayati, Samad
1990-01-01
A hardware and software environment for shared control of telerobot task execution has been implemented. Modes of task execution range from fully teleoperated to fully autonomous as well as shared where hand controller inputs from the human operator are mixed with autonomous system inputs in real time. The objective of the shared control environment is to aid the telerobot operator during task execution by merging real-time operator control from hand controllers with autonomous control to simplify task execution for the operator. The operator is the principal command source and can assign as much autonomy for a task as desired. The shared control hardware environment consists of two PUMA 560 robots, two 6-axis force reflecting hand controllers, Universal Motor Controllers for each of the robots and hand controllers, a SUN4 computer, and VME chassis containing 68020 processors and input/output boards. The operator interface for shared control, the User Macro Interface (UMI), is a menu driven interface to design a task and assign the levels of teleoperated and autonomous control. The operator also sets up the system monitor which checks safety limits during task execution. Cartesian-space degrees of freedom for teleoperated and/or autonomous control inputs are selected within UMI as well as the weightings for the teleoperation and autonmous inputs. These are then used during task execution to determine the mix of teleoperation and autonomous inputs. Some of the autonomous control primitives available to the user are Joint-Guarded-Move, Cartesian-Guarded-Move, Move-To-Touch, Pin-Insertion/Removal, Door/Crank-Turn, Bolt-Turn, and Slide. The operator can execute a task using pure teleoperation or mix control execution from the autonomous primitives with teleoperated inputs. Presently the shared control environment supports single arm task execution. Work is presently underway to provide the shared control environment for dual arm control. Teleoperation during shared control is only Cartesian space control and no force-reflection is provided. Force-reflecting teleoperation and joint space operator inputs are planned extensions to the environment.
Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model.
Papasavvas, Christoforos A; Wang, Yujiang; Trevelyan, Andrew J; Kaiser, Marcus
2015-09-01
Experimental results suggest that there are two distinct mechanisms of inhibition in cortical neuronal networks: subtractive and divisive inhibition. They modulate the input-output function of their target neurons either by increasing the input that is needed to reach maximum output or by reducing the gain and the value of maximum output itself, respectively. However, the role of these mechanisms on the dynamics of the network is poorly understood. We introduce a novel population model and numerically investigate the influence of divisive inhibition on network dynamics. Specifically, we focus on the transitions from a state of regular oscillations to a state of chaotic dynamics via period-doubling bifurcations. The model with divisive inhibition exhibits a universal transition rate to chaos (Feigenbaum behavior). In contrast, in an equivalent model without divisive inhibition, transition rates to chaos are not bounded by the universal constant (non-Feigenbaum behavior). This non-Feigenbaum behavior, when only subtractive inhibition is present, is linked to the interaction of bifurcation curves in the parameter space. Indeed, searching the parameter space showed that such interactions are impossible when divisive inhibition is included. Therefore, divisive inhibition prevents non-Feigenbaum behavior and, consequently, any abrupt transition to chaos. The results suggest that the divisive inhibition in neuronal networks could play a crucial role in keeping the states of order and chaos well separated and in preventing the onset of pathological neural dynamics.
Environmental assessment of metal exposure to corals living in Castle Harbour, Bermuda
Prouty, N.G.; Goodkin, N.F.; Jones, R.; Lamborg, C.H.; Storlazzi, C.D.; Hughen, K.A.
2013-01-01
Environmental contamination in Castle Harbour, Bermuda, has been linked to the dissolution and leaching of contaminants from the adjacent marine landfill. This study expands the evidence for environmental impact of leachate from the landfill by quantitatively demonstrating elevated metal uptake over the last 30 years in corals growing in Castle Harbour. Coral Pb/Ca, Zn/Ca and Mn/Ca ratios and total Hg concentrations are elevated relative to an adjacent control site in John Smith's Bay. The temporal variability in the Castle Harbour coral records suggests that while the landfill has increased in size over the last 35 years, the dominant input of metals is through periodic leaching of contaminants from the municipal landfill and surrounding sediment. Elevated contaminants in the surrounding sediment suggest that resuspension is an important transport medium for transferring heavy metals to corals. Increased winds, particularly during the 1990s, were accompanied by higher coral metal composition at Castle Harbour. Coupled with wind-induced resuspension, interannual changes in sea level within the Harbour can lead to increased bioavailability of sediment-bound metals and subsequent coral metal assimilation. At John Smith's Bay, large scale convective mixing may be driving interannual metal variability in the coral record rather than impacts from land-based activities. Results from this study provide important insights into the coupling of natural variability and anthropogenic input of contaminants to the nearshore environment.
When the Ostrich-Algorithm Fails: Blanking Method Affects Spike Train Statistics.
Joseph, Kevin; Mottaghi, Soheil; Christ, Olaf; Feuerstein, Thomas J; Hofmann, Ulrich G
2018-01-01
Modern electroceuticals are bound to employ the usage of electrical high frequency (130-180 Hz) stimulation carried out under closed loop control, most prominent in the case of movement disorders. However, particular challenges are faced when electrical recordings of neuronal tissue are carried out during high frequency electrical stimulation, both in-vivo and in-vitro . This stimulation produces undesired artifacts and can render the recorded signal only partially useful. The extent of these artifacts is often reduced by temporarily grounding the recording input during stimulation pulses. In the following study, we quantify the effects of this method, "blanking," on the spike count and spike train statistics. Starting from a theoretical standpoint, we calculate a loss in the absolute number of action potentials, depending on: width of the blanking window, frequency of stimulation, and intrinsic neuronal activity. These calculations were then corroborated by actual high signal to noise ratio (SNR) single cell recordings. We state that, for clinically relevant frequencies of 130 Hz (used for movement disorders) and realistic blanking windows of 2 ms, up to 27% of actual existing spikes are lost. We strongly advice cautioned use of the blanking method when spike rate quantification is attempted. Blanking (artifact removal by temporarily grounding input), depending on recording parameters, can lead to significant spike loss. Very careful use of blanking circuits is advised.
When the Ostrich-Algorithm Fails: Blanking Method Affects Spike Train Statistics
Joseph, Kevin; Mottaghi, Soheil; Christ, Olaf; Feuerstein, Thomas J.; Hofmann, Ulrich G.
2018-01-01
Modern electroceuticals are bound to employ the usage of electrical high frequency (130–180 Hz) stimulation carried out under closed loop control, most prominent in the case of movement disorders. However, particular challenges are faced when electrical recordings of neuronal tissue are carried out during high frequency electrical stimulation, both in-vivo and in-vitro. This stimulation produces undesired artifacts and can render the recorded signal only partially useful. The extent of these artifacts is often reduced by temporarily grounding the recording input during stimulation pulses. In the following study, we quantify the effects of this method, “blanking,” on the spike count and spike train statistics. Starting from a theoretical standpoint, we calculate a loss in the absolute number of action potentials, depending on: width of the blanking window, frequency of stimulation, and intrinsic neuronal activity. These calculations were then corroborated by actual high signal to noise ratio (SNR) single cell recordings. We state that, for clinically relevant frequencies of 130 Hz (used for movement disorders) and realistic blanking windows of 2 ms, up to 27% of actual existing spikes are lost. We strongly advice cautioned use of the blanking method when spike rate quantification is attempted. Impact statement Blanking (artifact removal by temporarily grounding input), depending on recording parameters, can lead to significant spike loss. Very careful use of blanking circuits is advised. PMID:29780301
Step-control of electromechanical systems
Lewis, Robert N.
1979-01-01
The response of an automatic control system to a general input signal is improved by applying a test input signal, observing the response to the test input signal and determining correctional constants necessary to provide a modified input signal to be added to the input to the system. A method is disclosed for determining correctional constants. The modified input signal, when applied in conjunction with an operating signal, provides a total system output exhibiting an improved response. This method is applicable to open-loop or closed-loop control systems. The method is also applicable to unstable systems, thus allowing controlled shut-down before dangerous or destructive response is achieved and to systems whose characteristics vary with time, thus resulting in improved adaptive systems.
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.
Petri net modelling of buffers in automated manufacturing systems.
Zhou, M; Dicesare, F
1996-01-01
This paper presents Petri net models of buffers and a methodology by which buffers can be included in a system without introducing deadlocks or overflows. The context is automated manufacturing. The buffers and models are classified as random order or order preserved (first-in-first-out or last-in-first-out), single-input-single-output or multiple-input-multiple-output, part type and/or space distinguishable or indistinguishable, and bounded or safe. Theoretical results for the development of Petri net models which include buffer modules are developed. This theory provides the conditions under which the system properties of boundedness, liveness, and reversibility are preserved. The results are illustrated through two manufacturing system examples: a multiple machine and multiple buffer production line and an automatic storage and retrieval system in the context of flexible manufacturing.
Team Electronic Gameplay Combining Different Means of Control
NASA Technical Reports Server (NTRS)
Palsson, Olafur S. (Inventor); Pope, Alan T. (Inventor)
2014-01-01
Disclosed are methods and apparatuses provided for modifying the effect of an operator controlled input device on an interactive device to encourage the self-regulation of at least one physiological activity by a person different than the operator. The interactive device comprises a display area which depicts images and apparatus for receiving at least one input from the operator controlled input device to thus permit the operator to control and interact with at least some of the depicted images. One effect modification comprises measurement of the physiological activity of a person different from the operator, while modifying the ability of the operator to control and interact with at least some of the depicted images by modifying the input from the operator controlled input device in response to changes in the measured physiological signal.
How the type of input function affects the dynamic response of conducting polymer actuators
NASA Astrophysics Data System (ADS)
Xiang, Xingcan; Alici, Gursel; Mutlu, Rahim; Li, Weihua
2014-10-01
There has been a growing interest in smart actuators typified by conducting polymer actuators, especially in their (i) fabrication, modeling and control with minimum external data and (ii) applications in bio-inspired devices, robotics and mechatronics. Their control is a challenging research problem due to the complex and nonlinear properties of these actuators, which cannot be predicted accurately. Based on an input-shaping technique, we propose a new method to improve the conducting polymer actuators’ command-following ability, while minimizing their electric power consumption. We applied four input functions with smooth characteristics to a trilayer conducting polymer actuator to experimentally evaluate its command-following ability under an open-loop control strategy and a simulated feedback control strategy, and, more importantly, to quantify how the type of input function affects the dynamic response of this class of actuators. We have found that the four smooth inputs consume less electrical power than sharp inputs such as a step input with discontinuous higher-order derivatives. We also obtained an improved transient response performance from the smooth inputs, especially under the simulated feedback control strategy, which we have proposed previously [X Xiang, R Mutlu, G Alici, and W Li, 2014 “Control of conducting polymer actuators without physical feedback: simulated feedback control approach with particle swarm optimization’, Journal of Smart Materials and Structure, 23]. The idea of using a smooth input command, which results in lower power consumption and better control performance, can be extended to other smart actuators. Consuming less electrical energy or power will have a direct effect on enhancing the operational life of these actuators.
Input filter compensation for switching regulators
NASA Technical Reports Server (NTRS)
Lee, F. C.; Kelkar, S. S.
1982-01-01
The problems caused by the interaction between the input filter, output filter, and the control loop are discussed. The input filter design is made more complicated because of the need to avoid performance degradation and also stay within the weight and loss limitations. Conventional input filter design techniques are then dicussed. The concept of pole zero cancellation is reviewed; this concept is the basis for an approach to control the peaking of the output impedance of the input filter and thus mitigate some of the problems caused by the input filter. The proposed approach for control of the peaking of the output impedance of the input filter is to use a feedforward loop working in conjunction with feedback loops, thus forming a total state control scheme. The design of the feedforward loop for a buck regulator is described. A possible implementation of the feedforward loop design is suggested.
A Computational Framework to Control Verification and Robustness Analysis
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.
2010-01-01
This paper presents a methodology for evaluating the robustness of a controller based on its ability to satisfy the design requirements. The framework proposed is generic since it allows for high-fidelity models, arbitrary control structures and arbitrary functional dependencies between the requirements and the uncertain parameters. The cornerstone of this contribution is the ability to bound the region of the uncertain parameter space where the degradation in closed-loop performance remains acceptable. The size of this bounding set, whose geometry can be prescribed according to deterministic or probabilistic uncertainty models, is a measure of robustness. The robustness metrics proposed herein are the parametric safety margin, the reliability index, the failure probability and upper bounds to this probability. The performance observed at the control verification setting, where the assumptions and approximations used for control design may no longer hold, will fully determine the proposed control assessment.
Wang, Fei-Yue; Jin, Ning; Liu, Derong; Wei, Qinglai
2011-01-01
In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an ε-error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method.
Dynamics of nonlinear feedback control.
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.
Mechanically triggered solute uptake in soft contact lenses.
Tavazzi, Silvia; Ferraro, Lorenzo; Fagnola, Matteo; Cozza, Federica; Farris, Stefano; Bonetti, Simone; Simonutti, Roberto; Borghesi, Alessandro
2015-06-01
Molecular arrangement plays a role in the diffusion of water and solutes across soft contact lenses. In particular, the uptake of solutes in hydrated contact lenses can occur as long as free water is available for diffusion. In this work, we investigated the effect of mechanical vibrations of low frequency (200 Hz) on the solute uptake. Hyaluronan, a polysaccharide of ophthalmic use, was taken as example of solute of interest. For a specific water-hydrated hydrogel material, differential scanning calorimetry experiments showed that a large fraction of the hydration water accounted for loosely-bound water, both before and after one week of daily-wear of the lenses. The size (of the order of magnitude of few hundreds of nanometers) of hyaluronan in aqueous solution was found to be less than the size of the pores of the lens observed by scanning electron microscopy. However, solute uptake in already-hydrated lenses was negligible by simple immersion, while a significant increase occurred under mechanical vibrations of 200 Hz, thus providing experimental evidence of mechanically triggered enhanced solute uptake, which is attributed to the release of interfacial loosely-bound water. Also other materials were taken into consideration. However, the effectiveness of mechanical vibrations for hyaluronan uptake is restricted to lenses containing interfacial loosely-bound water. Indeed, loosely-bound water is expected to be bound to the polymer with bonding energies of the order of magnitude of 10-100 J/g, which are compatible with the energy input supplied by the vibrations. Copyright © 2015 Elsevier B.V. All rights reserved.
Interplanetary medium data book
NASA Technical Reports Server (NTRS)
King, J. H.
1977-01-01
Unresolved questions on the physics of solar wind and its effects on magnetospheric processes and cosmic ray propagation were addressed with hourly averaged interplanetary plasma and magnetic field data. This composite data set is described with its content and extent, sources, limits of validity, and the mutual consistency studies and normalizations to which the input data were subjected. Hourly averaged parameters were presented in the form of digital listings and 27-day plots. The listings are contained in a separately bound appendix.
1991-11-08
only simple bounds on delays but also relate the delays in linear inequalities so that tradeoffs are apparent. We model circuits as communicating...set of linear inequalities constraining the variables. These relations provide synthesis tools with information about tradeoffs between circuit delays...available to express the original circuit as a graph of elementary gates and then cover the graph’s fanout-free trees with collections of three-input
Radar Imaging for Urban Sensing
2010-04-01
waveforms, we fix the input SNR to the matched filter in all cases. The noise variance may be obtained as, 97 ^ l ^feo (20) where Pmax is the highest...maximum likelihood, and cramer-rao bound," IEEE Trans. Acoust., Speech, Signal Processing, vol. 37, no. 5, pp. 720-741, May 1989. [16] L . Frazier...it may fail to work when directly applied to extended targets or target returns of low SNR. The Beamspace MUSIC (BS-MUSIC), in which the MUSIC
User's guide for mapIMG 3--Map image re-projection software package
Finn, Michael P.; Mattli, David M.
2012-01-01
Version 0.0 (1995), Dan Steinwand, U.S. Geological Survey (USGS)/Earth Resources Observation Systems (EROS) Data Center (EDC)--Version 0.0 was a command line version for UNIX that required four arguments: the input metadata, the output metadata, the input data file, and the output destination path. Version 1.0 (2003), Stephen Posch and Michael P. Finn, USGS/Mid-Continent Mapping Center (MCMC--Version 1.0 added a GUI interface that was built using the Qt library for cross platform development. Version 1.01 (2004), Jason Trent and Michael P. Finn, USGS/MCMC--Version 1.01 suggested bounds for the parameters of each projection. Support was added for larger input files, storage of the last used input and output folders, and for TIFF/ GeoTIFF input images. Version 2.0 (2005), Robert Buehler, Jason Trent, and Michael P. Finn, USGS/National Geospatial Technical Operations Center (NGTOC)--Version 2.0 added Resampling Methods (Mean, Mode, Min, Max, and Sum), updated the GUI design, and added the viewer/pre-viewer. The metadata style was changed to XML and was switched to a new naming convention. Version 3.0 (2009), David Mattli and Michael P. Finn, USGS/Center of Excellence for Geospatial Information Science (CEGIS)--Version 3.0 brings optimized resampling methods, an updated GUI, support for less than global datasets, UTM support and the whole codebase was ported to Qt4.
Predictive and Neural Predictive Control of Uncertain Systems
NASA Technical Reports Server (NTRS)
Kelkar, Atul G.
2000-01-01
Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.
Robustness in linear quadratic feedback design with application to an aircraft control problem
NASA Technical Reports Server (NTRS)
Patel, R. V.; Sridhar, B.; Toda, M.
1977-01-01
Some new results concerning robustness and asymptotic properties of error bounds of a linear quadratic feedback design are applied to an aircraft control problem. An autopilot for the flare control of the Augmentor Wing Jet STOL Research Aircraft (AWJSRA) is designed based on Linear Quadratic (LQ) theory and the results developed in this paper. The variation of the error bounds to changes in the weighting matrices in the LQ design is studied by computer simulations, and appropriate weighting matrices are chosen to obtain a reasonable error bound for variations in the system matrix and at the same time meet the practical constraints for the flare maneuver of the AWJSRA. Results from the computer simulation of a satisfactory autopilot design for the flare control of the AWJSRA are presented.
Regulation of 5'-adenosine monophosphate deaminase in the freeze tolerant wood frog, Rana sylvatica.
Dieni, Christopher A; Storey, Kenneth B
2008-04-22
The wood frog, Rana sylvatica, is one of a few vertebrate species that have developed natural freeze tolerance, surviving days or weeks with 65-70% of its total body water frozen in extracellular ice masses. Frozen frogs exhibit no vital signs and their organs must endure multiple stresses, particularly long term anoxia and ischemia. Maintenance of cellular energy supply is critical to viability in the frozen state and in skeletal muscle, AMP deaminase (AMPD) plays a key role in stabilizing cellular energetics. The present study investigated AMPD control in wood frog muscle. Wood frog AMPD was subject to multiple regulatory controls: binding to subcellular structures, protein phosphorylation, and effects of allosteric effectors, cryoprotectants and temperature. The percentage of bound AMPD activity increased from 20 to 35% with the transition to the frozen state. Bound AMPD showed altered kinetic parameters compared with the free enzyme (S0.5 AMP was reduced, Hill coefficient fell to approximately 1.0) and the transition to the frozen state led to a 3-fold increase in S0.5 AMP of the bound enzyme. AMPD was a target of protein phosphorylation. Bound AMPD from control frogs proved to be a low phosphate form with a low S0.5 AMP and was phosphorylated in incubations that stimulated PKA, PKC, CaMK, or AMPK. Bound AMPD from frozen frogs was a high phosphate form with a high S0.5 AMP that was reduced under incubation conditions that stimulated protein phosphatases. Frog muscle AMPD was activated by Mg.ATP and Mg.ADP and inhibited by Mg.GTP, KCl, NaCl and NH4Cl. The enzyme product, IMP, uniquely inhibited only the bound (phosphorylated) enzyme from muscle of frozen frogs. Activators and inhibitors differentially affected the free versus bound enzyme. S0.5 AMP of bound AMPD was also differentially affected by high versus low assay temperature (25 vs 5 degrees C) and by the presence/absence of the natural cryoprotectant (250 mM glucose) that accumulates during freezing. Maintenance of long term viability under the ischemic conditions in frozen muscle requires attention to the control of cellular energetics. Differential regulatory controls on AMPD by mechanisms including binding to muscle proteins, actions allosteric effectors, glucose and temperature effects and reversible phosphorylation adjust enzyme function for an optimal role in controlling cellular adenylate levels in ischemic frozen muscle. Stable modification of AMPD properties via freeze-responsive phosphorylation may contribute both to AMPD control and to coordinating AMPD function with other enzymes of energy metabolism in cold ischemic muscle.
Optimal control of LQR for discrete time-varying systems with input delays
NASA Astrophysics Data System (ADS)
Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng
2018-04-01
In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.
Celis-Plá, Paula S M; Brown, Murray T; Santillán-Sarmiento, Alex; Korbee, Nathalie; Sáez, Claudio A; Figueroa, Félix L
2018-03-01
Global scenarios evidence that contamination due to anthropogenic activities occur at different spatial-temporal scales, being important stressors: eutrophication, due to increased nutrient inputs; and metal pollution, mostly derived from industrial activities. In this study, we investigated ecophysiological and metabolic responses to copper and nutrient excess in the brown macroalga Cystoseira tamariscifolia. Whole plants were incubated in an indoor system under control conditions, two levels of nominal copper (0.5 and 2.0μM), and two levels of nutrient supply for two weeks. Maximal quantum yield (F v /F m ) and maximal electron transport rate (ETR max ) increased under copper exposure. Photosynthetic pigments and phenolic compounds (PC) increased under the highest copper levels. The intra-cellular copper content increased under high copper exposure in both nutrient conditions. C. tamariscifolia from the Atlantic displayed efficient metal exclusion mechanisms, since most of the total copper accumulated by the cell was bound to the cell wall. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Fleischer, Robert
1996-02-01
Using the SU(3) flavour symmetry of strong interactions, we propose strategies for extracting both the CKM-angle γ and the overlineb → overlineuu overlines tree-level amplitude T‧. We present also an approximate approach using the branching ratios for the modes B+ → π+K0, Bd0 → π-K+, overlineBd0 → π +K - and B+ → π+π0 which should be rather promising from the experimental point of view. The quantities γ and T‧ determined this way may well be used as an input to control electroweak penguins in nonleptonic B-decays as has been discussed in previous work. Following these lines, we propose strategies for obtaining quantitative insights into the physics of the electroweak penguin operators and performing some consistency checks. As a by-product, we derive an upper bound of 6° for the uncertainty originating from electroweak penguins in the α-determination by means of B → ππ decays.
Abizaid, Alfonso; Liu, Zhong-Wu; Andrews, Zane B.; Shanabrough, Marya; Borok, Erzsebet; Elsworth, John D.; Roth, Robert H.; Sleeman, Mark W.; Picciotto, Marina R.; Tschöp, Matthias H.; Gao, Xiao-Bing; Horvath, Tamas L.
2006-01-01
The gut hormone ghrelin targets the brain to promote food intake and adiposity. The ghrelin receptor growth hormone secretagogue 1 receptor (GHSR) is present in hypothalamic centers controlling energy metabolism as well as in the ventral tegmental area (VTA), a region important for motivational aspects of multiple behaviors, including feeding. Here we show that in mice and rats, ghrelin bound to neurons of the VTA, where it triggered increased dopamine neuronal activity, synapse formation, and dopamine turnover in the nucleus accumbens in a GHSR-dependent manner. Direct VTA administration of ghrelin also triggered feeding, while intra-VTA delivery of a selective GHSR antagonist blocked the orexigenic effect of circulating ghrelin and blunted rebound feeding following fasting. In addition, ghrelin- and GHSR-deficient mice showed attenuated feeding responses to restricted feeding schedules. Taken together, these data suggest that the mesolimbic reward circuitry is targeted by peripheral ghrelin to influence physiological mechanisms related to feeding. PMID:17060947
Stability basin estimates fall risk from observed kinematics, demonstrated on the Sit-to-Stand task.
Shia, Victor; Moore, Talia Yuki; Holmes, Patrick; Bajcsy, Ruzena; Vasudevan, Ram
2018-04-27
The ability to quantitatively measure stability is essential to ensuring the safety of locomoting systems. While the response to perturbation directly reflects the stability of a motion, this experimental method puts human subjects at risk. Unfortunately, existing indirect methods for estimating stability from unperturbed motion have been shown to have limited predictive power. This paper leverages recent advances in dynamical systems theory to accurately estimate the stability of human motion without requiring perturbation. This approach relies on kinematic observations of a nominal Sit-to-Stand motion to construct an individual-specific dynamic model, input bounds, and feedback control that are then used to compute the set of perturbations from which the model can recover. This set, referred to as the stability basin, was computed for 14 individuals, and was able to successfully differentiate between less and more stable Sit-to-Stand strategies for each individual with greater accuracy than existing methods. Copyright © 2018 Elsevier Ltd. All rights reserved.
Borovok, Ilya; Sigal, Nadejda
2018-01-01
Listeria monocytogenes (Lm) is a saprophyte and intracellular pathogen. Transition to the pathogenic state relies on sensing of host-derived metabolites, yet it remains unclear how these are recognized and how they mediate virulence gene regulation. We previously found that low availability of isoleucine signals Lm to activate the virulent state. This response is dependent on CodY, a global regulator and isoleucine sensor. Isoleucine-bound CodY represses metabolic pathways including branched-chain amino acids (BCAA) biosynthesis, however under BCAA depletion, as occurs during infection, BCAA biosynthesis is upregulated and isoleucine-unbound CodY activates virulence genes. While isoleucine was revealed as an important input signal, it was not identified how internal levels are controlled during infection. Here we show that Lm regulates BCAA biosynthesis via CodY and via a riboregulator located upstream to the BCAA biosynthesis genes, named Rli60. rli60 is transcribed when BCAA levels drop, forming a ribosome-mediated attenuator that cis-regulates the downstream genes according to BCAA supply. Notably, we found that Rli60 restricts BCAA production, essentially starving Lm, a mechanism that is directly linked to virulence, as it controls the internal isoleucine pool and thereby CodY activity. This controlled BCAA auxotrophy likely evolved to enable isoleucine to serve as a host signal and virulence effector. PMID:29529043
Brenner, Moran; Lobel, Lior; Borovok, Ilya; Sigal, Nadejda; Herskovits, Anat A
2018-03-01
Listeria monocytogenes (Lm) is a saprophyte and intracellular pathogen. Transition to the pathogenic state relies on sensing of host-derived metabolites, yet it remains unclear how these are recognized and how they mediate virulence gene regulation. We previously found that low availability of isoleucine signals Lm to activate the virulent state. This response is dependent on CodY, a global regulator and isoleucine sensor. Isoleucine-bound CodY represses metabolic pathways including branched-chain amino acids (BCAA) biosynthesis, however under BCAA depletion, as occurs during infection, BCAA biosynthesis is upregulated and isoleucine-unbound CodY activates virulence genes. While isoleucine was revealed as an important input signal, it was not identified how internal levels are controlled during infection. Here we show that Lm regulates BCAA biosynthesis via CodY and via a riboregulator located upstream to the BCAA biosynthesis genes, named Rli60. rli60 is transcribed when BCAA levels drop, forming a ribosome-mediated attenuator that cis-regulates the downstream genes according to BCAA supply. Notably, we found that Rli60 restricts BCAA production, essentially starving Lm, a mechanism that is directly linked to virulence, as it controls the internal isoleucine pool and thereby CodY activity. This controlled BCAA auxotrophy likely evolved to enable isoleucine to serve as a host signal and virulence effector.
Controlled modification of resonant tunneling in metal-insulator-insulator-metal structures
NASA Astrophysics Data System (ADS)
Mitrovic, I. Z.; Weerakkody, A. D.; Sedghi, N.; Ralph, J. F.; Hall, S.; Dhanak, V. R.; Luo, Z.; Beeby, S.
2018-01-01
We present comprehensive experimental and theoretical work on tunnel-barrier rectifiers comprising bilayer (Nb2O5/Al2O3) insulator configurations with similar (Nb/Nb) and dissimilar (Nb/Ag) metal electrodes. The electron affinity, valence band offset, and metal work function were ascertained by X-ray photoelectron spectroscopy, variable angle spectroscopic ellipsometry, and electrical measurements on fabricated reference structures. The experimental band line-up parameters were fed into a theoretical model to predict available bound states in the Nb2O5/Al2O3 quantum well and generate tunneling probability and transmittance curves under applied bias. The onset of strong resonance in the sub-V regime was found to be controlled by a work function difference of Nb/Ag electrodes in agreement with the experimental band alignment and theoretical model. A superior low-bias asymmetry of 35 at 0.1 V and a responsivity of 5 A/W at 0.25 V were observed for the Nb/4 nm Nb2O5/1 nm Al2O3/Ag structure, sufficient to achieve a rectification of over 90% of the input alternate current terahertz signal in a rectenna device.
Neurophysiological evidence for the influence of past experience on figure-ground perception.
Trujillo, Logan T; Allen, John J B; Schnyer, David M; Peterson, Mary A
2010-02-10
A fundamental aspect of perceptual organization entails segregating visual input into shaped figures presented against shapeless backgrounds; an outcome termed "figure-ground perception" or "shape assignment." The present study examined how early in processing past experience exerts an influence on shape assignment. Event-related potential (ERP) measures of brain activity were recorded while observers viewed silhouettes of novel objects that differed in whether or not a familiar shape was suggested on the outside-the groundside-of their bounding edges (experimental versus control silhouettes, respectively). Observers perceived both types of silhouettes as novel shapes and were unaware of the familiar shape suggested on the groundside of experimental silhouettes. Nevertheless, we expected that the familiar shape would be implicitly identified early in processing and would compete for figural status with the novel shape on the inside. Early (106-156 ms) ERPs were larger for experimental silhouettes than for control silhouettes lacking familiarity cues. The early ERP difference occurred during a time interval within which edge-segmentation-dependent response differences have been observed in previous neurophysiological investigations of figure-ground perception. These results provide the first neurophysiological evidence for an influence of past experience during the earliest stages of shape assignment.
Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise
NASA Astrophysics Data System (ADS)
Hinczewski, Michael; Thirumalai, D.
2014-10-01
Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show that this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov optimal noise filter. Using concepts from umbral calculus, we generalize the linear Wiener-Kolmogorov theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function—such as ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways and the manipulation of pathways through experimental probes such as oscillatory input.
A survey of the state of the art and focused research in range systems, task 2
NASA Technical Reports Server (NTRS)
Yao, K.
1986-01-01
Many communication, control, and information processing subsystems are modeled by linear systems incorporating tapped delay lines (TDL). Such optimized subsystems result in full precision multiplications in the TDL. In order to reduce complexity and cost in a microprocessor implementation, these multiplications can be replaced by single-shift instructions which are equivalent to powers of two multiplications. Since, in general, the obvious operation of rounding the infinite precision TDL coefficients to the nearest powers of two usually yield quite poor system performance, the optimum powers of two coefficient solution was considered. Detailed explanations on the use of branch-and-bound algorithms for finding the optimum powers of two solutions are given. Specific demonstration of this methodology to the design of a linear data equalizer and its implementation in assembly language on a 8080 microprocessor with a 12 bit A/D converter are reported. This simple microprocessor implementation with optimized TDL coefficients achieves a system performance comparable to the optimum linear equalization with full precision multiplications for an input data rate of 300 baud. The philosophy demonstrated in this implementation is dully applicable to many other microprocessor controlled information processing systems.
Error control techniques for satellite and space communications
NASA Technical Reports Server (NTRS)
Costello, Daniel J., Jr.
1990-01-01
An expurgated upper bound on the event error probability of trellis coded modulation is presented. This bound is used to derive a lower bound on the minimum achievable free Euclidean distance d sub (free) of trellis codes. It is shown that the dominant parameters for both bounds, the expurgated error exponent and the asymptotic d sub (free) growth rate, respectively, can be obtained from the cutoff-rate R sub O of the transmission channel by a simple geometric construction, making R sub O the central parameter for finding good trellis codes. Several constellations are optimized with respect to the bounds.
``Carbon Credits'' for Resource-Bounded Computations Using Amortised Analysis
NASA Astrophysics Data System (ADS)
Jost, Steffen; Loidl, Hans-Wolfgang; Hammond, Kevin; Scaife, Norman; Hofmann, Martin
Bounding resource usage is important for a number of areas, notably real-time embedded systems and safety-critical systems. In this paper, we present a fully automatic static type-based analysis for inferring upper bounds on resource usage for programs involving general algebraic datatypes and full recursion. Our method can easily be used to bound any countable resource, without needing to revisit proofs. We apply the analysis to the important metrics of worst-case execution time, stack- and heap-space usage. Our results from several realistic embedded control applications demonstrate good matches between our inferred bounds and measured worst-case costs for heap and stack usage. For time usage we infer good bounds for one application. Where we obtain less tight bounds, this is due to the use of software floating-point libraries.
The Extrapolation of Elementary Sequences
NASA Technical Reports Server (NTRS)
Laird, Philip; Saul, Ronald
1992-01-01
We study sequence extrapolation as a stream-learning problem. Input examples are a stream of data elements of the same type (integers, strings, etc.), and the problem is to construct a hypothesis that both explains the observed sequence of examples and extrapolates the rest of the stream. A primary objective -- and one that distinguishes this work from previous extrapolation algorithms -- is that the same algorithm be able to extrapolate sequences over a variety of different types, including integers, strings, and trees. We define a generous family of constructive data types, and define as our learning bias a stream language called elementary stream descriptions. We then give an algorithm that extrapolates elementary descriptions over constructive datatypes and prove that it learns correctly. For freely-generated types, we prove a polynomial time bound on descriptions of bounded complexity. An especially interesting feature of this work is the ability to provide quantitative measures of confidence in competing hypotheses, using a Bayesian model of prediction.
Constraints on the [Formula: see text] form factor from analyticity and unitarity.
Ananthanarayan, B; Caprini, I; Kubis, B
Motivated by the discrepancies noted recently between the theoretical calculations of the electromagnetic [Formula: see text] form factor and certain experimental data, we investigate this form factor using analyticity and unitarity in a framework known as the method of unitarity bounds. We use a QCD correlator computed on the spacelike axis by operator product expansion and perturbative QCD as input, and exploit unitarity and the positivity of its spectral function, including the two-pion contribution that can be reliably calculated using high-precision data on the pion form factor. From this information, we derive upper and lower bounds on the modulus of the [Formula: see text] form factor in the elastic region. The results provide a significant check on those obtained with standard dispersion relations, confirming the existence of a disagreement with experimental data in the region around [Formula: see text].
Spent fuel pool storage calculations using the ISOCRIT burnup credit tool
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kucukboyaci, Vefa; Marshall, William BJ J
2012-01-01
In order to conservatively apply burnup credit in spent fuel pool criticality safety analyses, Westinghouse has developed a software tool, ISOCRIT, for generating depletion isotopics. This tool is used to create isotopics data based on specific reactor input parameters, such as design basis assembly type; bounding power/burnup profiles; reactor specific moderator temperature profiles; pellet percent theoretical density; burnable absorbers, axial blanket regions, and bounding ppm boron concentration. ISOCRIT generates burnup dependent isotopics using PARAGON; Westinghouse's state-of-the-art and licensed lattice physics code. Generation of isotopics and passing the data to the subsequent 3D KENO calculations are performed in an automated fashion,more » thus reducing the chance for human error. Furthermore, ISOCRIT provides the means for responding to any customer request regarding re-analysis due to changed parameters (e.g., power uprate, exit temperature changes, etc.) with a quick turnaround.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bernal, Andrés; Patiny, Luc; Castillo, Andrés M.
2015-02-21
Nuclear magnetic resonance (NMR) assignment of small molecules is presented as a typical example of a combinatorial optimization problem in chemical physics. Three strategies that help improve the efficiency of solution search by the branch and bound method are presented: 1. reduction of the size of the solution space by resort to a condensed structure formula, wherein symmetric nuclei are grouped together; 2. partitioning of the solution space based on symmetry, that becomes the basis for an efficient branching procedure; and 3. a criterion of selection of input restrictions that leads to increased gaps between branches and thus faster pruningmore » of non-viable solutions. Although the examples chosen to illustrate this work focus on small-molecule NMR assignment, the results are generic and might help solving other combinatorial optimization problems.« less
Constructions for finite-state codes
NASA Technical Reports Server (NTRS)
Pollara, F.; Mceliece, R. J.; Abdel-Ghaffar, K.
1987-01-01
A class of codes called finite-state (FS) codes is defined and investigated. These codes, which generalize both block and convolutional codes, are defined by their encoders, which are finite-state machines with parallel inputs and outputs. A family of upper bounds on the free distance of a given FS code is derived from known upper bounds on the minimum distance of block codes. A general construction for FS codes is then given, based on the idea of partitioning a given linear block into cosets of one of its subcodes, and it is shown that in many cases the FS codes constructed in this way have a d sub free which is as large as possible. These codes are found without the need for lengthy computer searches, and have potential applications for future deep-space coding systems. The issue of catastropic error propagation (CEP) for FS codes is also investigated.
Feedback attitude sliding mode regulation control of spacecraft using arm motion
NASA Astrophysics Data System (ADS)
Shi, Ye; Liang, Bin; Xu, Dong; Wang, Xueqian; Xu, Wenfu
2013-09-01
The problem of spacecraft attitude regulation based on the reaction of arm motion has attracted extensive attentions from both engineering and academic fields. Most of the solutions of the manipulator’s motion tracking problem just achieve asymptotical stabilization performance, so that these controllers cannot realize precise attitude regulation because of the existence of non-holonomic constraints. Thus, sliding mode control algorithms are adopted to stabilize the tracking error with zero transient process. Due to the switching effects of the variable structure controller, once the tracking error reaches the designed hyper-plane, it will be restricted to this plane permanently even with the existence of external disturbances. Thus, precise attitude regulation can be achieved. Furthermore, taking the non-zero initial tracking errors and chattering phenomenon into consideration, saturation functions are used to replace sign functions to smooth the control torques. The relations between the upper bounds of tracking errors and the controller parameters are derived to reveal physical characteristic of the controller. Mathematical models of free-floating space manipulator are established and simulations are conducted in the end. The results show that the spacecraft’s attitude can be regulated to the position as desired by using the proposed algorithm, the steady state error is 0.000 2 rad. In addition, the joint tracking trajectory is smooth, the joint tracking errors converges to zero quickly with a satisfactory continuous joint control input. The proposed research provides a feasible solution for spacecraft attitude regulation by using arm motion, and improves the precision of the spacecraft attitude regulation.
Speech versus manual control of camera functions during a telerobotic task
NASA Technical Reports Server (NTRS)
Bierschwale, John M.; Sampaio, Carlos E.; Stuart, Mark A.; Smith, Randy L.
1989-01-01
Voice input for control of camera functions was investigated in this study. Objective were to (1) assess the feasibility of a voice-commanded camera control system, and (2) identify factors that differ between voice and manual control of camera functions. Subjects participated in a remote manipulation task that required extensive camera-aided viewing. Each subject was exposed to two conditions, voice and manual input, with a counterbalanced administration order. Voice input was found to be significantly slower than manual input for this task. However, in terms of remote manipulator performance errors and subject preference, there was no difference between modalities. Voice control of continuous camera functions is not recommended. It is believed that the use of voice input for discrete functions, such as multiplexing or camera switching, could aid performance. Hybrid mixes of voice and manual input may provide the best use of both modalities. This report contributes to a better understanding of the issues that affect the design of an efficient human/telerobot interface.
NASA Astrophysics Data System (ADS)
Li, Keqiang; Gao, Feng; Li, Shengbo Eben; Zheng, Yang; Gao, Hongbo
2017-12-01
This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.
Adaptive Control Based Harvesting Strategy for a Predator-Prey Dynamical System.
Sen, Moitri; Simha, Ashutosh; Raha, Soumyendu
2018-04-23
This paper deals with designing a harvesting control strategy for a predator-prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy.
Automatic insulation resistance testing apparatus
Wyant, Francis J.; Nowlen, Steven P.; Luker, Spencer M.
2005-06-14
An apparatus and method for automatic measurement of insulation resistances of a multi-conductor cable. In one embodiment of the invention, the apparatus comprises a power supply source, an input measuring means, an output measuring means, a plurality of input relay controlled contacts, a plurality of output relay controlled contacts, a relay controller and a computer. In another embodiment of the invention the apparatus comprises a power supply source, an input measuring means, an output measuring means, an input switching unit, an output switching unit and a control unit/data logger. Embodiments of the apparatus of the invention may also incorporate cable fire testing means. The apparatus and methods of the present invention use either voltage or current for input and output measured variables.
Studies of heat source driven natural convection
NASA Technical Reports Server (NTRS)
Kulacki, F. A.; Nagle, M. E.; Cassen, P.
1974-01-01
Natural convection energy transport in a horizontal layer of internally heated fluid with a zero heat flux lower boundary, and an isothermal upper boundary, has been studied. Quantitative information on the time-mean temperature distribution and the fluctuating component of temperature about the mean temperature in steady turbulent convection are obtained from a small thermocouple inserted into the layer through the upper bounding plate. Data are also presented on the development of temperature at several vertical positions when the layer is subject to both a sudden increase and to a sudden decrease in power input. For changes of power input from zero to a value corresponding to a Rayleigh number much greater than the critical linear stability theory value, a slight hysteresis in temperature profiles near the upper boundary is observed between the heat-up and cool-down modes.
21st-century rise in anthropogenic nitrogen deposition on a remote coral reef
NASA Astrophysics Data System (ADS)
Ren, Haojia; Chen, Yi-Chi; Wang, Xingchen T.; Wong, George T. F.; Cohen, Anne L.; DeCarlo, Thomas M.; Weigand, Mira A.; Mii, Horng-Sheng; Sigman, Daniel M.
2017-05-01
With the rapid rise in pollution-associated nitrogen inputs to the western Pacific, it has been suggested that even the open ocean has been affected. In a coral core from Dongsha Atoll, a remote coral reef ecosystem, we observe a decline in the 15N/14N of coral skeleton-bound organic matter, which signals increased deposition of anthropogenic atmospheric N on the open ocean and its incorporation into plankton and, in turn, the atoll corals. The first clear change occurred just before 2000 CE, decades later than predicted by other work. The amplitude of change suggests that, by 2010, anthropogenic atmospheric N deposition represented 20 ± 5% of the annual N input to the surface ocean in this region, which appears to be at the lower end of other estimates.
Properties of Zero-Free Transfer Function Matrices
NASA Astrophysics Data System (ADS)
D. O. Anderson, Brian; Deistler, Manfred
Transfer functions of linear, time-invariant finite-dimensional systems with more outputs than inputs, as arise in factor analysis (for example in econometrics), have, for state-variable descriptions with generic entries in the relevant matrices, no finite zeros. This paper gives a number of characterizations of such systems (and indeed square discrete-time systems with no zeros), using state-variable, impulse response, and matrix-fraction descriptions. Key properties include the ability to recover the input values at any time from a bounded interval of output values, without any knowledge of an initial state, and an ability to verify the no-zero property in terms of a property of the impulse response coefficient matrices. Results are particularized to cases where the transfer function matrix in question may or may not have a zero at infinity or a zero at zero.
Shipboard fisheries management terminals
NASA Technical Reports Server (NTRS)
Nagler, R. G.; Sager, E. V.
1980-01-01
The needs of the National Marine Fisheries Service (NMGS), National Weather Service, and the U.S. Coast Guard for locational, biological, and environmental data were assessed. The fisheries conservation zones and the yellowfin tuna jurisdiction of the NMFS operates observer programs on foreign and domestic fishing vessels. Data input terminal and data transfer and processing technology are reviewed to establish available capability. A matrix of implementation options is generated to identify the benefits of each option, and preliminary cost estimates are made. Recommendations are made for incremental application of available off the shelf hardware to obtain improved performance and benefits within a well bounded cost. Terminal recommendations are made for three interdependent shipboard units emphasizing: (1) the determination of location and fishing activity; (2) hand held data inputting and formatting in the fishing work areas; and (3) data manipulation, merging, and editing.
Spin-the-bottle Sort and Annealing Sort: Oblivious Sorting via Round-robin Random Comparisons
Goodrich, Michael T.
2013-01-01
We study sorting algorithms based on randomized round-robin comparisons. Specifically, we study Spin-the-bottle sort, where comparisons are unrestricted, and Annealing sort, where comparisons are restricted to a distance bounded by a temperature parameter. Both algorithms are simple, randomized, data-oblivious sorting algorithms, which are useful in privacy-preserving computations, but, as we show, Annealing sort is much more efficient. We show that there is an input permutation that causes Spin-the-bottle sort to require Ω(n2 log n) expected time in order to succeed, and that in O(n2 log n) time this algorithm succeeds with high probability for any input. We also show there is a specification of Annealing sort that runs in O(n log n) time and succeeds with very high probability. PMID:24550575
Communication: Fitting potential energy surfaces with fundamental invariant neural network
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shao, Kejie; Chen, Jun; Zhao, Zhiqiang
A more flexible neural network (NN) method using the fundamental invariants (FIs) as the input vector is proposed in the construction of potential energy surfaces for molecular systems involving identical atoms. Mathematically, FIs finitely generate the permutation invariant polynomial (PIP) ring. In combination with NN, fundamental invariant neural network (FI-NN) can approximate any function to arbitrary accuracy. Because FI-NN minimizes the size of input permutation invariant polynomials, it can efficiently reduce the evaluation time of potential energy, in particular for polyatomic systems. In this work, we provide the FIs for all possible molecular systems up to five atoms. Potential energymore » surfaces for OH{sub 3} and CH{sub 4} were constructed with FI-NN, with the accuracy confirmed by full-dimensional quantum dynamic scattering and bound state calculations.« less
Automatic Constraint Detection for 2D Layout Regularization.
Jiang, Haiyong; Nan, Liangliang; Yan, Dong-Ming; Dong, Weiming; Zhang, Xiaopeng; Wonka, Peter
2016-08-01
In this paper, we address the problem of constraint detection for layout regularization. The layout we consider is a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important in digitizing plans or images, such as floor plans and facade images, and in the improvement of user-created contents, such as architectural drawings and slide layouts. To regularize a layout, we aim to improve the input by detecting and subsequently enforcing alignment, size, and distance constraints between layout elements. Similar to previous work, we formulate layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm that automatically detects constraints. We evaluate the proposed framework using a variety of input layouts from different applications. Our results demonstrate that our method has superior performance to the state of the art.
Numerical simulations of flares on M dwarf stars. I - Hydrodynamics and coronal X-ray emission
NASA Technical Reports Server (NTRS)
Cheng, Chung-Chieh; Pallavicini, Roberto
1991-01-01
Flare-loop models are utilized to simulate the time evolution and physical characteristics of stellar X-ray flares by varying the values of flare-energy input and loop parameters. The hydrodynamic evolution is studied in terms of changes in the parameters of the mass, energy, and momentum equations within an area bounded by the chromosphere and the corona. The zone supports a magnetically confined loop for which processes are described including the expansion of heated coronal gas, chromospheric evaporation, and plasma compression at loop footpoints. The intensities, time profiles, and average coronal temperatures of X-ray flares are derived from the simulations and compared to observational evidence. Because the amount of evaporated material does not vary linearly with flare-energy input, large loops are required to produce the energy measured from stellar flares.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Su Jing; Chen Shaohao; Jaron-Becker, Agnieszka
We theoretically study the control of two-photon excitation to bound and dissociative states in a molecule induced by trains of laser pulses, which are equivalent to certain sets of spectral phase modulated pulses. To this end, we solve the time-dependent Schroedinger equation for the interaction of molecular model systems with an external intense laser field. Our numerical results for the temporal evolution of the population in the excited states show that, in the case of an excited dissociative state, control schemes, previously validated for the atomic case, fail due to the coupling of electronic and nuclear motion. In contrast, formore » excitation to bound states the two-photon excitation probability is controlled via the time delay and the carrier-envelope phase difference between two consecutive pulses in the train.« less
Advances in Experiment Design for High Performance Aircraft
NASA Technical Reports Server (NTRS)
Morelli, Engene A.
1998-01-01
A general overview and summary of recent advances in experiment design for high performance aircraft is presented, along with results from flight tests. General theoretical background is included, with some discussion of various approaches to maneuver design. Flight test examples from the F-18 High Alpha Research Vehicle (HARV) are used to illustrate applications of the theory. Input forms are compared using Cramer-Rao bounds for the standard errors of estimated model parameters. Directions for future research in experiment design for high performance aircraft are identified.
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.
Improved robustness and performance of discrete time sliding mode control systems.
Chakrabarty, Sohom; Bartoszewicz, Andrzej
2016-11-01
This paper presents a theoretical analysis along with simulations to show that increased robustness can be achieved for discrete time sliding mode control systems by choosing the sliding variable, or the output, to be of relative degree two instead of relative degree one. In other words it successfully reduces the ultimate bound of the sliding variable compared to the ultimate bound for standard discrete time sliding mode control systems. It is also found out that for such a selection of relative degree two output of the discrete time system, the reduced order system during sliding becomes finite time stable in absence of disturbance. With disturbance, it becomes finite time ultimately bounded. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Microfluidic Flows and Heat Transfer and Their Influence on Optical Modes in Microstructure Fibers
Davies, Edward; Christodoulides, Paul; Florides, George; Kalli, Kyriacos
2014-01-01
A finite element analysis (FEA) model has been constructed to predict the thermo-fluidic and optical properties of a microstructure optical fiber (MOF) accounting for changes in external temperature, input water velocity and optical fiber geometry. Modeling a water laminar flow within a water channel has shown that the steady-state temperature is dependent on the water channel radius while independent of the input velocity. There is a critical channel radius below which the steady-state temperature of the water channel is constant, while above, the temperature decreases. However, the distance required to reach steady state within the water channel is dependent on both the input velocity and the channel radius. The MOF has been found capable of supporting multiple modes. Despite the large thermo-optic coefficient of water, the bound modes’ response to temperature was dominated by the thermo-optic coefficient of glass. This is attributed to the majority of the light being confined within the glass, which increased with increasing external temperature due to a larger difference in the refractive index between the glass core and the water channel. PMID:28788263
Western Greenland Subglacial Hydrologic Modeling and Observables: Seismicity and GPS
NASA Astrophysics Data System (ADS)
Carmichael, J. D.; Joughin, I. R.
2010-12-01
I present a hydro-mechanical model of the Western Greenland ice sheet with surface observables for two modes of meltwater input. Using input prescribed from distributed surface data, First, I bound the subglacial carrying capacity for both a distributed and localized system, in a typical summer. I provide observations of the ambient seismic response and its support for an established surface-to-bed connection. Second, I show the ice sheet response to large impulsive hydraulic inputs (lake drainage events) should produce distinct seismic observables that depend upon the localization of the drainage systems. In the former case, the signal propagates as a diffusive wave, while the channelized case, the response is localized. I provide a discussion of how these results are consistent with previous reports (Das et al, 2008, Joughin et al, 2008) of melt-induced speedup along Greenland's Western Flank. Late summer seismicity for a four-receiver array deployed near a supraglacial lake, 68 44.379N, 49 30.064W. Clusters of seismic activity are characterized by dominant shear-wave energy, consistent with basal sliding events.
Modal control of an oblique wing aircraft
NASA Technical Reports Server (NTRS)
Phillips, James D.
1989-01-01
A linear modal control algorithm is applied to the NASA Oblique Wing Research Aircraft (OWRA). The control law is evaluated using a detailed nonlinear flight simulation. It is shown that the modal control law attenuates the coupling and nonlinear aerodynamics of the oblique wing and remains stable during control saturation caused by large command inputs or large external disturbances. The technique controls each natural mode independently allowing single-input/single-output techniques to be applied to multiple-input/multiple-output systems.
Random Predictor Models for Rigorous Uncertainty Quantification: Part 2
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.
2015-01-01
This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.
Random Predictor Models for Rigorous Uncertainty Quantification: Part 1
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.
2015-01-01
This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nishimura, Takahiro, E-mail: t-nishimura@ist.osaka-u.ac.jp; Fujii, Ryo; Ogura, Yusuke
Molecular logic circuits represent a promising technology for observation and manipulation of biological systems at the molecular level. However, the implementation of molecular logic circuits for temporal and programmable operation remains challenging. In this paper, we demonstrate an optically controllable logic circuit that uses fluorescence resonance energy transfer (FRET) for signaling. The FRET-based signaling process is modulated by both molecular and optical inputs. Based on the distance dependence of FRET, the FRET pathways required to execute molecular logic operations are formed on a DNA nanostructure as a circuit based on its molecular inputs. In addition, the FRET pathways on themore » DNA nanostructure are controlled optically, using photoswitching fluorescent molecules to instruct the execution of the desired operation and the related timings. The behavior of the circuit can thus be controlled using external optical signals. As an example, a molecular logic circuit capable of executing two different logic operations was studied. The circuit contains functional DNAs and a DNA scaffold to construct two FRET routes for executing Input 1 AND Input 2 and Input 1 AND NOT Input 3 operations on molecular inputs. The circuit produced the correct outputs with all possible combinations of the inputs by following the light signals. Moreover, the operation execution timings were controlled based on light irradiation and the circuit responded to time-dependent inputs. The experimental results demonstrate that the circuit changes the output for the required operations following the input of temporal light signals.« less
Self-tuning multivariable pole placement control of a multizone crystal growth furnace
NASA Technical Reports Server (NTRS)
Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.
1992-01-01
This paper presents the design and implementation of a multivariable self-tuning temperature controller for the control of lead bromide crystal growth. The crystal grows inside a multizone transparent furnace. There are eight interacting heating zones shaping the axial temperature distribution inside the furnace. A multi-input, multi-output furnace model is identified on-line by a recursive least squares estimation algorithm. A multivariable pole placement controller based on this model is derived and implemented. Comparison between single-input, single-output and multi-input, multi-output self-tuning controllers demonstrates that the zone-to-zone interactions can be minimized better by a multi-input, multi-output controller design. This directly affects the quality of crystal grown.
Radac, Mircea-Bogdan; Precup, Radu-Emil; Petriu, Emil M
2015-11-01
This paper proposes a novel model-free trajectory tracking of multiple-input multiple-output (MIMO) systems by the combination of iterative learning control (ILC) and primitives. The optimal trajectory tracking solution is obtained in terms of previously learned solutions to simple tasks called primitives. The library of primitives that are stored in memory consists of pairs of reference input/controlled output signals. The reference input primitives are optimized in a model-free ILC framework without using knowledge of the controlled process. The guaranteed convergence of the learning scheme is built upon a model-free virtual reference feedback tuning design of the feedback decoupling controller. Each new complex trajectory to be tracked is decomposed into the output primitives regarded as basis functions. The optimal reference input for the control system to track the desired trajectory is next recomposed from the reference input primitives. This is advantageous because the optimal reference input is computed straightforward without the need to learn from repeated executions of the tracking task. In addition, the optimization problem specific to trajectory tracking of square MIMO systems is decomposed in a set of optimization problems assigned to each separate single-input single-output control channel that ensures a convenient model-free decoupling. The new model-free primitive-based ILC approach is capable of planning, reasoning, and learning. A case study dealing with the model-free control tuning for a nonlinear aerodynamic system is included to validate the new approach. The experimental results are given.
The Geochemical Record of Cultural Eutrophication and Remediation Efforts in Three Connecticut Lakes
NASA Astrophysics Data System (ADS)
Ku, T.; Bourne, H. L.; Tirtajana, S.; Nahar, M.; Kading, T.
2009-12-01
Cultural eutrophication is the process whereby human activity increases the amount of nutrients, primarily nitrogen and phosphorous, entering an aquatic ecosystem causing excessive biological growth. To reverse or decelerate cultural eutrophication, many regulatory agencies have implemented stringent laws intended to lower the flux of nutrients into impacted water bodies or have emplaced internal remediation systems designed to decrease primary productivity. To quantify the effects of cultural eutrophication and remediation efforts, we examined sedimentary histories of three eutrophic Connecticut lakes that record the transition from pre-anthropogenic conditions into eutrophication and through recent remediation. The three Connecticut lakes (Lake Waramaug, Beseck Lake, and Amos Lake) represent a range of remediation activities. Since 1983, Lake Waramaug has been the focus of significant remediation efforts including the installation of three hypolimnetic withdrawal / layer aeration systems, zoning regulations to limit runoff, and the stocking and seeding of fish and zooplankton. Beseck Lake has experienced episodic eutrophic conditions, in part due to failing septic systems, and in 2001, 433 residences were converted from septic systems to a city sewer system. Amos Lake serves as a cultural eutrophication end member as it has not has received any major remediation. Multiple freeze and gravity cores were collected from 2005-2008. Radiocarbon, Pb-210, Cs-137, Hg, and Pb measurements determined sediment ages. Organic C accumulation rates, C/N ratios, organic matter delta-15N, bulk sediment Fe and Al concentrations, and P speciation (labile, iron-bound, aluminum-bound, organic, and total) determined sediment and nutrient sources and accumulations. Dithionite-extractable iron, pyrite S, and pyrite delta-34S provided insight into changes in P-Fe-S cycling. The sediment cores represent the last few hundreds of years of lake history and, importantly, some Lake Waramaug freeze cores preserved the sediments deposited after remediation efforts began. European settlement beginning in the 1700s caused an increase in total P and organic C sedimentation rates, a decrease in C/N, an increase in delta-15N, and an increase in allochthonous aluminosilicate sedimentation. The increase in delta-15N since the 1700s was caused the influx of high delta-15N sources such as agricultural fertilizers. In some Lake Waramaug cores, delta-15N has decreased in the last few decades, likely in response to new zoning laws, and demonstrates that remediation efforts have successfully altered nutrient inputs into the lake. Increased nutrient and aluminosilicate inputs during the 1800 and 1900s caused the dominant sediment P reservoir to shift from organic-P to Fe- or Al- bound P. In some cases, Fe-bound P decreased when pyrite S concentrations increased and d34S values decreased, suggesting that increased atmospheric sulfur inputs and subsequent pyritization has decreased the iron available to bind phosphorus. This work expands our knowledge of recovering aquatic systems and shows that recent sediment records may be used to measure the success of remediation strategies.
State, Parameter, and Unknown Input Estimation Problems in Active Automotive Safety Applications
NASA Astrophysics Data System (ADS)
Phanomchoeng, Gridsada
A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is presented. The developed theory is used to estimate vertical tire forces and predict tripped rollovers in situations involving road bumps, potholes, and lateral unknown force inputs. To estimate the tire-road friction coefficients at each individual tire of the vehicle, algorithms to estimate longitudinal forces and slip ratios at each tire are proposed. Subsequently, tire-road friction coefficients are obtained using recursive least squares parameter estimators that exploit the relationship between longitudinal force and slip ratio at each tire. The developed approaches are evaluated through simulations with industry standard software, CARSIM, with experimental tests on a Volvo XC90 sport utility vehicle and with experimental tests on a 1/8th scaled vehicle. The simulation and experimental results show that the developed approaches can reliably estimate the vehicle parameters and state variables needed for effective ESC and rollover prevention applications.
Input filter compensation for switching regulators
NASA Technical Reports Server (NTRS)
Lee, F. C.
1984-01-01
Problems caused by input filter interaction and conventional input filter design techniques are discussed. The concept of feedforward control is modeled with an input filter and a buck regulator. Experimental measurement and comparison to the analytical predictions is carried out. Transient response and the use of a feedforward loop to stabilize the regulator system is described. Other possible applications for feedforward control are included.
NASA Astrophysics Data System (ADS)
Keller, J. Y.; Chabir, K.; Sauter, D.
2016-03-01
State estimation of stochastic discrete-time linear systems subject to unknown inputs or constant biases has been widely studied but no work has been dedicated to the case where a disturbance switches between unknown input and constant bias. We show that such disturbance can affect a networked control system subject to deception attacks and data losses on the control signals transmitted by the controller to the plant. This paper proposes to estimate the switching disturbance from an augmented state version of the intermittent unknown input Kalman filter recently developed by the authors. Sufficient stochastic stability conditions are established when the arrival binary sequence of data losses follows a Bernoulli random process.
How much control is enough? Influence of unreliable input on user experience.
van de Laar, Bram; Plass-Oude Bos, Danny; Reuderink, Boris; Poel, Mannes; Nijholt, Anton
2013-12-01
Brain–computer interfaces (BCI) provide a valuable new input modality within human–computer interaction systems. However, like other body-based inputs such as gesture or gaze based systems, the system recognition of input commands is still far from perfect. This raises important questions, such as what level of control should such an interface be able to provide. What is the relationship between actual and perceived control? And in the case of applications for entertainment in which fun is an important part of user experience, should we even aim for the highest level of control, or is the optimum elsewhere? In this paper, we evaluate whether we can modulate the amount of control and if a game can be fun with less than perfect control. In the experiment users (n = 158) played a simple game in which a hamster has to be guided to the exit of a maze. The amount of control the user has over the hamster is varied. The variation of control through confusion matrices makes it possible to simulate the experience of using a BCI, while using the traditional keyboard for input. After each session the user completed a short questionnaire on user experience and perceived control. Analysis of the data showed that the perceived control of the user could largely be explained by the amount of control in the respective session. As expected, user frustration decreases with increasing control. Moreover, the results indicate that the relation between fun and control is not linear. Although at lower levels of control fun does increase with improved control, the level of fun drops just before perfect control is reached (with an optimum around 96%). This poses new insights for developers of games who want to incorporate some form of BCI or other modality with unreliable input in their game: for creating a fun game, unreliable input can be used to create a challenge for the user.
NASA Astrophysics Data System (ADS)
Tryfonidis, Michail
It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that visuomotor learning is important not only for error correction through internal model adaptation on ground or in microgravity, but also for the minimization of the total mean-square error in the presence of random variability. Thus human intelligent decision displays certain attributes that seem to conform to Bayesian statistical games. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
A Proteomic View at the Biochemistry of Syntrophic Butyrate Oxidation in Syntrophomonas wolfei
Schmidt, Alexander; Müller, Nicolai; Schink, Bernhard; Schleheck, David
2013-01-01
In syntrophic conversion of butyrate to methane and CO2, butyrate is oxidized to acetate by secondary fermenting bacteria such as Syntrophomonas wolfei in close cooperation with methanogenic partner organisms, e.g., Methanospirillum hungatei. This process involves an energetically unfavourable shift of electrons from the level of butyryl-CoA oxidation to the substantially lower redox potential of proton and/or CO2 reduction, in order to transfer these electrons to the methanogenic partner via hydrogen and/or formate. In the present study, all prominent membrane-bound and soluble proteins expressed in S. wolfei specifically during syntrophic growth with butyrate, in comparison to pure-culture growth with crotonate, were examined by one- and two-dimensional gel electrophoresis, and identified by peptide fingerprinting-mass spectrometry. A membrane-bound, externally oriented, quinone-linked formate dehydrogenase complex was expressed at high level specifically during syntrophic butyrate oxidation, comprising a selenocystein-linked catalytic subunit with a membrane-translocation pathway signal (TAT), a membrane-bound iron-sulfur subunit, and a membrane-bound cytochrome. Soluble hydrogenases were expressed at high levels specifically during growth with crotonate. The results were confirmed by native protein gel electrophoresis, by formate dehydrogenase and hydrogenase-activity staining, and by analysis of formate dehydrogenase and hydrogenase activities in intact cells and cell extracts. Furthermore, constitutive expression of a membrane-bound, internally oriented iron-sulfur oxidoreductase (DUF224) was confirmed, together with expression of soluble electron-transfer flavoproteins (EtfAB) and two previously identified butyryl-CoA dehydrogenases. Our findings allow to depict an electron flow scheme for syntrophic butyrate oxidation in S. wolfei. Electrons derived from butyryl-CoA are transferred through a membrane-bound EtfAB:quinone oxidoreductase (DUF224) to a menaquinone cycle and further via a b-type cytochrome to an externally oriented formate dehydrogenase. Hence, an ATP hydrolysis-driven proton-motive force across the cytoplasmatic membrane would provide the energy input for the electron potential shift necessary for formate formation. PMID:23468890
Isotopic evidence for nitrogen mobility in peat bogs
NASA Astrophysics Data System (ADS)
Novak, Martin; Stepanova, Marketa; Jackova, Ivana; Vile, Melanie A.; Wieder, R. Kelman; Buzek, Frantisek; Adamova, Marie; Erbanova, Lucie; Fottova, Daniela; Komarek, Arnost
2014-05-01
Elevated nitrogen (N) input may reduce carbon (C) storage in peat. Under low atmospheric deposition, most N is bound in the moss layer. Under high N inputs, Sphagnum is not able to prevent penetration of dissolved N to deeper peat. Nitrogen may become available to the roots of invading vascular plants. The concurrent oxygenation of deeper peat layers, along with higher supply of labile organic C, may enhance microbial decomposition and lead to peat thinning. The resulting higher emissions of greenhouse gases may accelerate global warming. Seepage of N to deeper peat has never been quantified. Here we present evidence for post-depositional mobility of atmogenic N in peat, based on natural-abundance N isotope ratios. We conducted a reciprocal peat transplant experiment between two Sphagnum-dominated peat bogs in the Czech Republic (Central Europe), differing in anthropogenic N inputs. The northern site VJ received as much as 33 kg N ha-1 yr-1 via spruce canopy throughfall. The southern site was less polluted (17.6 kg N ha-1 yr-1). Isotope signatures of living moss differed between the two sites (δ15N of -3‰ and -7‰ at VJ and CB, respectively). After 18 months, an isotope mass balance was constructed. In the CB-to-VJ transplant, a significant portion of original CB nitrogen (98-31%) was removed and replaced by nitrogen of the host site throughout the top 10 cm of the profile. Nitrogen, deposited at VJ, was immobilized in imported CB peat that was up to 20 years old. Additionally, we compared N concentration and N accumulation rates in 210Pb-dated peat profiles with well-constrained data on historical atmospheric N pollution. Nationwide N emissions peaked in 1990, while VJ exhibited the highest N content in peat that formed in 1930. This de-coupling of N inputs and N retention in peat might be interpreted as a result of translocation of dissolved pollutant N downcore, corroborating our δ15N results at VJ and CB. Data from a variety of peat bogs along pollution and climatic gradients would be needed to test to what extent the record of atmospheric N inputs in peat is overprinted by variable, locally-controlled decomposition rates.
Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model
Papasavvas, Christoforos A.; Wang, Yujiang; Trevelyan, Andrew J.; Kaiser, Marcus
2016-01-01
Experimental results suggest that there are two distinct mechanisms of inhibition in cortical neuronal networks: subtractive and divisive inhibition. They modulate the input-output function of their target neurons either by increasing the input that is needed to reach maximum output or by reducing the gain and the value of maximum output itself, respectively. However, the role of these mechanisms on the dynamics of the network is poorly understood. We introduce a novel population model and numerically investigate the influence of divisive inhibition on network dynamics. Specifically, we focus on the transitions from a state of regular oscillations to a state of chaotic dynamics via period-doubling bifurcations. The model with divisive inhibition exhibits a universal transition rate to chaos (Feigenbaum behavior). In contrast, in an equivalent model without divisive inhibition, transition rates to chaos are not bounded by the universal constant (non-Feigenbaum behavior). This non-Feigenbaum behavior, when only subtractive inhibition is present, is linked to the interaction of bifurcation curves in the parameter space. Indeed, searching the parameter space showed that such interactions are impossible when divisive inhibition is included. Therefore, divisive inhibition prevents non-Feigenbaum behavior and, consequently, any abrupt transition to chaos. The results suggest that the divisive inhibition in neuronal networks could play a crucial role in keeping the states of order and chaos well separated and in preventing the onset of pathological neural dynamics. PMID:26465514
Accessory replicative helicases and the replication of protein-bound DNA.
Brüning, Jan-Gert; Howard, Jamieson L; McGlynn, Peter
2014-12-12
Complete, accurate duplication of the genetic material is a prerequisite for successful cell division. Achieving this accuracy is challenging since there are many barriers to replication forks that may cause failure to complete genome duplication or result in possibly catastrophic corruption of the genetic code. One of the most important types of replicative barriers are proteins bound to the template DNA, especially transcription complexes. Removal of these barriers demands energy input not only to separate the DNA strands but also to disrupt multiple bonds between the protein and DNA. Replicative helicases that unwind the template DNA for polymerases at the fork can displace proteins bound to the template. However, even occasional failures in protein displacement by the replicative helicase could spell disaster. In such circumstances, failure to restart replication could result in incomplete genome duplication. Avoiding incomplete genome duplication via the repair and restart of blocked replication forks also challenges viability since the involvement of recombination enzymes is associated with the risk of genome rearrangements. Organisms have therefore evolved accessory replicative helicases that aid replication fork movement along protein-bound DNA. These helicases reduce the dangers associated with replication blockage by protein-DNA complexes, aiding clearance of blocks and resumption of replication by the same replisome thus circumventing the need for replication repair and restart. This review summarises recent work in bacteria and eukaryotes that has begun to delineate features of accessory replicative helicases and their importance in genome stability. Copyright © 2014. Published by Elsevier Ltd.
Amortized entanglement of a quantum channel and approximately teleportation-simulable channels
NASA Astrophysics Data System (ADS)
Kaur, Eneet; Wilde, Mark M.
2018-01-01
This paper defines the amortized entanglement of a quantum channel as the largest difference in entanglement between the output and the input of the channel, where entanglement is quantified by an arbitrary entanglement measure. We prove that the amortized entanglement of a channel obeys several desirable properties, and we also consider special cases such as the amortized relative entropy of entanglement and the amortized Rains relative entropy. These latter quantities are shown to be single-letter upper bounds on the secret-key-agreement and PPT-assisted quantum capacities of a quantum channel, respectively. Of especial interest is a uniform continuity bound for these latter two special cases of amortized entanglement, in which the deviation between the amortized entanglement of two channels is bounded from above by a simple function of the diamond norm of their difference and the output dimension of the channels. We then define approximately teleportation- and positive-partial-transpose-simulable (PPT-simulable) channels as those that are close in diamond norm to a channel which is either exactly teleportation- or PPT-simulable, respectively. These results then lead to single-letter upper bounds on the secret-key-agreement and PPT-assisted quantum capacities of channels that are approximately teleportation- or PPT-simulable, respectively. Finally, we generalize many of the concepts in the paper to the setting of general resource theories, defining the amortized resourcefulness of a channel and the notion of ν-freely-simulable channels, connecting these concepts in an operational way as well.
Structured Uncertainty Bound Determination From Data for Control and Performance Validation
NASA Technical Reports Server (NTRS)
Lim, Kyong B.
2003-01-01
This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems.
NASA Astrophysics Data System (ADS)
Eleiwi, Fadi; Laleg-Kirati, Taous Meriem
2018-06-01
An observer-based perturbation extremum seeking control is proposed for a direct-contact membrane distillation (DCMD) process. The process is described with a dynamic model that is based on a 2D advection-diffusion equation model which has pump flow rates as process inputs. The objective of the controller is to optimise the trade-off between the permeate mass flux and the energy consumption by the pumps inside the process. Cases of single and multiple control inputs are considered through the use of only the feed pump flow rate or both the feed and the permeate pump flow rates. A nonlinear Lyapunov-based observer is designed to provide an estimation for the temperature distribution all over the designated domain of the DCMD process. Moreover, control inputs are constrained with an anti-windup technique to be within feasible and physical ranges. Performance of the proposed structure is analysed, and simulations based on real DCMD process parameters for each control input are provided.
Control design for robust stability in linear regulators: Application to aerospace flight control
NASA Technical Reports Server (NTRS)
Yedavalli, R. K.
1986-01-01
Time domain stability robustness analysis and design for linear multivariable uncertain systems with bounded uncertainties is the central theme of the research. After reviewing the recently developed upper bounds on the linear elemental (structured), time varying perturbation of an asymptotically stable linear time invariant regulator, it is shown that it is possible to further improve these bounds by employing state transformations. Then introducing a quantitative measure called the stability robustness index, a state feedback conrol design algorithm is presented for a general linear regulator problem and then specialized to the case of modal systems as well as matched systems. The extension of the algorithm to stochastic systems with Kalman filter as the state estimator is presented. Finally an algorithm for robust dynamic compensator design is presented using Parameter Optimization (PO) procedure. Applications in a aircraft control and flexible structure control are presented along with a comparison with other existing methods.
Method and apparatus for automatic control of a humanoid robot
NASA Technical Reports Server (NTRS)
Abdallah, Muhammad E (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)
2013-01-01
A robotic system includes a humanoid robot having a plurality of joints adapted for force control with respect to an object acted upon by the robot, a graphical user interface (GUI) for receiving an input signal from a user, and a controller. The GUI provides the user with intuitive programming access to the controller. The controller controls the joints using an impedance-based control framework, which provides object level, end-effector level, and/or joint space-level control of the robot in response to the input signal. A method for controlling the robotic system includes receiving the input signal via the GUI, e.g., a desired force, and then processing the input signal using a host machine to control the joints via an impedance-based control framework. The framework provides object level, end-effector level, and/or joint space-level control of the robot, and allows for functional-based GUI to simplify implementation of a myriad of operating modes.
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.
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
NASA Astrophysics Data System (ADS)
Pitcavage, E.; Furman, T.; Nelson, W. R.
2017-12-01
The East African Rift System (EARS) is earth's largest continental divergent boundary and an unparalleled natural laboratory for understanding magmatism related to successful continental rifting. Classic views of continental rifting suggest that faulting and extension are facilitated by ascending magmas that weaken the lithosphere thermally and structurally within basin-bounding accommodation zones. In the EARS Western Rift (WR), many volcanic fields are not aligned along rift-bounding faults, and magma compositions lack evidence for asthenospheric inputs expected along lithosphere-penetrating fault systems. We note that compositional input from the Cenozoic Afar mantle plume is not recognized convincingly in WR mafic alkaline lavas1. Rather, magma compositions demonstrate significant input from anciently metasomatized sub-continental lithospheric mantle (SCLM). Destabilization and foundering of metasomatized SCLM has an increasingly recognized role in continental magmatism worldwide, producing volatile-rich, alkaline volcanics when drips of foundered SCLM devolatilize and melt on descent. This magmatism can lead to faulting: the lithospheric thinning that results from this process may play a role in physical aspects of rifting, contrasting with faulting facilitated by asthenospheric melts. Geochemical and geophysical evidence indicates that drip magmatism has occurred in several EARS provinces, including Turkana, Chyulu Hills, and in Afar2 where it is geographically coincident with successful rifting. We present bulk geochemical data that suggest drip melting of metasomatized SCLM is occurring in several WR volcanic fields. We focus on Bufumbira (Uganda), where mafic lavas are derived from garnet+phlogopite+amphibole+zircon-bearing pyroxenite, indicating a deep metasomatized SCLM source. Isotopic and trace element data suggest that extent of melting increased with depth of melting, a signature of lithospheric drip. We propose that drip magmatism is an important driver of volcanism in the early history of these igneous provinces and may be fundamentally related to the onset of successful rifting. 1. Graham, D. et al. Goldschmidt Conference Abstracts (2011). 2. Furman, T., et al. Geochim. Cosmochim. Acta 185, 418-434 (2016).
Automated determination of arterial input function for DCE-MRI of the prostate
NASA Astrophysics Data System (ADS)
Zhu, Yingxuan; Chang, Ming-Ching; Gupta, Sandeep
2011-03-01
Prostate cancer is one of the commonest cancers in the world. Dynamic contrast enhanced MRI (DCE-MRI) provides an opportunity for non-invasive diagnosis, staging, and treatment monitoring. Quantitative analysis of DCE-MRI relies on determination of an accurate arterial input function (AIF). Although several methods for automated AIF detection have been proposed in literature, none are optimized for use in prostate DCE-MRI, which is particularly challenging due to large spatial signal inhomogeneity. In this paper, we propose a fully automated method for determining the AIF from prostate DCE-MRI. Our method is based on modeling pixel uptake curves as gamma variate functions (GVF). First, we analytically compute bounds on GVF parameters for more robust fitting. Next, we approximate a GVF for each pixel based on local time domain information, and eliminate the pixels with false estimated AIFs using the deduced upper and lower bounds. This makes the algorithm robust to signal inhomogeneity. After that, according to spatial information such as similarity and distance between pixels, we formulate the global AIF selection as an energy minimization problem and solve it using a message passing algorithm to further rule out the weak pixels and optimize the detected AIF. Our method is fully automated without training or a priori setting of parameters. Experimental results on clinical data have shown that our method obtained promising detection accuracy (all detected pixels inside major arteries), and a very good match with expert traced manual AIF.
An error bound for a discrete reduced order model of a linear multivariable system
NASA Technical Reports Server (NTRS)
Al-Saggaf, Ubaid M.; Franklin, Gene F.
1987-01-01
The design of feasible controllers for high dimension multivariable systems can be greatly aided by a method of model reduction. In order for the design based on the order reduction to include a guarantee of stability, it is sufficient to have a bound on the model error. Previous work has provided such a bound for continuous-time systems for algorithms based on balancing. In this note an L-infinity bound is derived for model error for a method of order reduction of discrete linear multivariable systems based on balancing.
Heebner, John E [Livermore, CA
2010-08-03
In one general embodiment, a method for ultrafast optical signal detecting is provided. In operation, a first optical input signal is propagated through a first wave guiding layer of a waveguide. Additionally, a second optical input signal is propagated through a second wave guiding layer of the waveguide. Furthermore, an optical control signal is applied to a top of the waveguide, the optical control signal being oriented diagonally relative to the top of the waveguide such that the application is used to influence at least a portion of the first optical input signal propagating through the first wave guiding layer of the waveguide. In addition, the first and the second optical input signals output from the waveguide are combined. Further, the combined optical signals output from the waveguide are detected. In another general embodiment, a system for ultrafast optical signal recording is provided comprising a waveguide including a plurality of wave guiding layers, an optical control source positioned to propagate an optical control signal towards the waveguide in a diagonal orientation relative to a top of the waveguide, at least one optical input source positioned to input an optical input signal into at least a first and a second wave guiding layer of the waveguide, and a detector for detecting at least one interference pattern output from the waveguide, where at least one of the interference patterns results from a combination of the optical input signals input into the first and the second wave guiding layer. Furthermore, propagation of the optical control signal is used to influence at least a portion of the optical input signal propagating through the first wave guiding layer of the waveguide.
The SISMA Project: A pre-operative seismic hazard monitoring system.
NASA Astrophysics Data System (ADS)
Massimiliano Chersich, M. C.; Amodio, A. A. Angelo; Francia, A. F. Andrea; Sparpaglione, C. S. Claudio
2009-04-01
Galileian Plus is currently leading the development, in collaboration with several Italian Universities, of the SISMA (Seismic Information System for Monitoring and Alert) Pilot Project financed by the Italian Space Agency. The system is devoted to the continuous monitoring of the seismic risk and is addressed to support the Italian Civil Protection decisional process. Completion of the Pilot Project is planned at the beginning of 2010. Main scientific paradigm of SISMA is an innovative deterministic approach integrating geophysical models, geodesy and active tectonics. This paper will give a general overview of project along with its progress status and a particular focus will be put on the architectural design details and to the software implementation choices. SISMA is built on top of a software infrastructure developed by Galileian Plus to integrate the scientific programs devoted to the update of seismic risk maps. The main characteristics of the system may be resumed as follow: automatic download of input data; integration of scientific programs; definition and scheduling of chains of processes; monitoring and control of the system through a graphical user interface (GUI); compatibility of the products with ESRI ArcGIS, by mean of post-processing conversion. a) automatic download of input data SISMA needs input data such as GNSS observations, updated seismic catalogue, SAR satellites orbits, etc. that are periodically updated and made available from remote servers through FTP and HTTP. This task is accomplished by a dedicated user configurable component. b) integration of scientific programs SISMA integrates many scientific programs written in different languages (Fortran, C, C++, Perl and Bash) and running into different operating systems. This design requirements lead to the development of a distributed system which is platform independent and is able to run any terminal-based program following few simple predefined rules. c) definition and scheduling of chains of processes Processes are bound each other, in the sense that the output of process "A" should be passed as input to process "B". In this case the process "B" must run automatically as soon as the required input is ready. In SISMA this issue is handled with the "data-driven" activation concept allowing specifying that a process should be started as soon as the needed input datum has been made available in the archive. Moreover SISMA may run processes on a "time-driven" base. The infrastructure of SISMA provides a configurable scheduler allowing the user to define the start time and the periodicity of such processes. d) monitoring and control The operator of the system needs to monitor and control every process running in the system. The SISMA infrastructure allows, through its GUI, the user to: view log messages of running and old processes; stop running processes; monitor processes executions; monitor resource status (available ram, network reachability, and available disk space) for every machine in the system. e) compatibility with ESRI Shapefiles Nearly all the SISMA data has some geographic information, and it is useful to integrate it in a Geographic Information System (GIS). Processors output are georeferred, but they are generated as ASCII files in a proprietary format, and thus cannot directly loaded in a GIS. The infrastructures provides a simple framework for adding filters that reads the data in the proprietary format and converts it to ESRI Shapefile format.
Model and Data Reduction for Control, Identification and Compressed Sensing
NASA Astrophysics Data System (ADS)
Kramer, Boris
This dissertation focuses on problems in design, optimization and control of complex, large-scale dynamical systems from different viewpoints. The goal is to develop new algorithms and methods, that solve real problems more efficiently, together with providing mathematical insight into the success of those methods. There are three main contributions in this dissertation. In Chapter 3, we provide a new method to solve large-scale algebraic Riccati equations, which arise in optimal control, filtering and model reduction. We present a projection based algorithm utilizing proper orthogonal decomposition, which is demonstrated to produce highly accurate solutions at low rank. The method is parallelizable, easy to implement for practitioners, and is a first step towards a matrix free approach to solve AREs. Numerical examples for n ≥ 106 unknowns are presented. In Chapter 4, we develop a system identification method which is motivated by tangential interpolation. This addresses the challenge of fitting linear time invariant systems to input-output responses of complex dynamics, where the number of inputs and outputs is relatively large. The method reduces the computational burden imposed by a full singular value decomposition, by carefully choosing directions on which to project the impulse response prior to assembly of the Hankel matrix. The identification and model reduction step follows from the eigensystem realization algorithm. We present three numerical examples, a mass spring damper system, a heat transfer problem, and a fluid dynamics system. We obtain error bounds and stability results for this method. Chapter 5 deals with control and observation design for parameter dependent dynamical systems. We address this by using local parametric reduced order models, which can be used online. Data available from simulations of the system at various configurations (parameters, boundary conditions) is used to extract a sparse basis to represent the dynamics (via dynamic mode decomposition). Subsequently, a new, compressed sensing based classification algorithm is developed which incorporates the extracted dynamic information into the sensing basis. We show that this augmented classification basis makes the method more robust to noise, and results in superior identification of the correct parameter. Numerical examples consist of a Navier-Stokes, as well as a Boussinesq flow application.
Kuan, Shu-Chien; Chen, Kuei-Min; Wang, Chi
2012-04-01
Institutional wheelchair-bound older adults often do not get regular exercise and are prone to health problems. The aim of this study was to test the effects of a 12-week qigong exercise program on the physiological and psychological health of wheelchair-bound older adults in long-term care facilities. Study design was quasi-experimental, pre-post test, nonequivalent control group. Participants comprised a convenience sample of 72 wheelchair-bound older adults (qigong = 34; control = 38). The qigong group exercised 35 min/day, 5 days/week for 12 weeks. Measures for physical health (blood pressure, heart rate variability, and distal skin temperature) and psychological health (Brief Symptom Rating Scale-5) were collected before and during study Weeks 4, 8, and 12. The qigong group participants' blood pressure, distal skin temperature, and psychological health were significantly improved (all p < .001). These findings suggest that qigong exercise is a suitable daily activity for elderly residents in long-term care facilities and may help in the control of blood pressure among older adults.
Spatial light modulators for full cross-connections in optical networks
NASA Technical Reports Server (NTRS)
Juday, Richard D. (Inventor)
2004-01-01
A polarization-independent optical switch is disclosed for switching at least one incoming beam from at least one input source to at least one output drain. The switch includes a polarizing beam splitter to split each of the at least one incoming beam into a first input beam and a second input beam, wherein the first input beam and the second input beams are independently polarized; a wave plate optically coupled to the second input beam for converting the polarization of the second input beam to an appropriately polarized second input beam; a beam combiner optically coupled to the first input beam and the modified second input beam, wherein the beam combiner accepts the first input beam and the modified second input beam to produce a combined beam; the combined beam is invariant to the polarization state of the input source's polarization; and a controllable spatial light modulator optically coupled to the combined beam, wherein the combined beam is diffracted by the controllable spatial light modulator to place light at a plurality of output locations.
Master control data handling program uses automatic data input
NASA Technical Reports Server (NTRS)
Alliston, W.; Daniel, J.
1967-01-01
General purpose digital computer program is applicable for use with analysis programs that require basic data and calculated parameters as input. It is designed to automate input data preparation for flight control computer programs, but it is general enough to permit application in other areas.
Coherent perfect absorption in a quantum nonlinear regime of cavity quantum electrodynamics
NASA Astrophysics Data System (ADS)
Wei, Yang-hua; Gu, Wen-ju; Yang, Guoqing; Zhu, Yifu; Li, Gao-xiang
2018-05-01
Coherent perfect absorption (CPA) is investigated in the quantum nonlinear regime of cavity quantum electrodynamics (CQED), in which a single two-level atom couples to a single-mode cavity weakly driven by two identical laser fields. In the strong-coupling regime and due to the photon blockade effect, the weakly driven CQED system can be described as a quantum system with three polariton states. CPA is achieved at a critical input field strength when the frequency of the input fields matches the polariton transition frequency. In the quantum nonlinear regime, the incoherent dissipation processes such as atomic and photon decays place a lower bound for the purity of the intracavity quantum field. Our results show that under the CPA condition, the intracavity field always exhibits the quadrature squeezing property manifested by the quantum nonlinearity, and the outgoing photon flux displays the super-Poissonian distribution.
Underwater wireless optical MIMO system with spatial modulation and adaptive power allocation
NASA Astrophysics Data System (ADS)
Huang, Aiping; Tao, Linwei; Niu, Yilong
2018-04-01
In this paper, we investigate the performance of underwater wireless optical multiple-input multiple-output communication system combining spatial modulation (SM-UOMIMO) with flag dual amplitude pulse position modulation (FDAPPM). Channel impulse response for coastal and harbor ocean water links are obtained by Monte Carlo (MC) simulation. Moreover, we obtain the closed-form and upper bound average bit error rate (BER) expressions for receiver diversity including optical combining, equal gain combining and selected combining. And a novel adaptive power allocation algorithm (PAA) is proposed to minimize the average BER of SM-UOMIMO system. Our numeric results indicate an excellent match between the analytical results and numerical simulations, which confirms the accuracy of our derived expressions. Furthermore, the results show that adaptive PAA outperforms conventional fixed factor PAA and equal PAA obviously. Multiple-input single-output system with adaptive PAA obtains even better BER performance than MIMO one, at the same time reducing receiver complexity effectively.
The behavior of quantization spectra as a function of signal-to-noise ratio
NASA Technical Reports Server (NTRS)
Flanagan, M. J.
1991-01-01
An expression for the spectrum of quantization error in a discrete-time system whose input is a sinusoid plus white Gaussian noise is derived. This quantization spectrum consists of two components: a white-noise floor and spurious harmonics. The dithering effect of the input Gaussian noise in both components of the spectrum is considered. Quantitative results in a discrete Fourier transform (DFT) example show the behavior of spurious harmonics as a function of the signal-to-noise ratio (SNR). These results have strong implications for digital reception and signal analysis systems. At low SNRs, spurious harmonics decay exponentially on a log-log scale, and the resulting spectrum is white. As the SNR increases, the spurious harmonics figure prominently in the output spectrum. A useful expression is given that roughly bounds the magnitude of a spurious harmonic as a function of the SNR.
Onset of η-nuclear binding in a pionless EFT approach
NASA Astrophysics Data System (ADS)
Barnea, N.; Bazak, B.; Friedman, E.; Gal, A.
2017-08-01
ηNNN and ηNNNN bound states are explored in stochastic variational method (SVM) calculations within a pionless effective field theory (EFT) approach at leading order. The theoretical input consists of regulated NN and NNN contact terms, and a regulated energy dependent ηN contact term derived from coupled-channel models of the N* (1535) nucleon resonance. A self consistency procedure is applied to deal with the energy dependence of the ηN subthreshold input, resulting in a weak dependence of the calculated η-nuclear binding energies on the EFT regulator. It is found, in terms of the ηN scattering length aηN, that the onset of binding η 3He requires a minimal value of ReaηN close to 1 fm, yielding then a few MeV η binding in η 4He. The onset of binding η 4He requires a lower value of ReaηN, but exceeding 0.7 fm.
Compositional Solution Space Quantification for Probabilistic Software Analysis
NASA Technical Reports Server (NTRS)
Borges, Mateus; Pasareanu, Corina S.; Filieri, Antonio; d'Amorim, Marcelo; Visser, Willem
2014-01-01
Probabilistic software analysis aims at quantifying how likely a target event is to occur during program execution. Current approaches rely on symbolic execution to identify the conditions to reach the target event and try to quantify the fraction of the input domain satisfying these conditions. Precise quantification is usually limited to linear constraints, while only approximate solutions can be provided in general through statistical approaches. However, statistical approaches may fail to converge to an acceptable accuracy within a reasonable time. We present a compositional statistical approach for the efficient quantification of solution spaces for arbitrarily complex constraints over bounded floating-point domains. The approach leverages interval constraint propagation to improve the accuracy of the estimation by focusing the sampling on the regions of the input domain containing the sought solutions. Preliminary experiments show significant improvement on previous approaches both in results accuracy and analysis time.
Bolometer Results in the Long-Microwave-Heated WEGA Stellarator
NASA Astrophysics Data System (ADS)
Zhang, D.; Otte, M.; Giannone, L.
2006-01-01
A 12 channel bolometer camera based on a gold foil absorber has been installed on the WEGA stellarator to measure the radiation power losses of the plasma. The measured total radiation power is typically less than 30% of the ECRH input power. However, this radiated power fraction depends on the ECRH input power, the magnetic configuration and the field strength as well as the working gas. For separatrix-bounded configurations, core-peaked radiation intensity profiles are usually detected, while in a limiter-configuration they are flatter, broader and more asymmetric. In addition, significant radiation originating from the SOL region is measured for all the cases studied. The SOL radiation changes with changing the plasma-wave interaction region, indicating a strong correlation between radiation and power deposition. Under the WEGA-plasma conditions (Te<10 eV), it is considered that the radiation profile reflects the plasma pressure associated with the power deposition distribution of the ECRH.
Non-steady state diagenesis of organic and inorganic sulfur in lake sediments
NASA Astrophysics Data System (ADS)
Couture, Raoul-Marie; Fischer, Rachele; Van Cappellen, Philippe; Gobeil, Charles
2016-12-01
Sulfur controls the fate of many geochemical elements in lake sediments, including iron, phosphorus and environmentally important trace elements. We measured the speciation of pore-water and sediment-bound sulfur (aqueous sulfate and sulfides, elemental sulfur, iron monosulfide, pyrite, organic sulfur) and supporting geochemical variables (carbon, oxygen, iron) in the sediments of a perennially oxygenated and a seasonally anoxic basin of an oligotrophic lake in Québec, using a combination of pore-water analyses, sequential extractions and X-ray absorption near edge structure. A non-steady state early diagenetic model was developed and calibrated against this extensive dataset to help unravel the pathways and quantify the rates of S transformations. Results suggest that the main source of S to the sediments is the settling of organic ester-sulfate (R-O-SO3-H). Hydrolysis of these compounds provides an additional source of sulfate for anaerobic microbial oxidation of sedimentary organic matter, releasing sulfide to the pore-water. Reduced solid-bound S species accumulate as thiols (R-SH) and iron sulfides in the perennially oxygenated and seasonally anoxic basin, respectively. The model-estimated rate constant for R-SH formation is lower than previously estimated for this particular lacustrine site, but similar to that proposed for marine shelf sediments. The solid sediment S profiles, however, carry the imprint of the time-dependent sulfate input to the lake. Iron sulfide enrichments formed during past decades of elevated atmospheric SO4 deposition are presently dissolving. In the sediments of the perennially oxygenated basin this reaction hampers the build-up of Fe(III) (oxy)hydroxide near the sediment-water interface.
New multirate sampled-data control law structure and synthesis algorithm
NASA Technical Reports Server (NTRS)
Berg, Martin C.; Mason, Gregory S.; Yang, Gen-Sheng
1992-01-01
A new multirate sampled-data control law structure is defined and a new parameter-optimization-based synthesis algorithm for that structure is introduced. The synthesis algorithm can be applied to multirate, multiple-input/multiple-output, sampled-data control laws having a prescribed dynamic order and structure, and a priori specified sampling/update rates for all sensors, processor states, and control inputs. The synthesis algorithm is applied to design two-input, two-output tip position controllers of various dynamic orders for a sixth-order, two-link robot arm model.
Hybrid zero-voltage switching (ZVS) control for power inverters
Amirahmadi, Ahmadreza; Hu, Haibing; Batarseh, Issa
2016-11-01
A power inverter combination includes a half-bridge power inverter including first and second semiconductor power switches receiving input power having an intermediate node therebetween providing an inductor current through an inductor. A controller includes input comparison circuitry receiving the inductor current having outputs coupled to first inputs of pulse width modulation (PWM) generation circuitry, and a predictive control block having an output coupled to second inputs of the PWM generation circuitry. The predictive control block is coupled to receive a measure of Vin and an output voltage at a grid connection point. A memory stores a current control algorithm configured for resetting a PWM period for a switching signal applied to control nodes of the first and second power switch whenever the inductor current reaches a predetermined upper limit or a predetermined lower limit.
Input design for identification of aircraft stability and control derivatives
NASA Technical Reports Server (NTRS)
Gupta, N. K.; Hall, W. E., Jr.
1975-01-01
An approach for designing inputs to identify stability and control derivatives from flight test data is presented. This approach is based on finding inputs which provide the maximum possible accuracy of derivative estimates. Two techniques of input specification are implemented for this objective - a time domain technique and a frequency domain technique. The time domain technique gives the control input time history and can be used for any allowable duration of test maneuver, including those where data lengths can only be of short duration. The frequency domain technique specifies the input frequency spectrum, and is best applied for tests where extended data lengths, much longer than the time constants of the modes of interest, are possible. These technqiues are used to design inputs to identify parameters in longitudinal and lateral linear models of conventional aircraft. The constraints of aircraft response limits, such as on structural loads, are realized indirectly through a total energy constraint on the input. Tests with simulated data and theoretical predictions show that the new approaches give input signals which can provide more accurate parameter estimates than can conventional inputs of the same total energy. Results obtained indicate that the approach has been brought to the point where it should be used on flight tests for further evaluation.
NASA Technical Reports Server (NTRS)
Griffin, Brian Joseph; Burken, John J.; Xargay, Enric
2010-01-01
This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1995-01-01
Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for open loop parameter identification purposes, specifically for optimal input design validation at 5 degrees angle of attack, identification of individual strake effectiveness at 40 and 50 degrees angle of attack, and study of lateral dynamics and lateral control effectiveness at 40 and 50 degrees angle of attack. Each maneuver is to be realized by applying square wave inputs to specific control effectors using the On-Board Excitation System (OBES). Maneuver descriptions and complete specifications of the time/amplitude points define each input are included, along with plots of the input time histories.
L∞-gain adaptive fuzzy fault accommodation control design for nonlinear time-delay systems.
Wu, Huai-Ning; Qiang, Xiao-Hong; Guo, Lei
2011-06-01
In this paper, an adaptive fuzzy fault accommodation (FA) control design with a guaranteed L(∞)-gain performance is developed for a class of nonlinear time-delay systems with persistent bounded disturbances. Using the Lyapunov technique and the Razumikhin-type lemma, the existence condition of the L(∞) -gain adaptive fuzzy FA controllers is provided in terms of linear matrix inequalities (LMIs). In the proposed FA scheme, a fuzzy logic system is employed to approximate the unknown term in the derivative of the Lyapunov function due to the unknown fault function; a continuous-state feedback control strategy is adopted for the control design to avoid the undesirable chattering phenomenon. The resulting FA controllers can ensure that every response of the closed-loop system is uniformly ultimately bounded with a guaranteed L(∞)-gain performance in the presence of a fault. Moreover, by the existing LMI optimization technique, a suboptimal controller is obtained in the sense of minimizing an upper bound of the L(∞)-gain. Finally, the achieved simulation results on the FA control of a continuous stirred tank reactor (CSTR) show the effectiveness of the proposed design procedure.
2013-04-22
Following for Unmanned Aerial Vehicles Using L1 Adaptive Augmentation of Commercial Autopilots, Journal of Guidance, Control, and Dynamics, (3 2010): 0...Naira Hovakimyan. L1 Adaptive Controller for MIMO system with Unmatched Uncertainties using Modi?ed Piecewise Constant Adaptation Law, IEEE 51st...adaptive input nominal input with Nominal input L1 ‐based control generator This L1 adaptive control architecture uses data from the reference model
Real Time Trajectory Planning for Groups of Unmanned Vehicles
2005-08-22
positions of the robots, and a third set determines the local relations of the neighboring robots. They have used a nonholonomic kinematic model for the...Note that the vehicles are not physically coupled in any way. A feedback control law for control inputs F.2 and T2 miust be determined to control... Vb12 71 = 01 + 01 2 - 02 The goal is finding a control law for the two inputs [F2 , T2] to stabilize the outputs. Therefore, the input-output equations
Robison, G.H. et al.
1960-11-15
An electronic system is described for indicating the occurrence of a plurality of electrically detectable events within predetermined time intervals. It is comprised of separate input means electrically associated with the events under observation: an electronic channel associated with each input means including control means and indicating means; timing means associated with each of the input means and the control means and adapted to derive a signal from the input means and apply it after a predetermined time to the control means to effect deactivation of each of the channels; and means for resetting the system to its initial condition after observation of each group of events.
Reservoir Models for Gas Hydrate Numerical Simulation
NASA Astrophysics Data System (ADS)
Boswell, R.
2016-12-01
Scientific and industrial drilling programs have now providing detailed information on gas hydrate systems that will increasingly be the subject of field experiments. The need to carefully plan these programs requires reliable prediction of reservoir response to hydrate dissociation. Currently, a major emphasis in gas hydrate modeling is the integration of thermodynamic/hydrologic phenomena with geomechanical response for both reservoir and bounding strata. However, also critical to the ultimate success of these efforts is the appropriate development of input geologic models, including several emerging issues, including (1) reservoir heterogeneity, (2) understanding of the initial petrophysical characteristics of the system (reservoirs and seals), the dynamic evolution of those characteristics during active dissociation, and the interdependency of petrophysical parameters and (3) the nature of reservoir boundaries. Heterogeneity is ubiquitous aspect of every natural reservoir, and appropriate characterization is vital. However, heterogeneity is not random. Vertical variation can be evaluated with core and well log data; however, core data often are challenged by incomplete recovery. Well logs also provide interpretation challenges, particularly where reservoirs are thinly-bedded due to limitation in vertical resolution. This imprecision will extend to any petrophysical measurements that are derived from evaluation of log data. Extrapolation of log data laterally is also complex, and should be supported by geologic mapping. Key petrophysical parameters include porosity, permeability and it many aspects, and water saturation. Field data collected to date suggest that the degree of hydrate saturation is strongly controlled by/dependant upon reservoir quality and that the ratio of free to bound water in the remaining pore space is likely also controlled by reservoir quality. Further, those parameters will also evolve during dissociation, and not necessary in a simple/linear way. Significant progress has also occurred in recent years with regard to the geologic characterization of reservoir boundaries. Vertical boundaries with overlying clay-rich "seals" are now widely-appreciated to have non-zero permeability, and lateral boundaries are sources of potential lateral fluid flow.
Approximation theory for LQG (Linear-Quadratic-Gaussian) optimal control of flexible structures
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Adamian, A.
1988-01-01
An approximation theory is presented for the LQG (Linear-Quadratic-Gaussian) optimal control problem for flexible structures whose distributed models have bounded input and output operators. The main purpose of the theory is to guide the design of finite dimensional compensators that approximate closely the optimal compensator. The optimal LQG problem separates into an optimal linear-quadratic regulator problem and an optimal state estimation problem. The solution of the former problem lies in the solution to an infinite dimensional Riccati operator equation. The approximation scheme approximates the infinite dimensional LQG problem with a sequence of finite dimensional LQG problems defined for a sequence of finite dimensional, usually finite element or modal, approximations of the distributed model of the structure. Two Riccati matrix equations determine the solution to each approximating problem. The finite dimensional equations for numerical approximation are developed, including formulas for converting matrix control and estimator gains to their functional representation to allow comparison of gains based on different orders of approximation. Convergence of the approximating control and estimator gains and of the corresponding finite dimensional compensators is studied. Also, convergence and stability of the closed-loop systems produced with the finite dimensional compensators are discussed. The convergence theory is based on the convergence of the solutions of the finite dimensional Riccati equations to the solutions of the infinite dimensional Riccati equations. A numerical example with a flexible beam, a rotating rigid body, and a lumped mass is given.
Compensation for electrical converter nonlinearities
Perisic, Milun; Ransom, Ray M; Kajouke, Lateef A
2013-11-19
Systems and methods are provided for delivering energy from an input interface to an output interface. An electrical system includes an input interface, an output interface, an energy conversion module between the input interface and the output interface, an inductive element between the input interface and the energy conversion module, and a control module. The control module determines a compensated duty cycle control value for operating the energy conversion module to produce a desired voltage at the output interface and operates the energy conversion module to deliver energy to the output interface with a duty cycle that is influenced by the compensated duty cycle control value. The compensated duty cycle control value is influenced by the current through the inductive element and accounts for voltage across the switching elements of the energy conversion module.
Intelligent and robust optimization frameworks for smart grids
NASA Astrophysics Data System (ADS)
Dhansri, Naren Reddy
A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.
A grid spacing control technique for algebraic grid generation methods
NASA Technical Reports Server (NTRS)
Smith, R. E.; Kudlinski, R. A.; Everton, E. L.
1982-01-01
A technique which controls the spacing of grid points in algebraically defined coordinate transformations is described. The technique is based on the generation of control functions which map a uniformly distributed computational grid onto parametric variables defining the physical grid. The control functions are smoothed cubic splines. Sets of control points are input for each coordinate directions to outline the control functions. Smoothed cubic spline functions are then generated to approximate the input data. The technique works best in an interactive graphics environment where control inputs and grid displays are nearly instantaneous. The technique is illustrated with the two-boundary grid generation algorithm.
Relations between work and entropy production for general information-driven, finite-state engines
NASA Astrophysics Data System (ADS)
Merhav, Neri
2017-02-01
We consider a system model of a general finite-state machine (ratchet) that simultaneously interacts with three kinds of reservoirs: a heat reservoir, a work reservoir, and an information reservoir, the latter being taken to be a running digital tape whose symbols interact sequentially with the machine. As has been shown in earlier work, this finite-state machine can act as a demon (with memory), which creates a net flow of energy from the heat reservoir into the work reservoir (thus extracting useful work) at the price of increasing the entropy of the information reservoir. Under very few assumptions, we propose a simple derivation of a family of inequalities that relate the work extraction with the entropy production. These inequalities can be seen as either upper bounds on the extractable work or as lower bounds on the entropy production, depending on the point of view. Many of these bounds are relatively easy to calculate and they are tight in the sense that equality can be approached arbitrarily closely. In their basic forms, these inequalities are applicable to any finite number of cycles (and not only asymptotically), and for a general input information sequence (possibly correlated), which is not necessarily assumed even stationary. Several known results are obtained as special cases.
Quantum state tomography and fidelity estimation via Phaselift
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Yiping; Liu, Huan; Zhao, Qing, E-mail: qzhaoyuping@bit.edu.cn
Experiments of multi-photon entanglement have been performed by several groups. Obviously, an increase on the photon number for fidelity estimation and quantum state tomography causes a dramatic increase in the elements of the positive operator valued measures (POVMs), which results in a great consumption of time in measurements. In practice, we wish to obtain a good estimation of fidelity and quantum states through as few measurements as possible for multi-photon entanglement. Phaselift provides such a chance to estimate fidelity for entangling states based on less data. In this paper, we would like to show how the Phaselift works for sixmore » qubits in comparison to the data given by Pan’s group, i.e., we use a fraction of the data as input to estimate the rest of the data through the obtained density matrix, and thus goes beyond the simple fidelity analysis. The fidelity bound is also provided for general Schrödinger Cat state. Based on the fidelity bound, we propose an optimal measurement approach which could both reduce the copies and keep the fidelity bound gap small. The results demonstrate that the Phaselift can help decrease the measured elements of POVMs for six qubits. Our conclusion is based on the prior knowledge that a pure state is the target state prepared by experiments.« less
NASA Astrophysics Data System (ADS)
Boski, Marcin; Paszke, Wojciech
2017-01-01
This paper deals with designing of iterative learning control schemes for uncertain systems with static nonlinearities. More specifically, the nonlinear part is supposed to be sector bounded and system matrices are assumed to range in the polytope of matrices. For systems with such nonlinearities and uncertainties the repetitive process setting is exploited to develop a linear matrix inequality based conditions for computing the feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure convergence of the trial-to-trial error dynamics, respectively. Numerical examples illustrate the theoretical results and confirm effectiveness of the designed control scheme.
Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.
Liu, Yong-Hua; Huang, Liangpei; Xiao, Dongming; Guo, Yong
2015-09-01
In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pisenti, N.; Gaebler, C. P. E.; Lynn, T. W.
Measuring an entangled state of two particles is crucial to many quantum communication protocols. Yet Bell-state distinguishability using a finite apparatus obeying linear evolution and local measurement is theoretically limited. We extend known bounds for Bell-state distinguishability in one and two variables to the general case of entanglement in n two-state variables. We show that at most 2{sup n+1}-1 classes out of 4{sup n} hyper-Bell states can be distinguished with one copy of the input state. With two copies, complete distinguishability is possible. We present optimal schemes in each case.
Robust autoassociative memory with coupled networks of Kuramoto-type oscillators
NASA Astrophysics Data System (ADS)
Heger, Daniel; Krischer, Katharina
2016-08-01
Uncertain recognition success, unfavorable scaling of connection complexity, or dependence on complex external input impair the usefulness of current oscillatory neural networks for pattern recognition or restrict technical realizations to small networks. We propose a network architecture of coupled oscillators for pattern recognition which shows none of the mentioned flaws. Furthermore we illustrate the recognition process with simulation results and analyze the dynamics analytically: Possible output patterns are isolated attractors of the system. Additionally, simple criteria for recognition success are derived from a lower bound on the basins of attraction.
Qutrit witness from the Grothendieck constant of order four
NASA Astrophysics Data System (ADS)
Diviánszky, Péter; Bene, Erika; Vértesi, Tamás
2017-07-01
In this paper, we prove that KG(3 )
Some conservative estimates in quantum cryptography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Molotkov, S. N.
2006-08-15
Relationship is established between the security of the BB84 quantum key distribution protocol and the forward and converse coding theorems for quantum communication channels. The upper bound Q{sub c} {approx} 11% on the bit error rate compatible with secure key distribution is determined by solving the transcendental equation H(Q{sub c})=C-bar({rho})/2, where {rho} is the density matrix of the input ensemble, C-bar({rho}) is the classical capacity of a noiseless quantum channel, and H(Q) is the capacity of a classical binary symmetric channel with error rate Q.
Distance bounded energy detecting ultra-wideband impulse radio secure protocol.
Hedin, Daniel S; Kollmann, Daniel T; Gibson, Paul L; Riehle, Timothy H; Seifert, Gregory J
2014-01-01
We present a demonstration of a novel protocol for secure transmissions on a Ultra-wideband impulse radio that includes distance bounding. Distance bounding requires radios to be within a certain radius to communicate. This new protocol can be used in body area networks for medical devices where security is imperative. Many current wireless medical devices were not designed with security as a priority including devices that can be life threatening if controlled by a hacker. This protocol provides multiple levels of security including encryption and a distance bounding test to prevent long distance attacks.
TRIAC/SCR proportional control circuit
Hughes, Wallace J.
1999-01-01
A power controller device which uses a voltage-to-frequency converter in conjunction with a zero crossing detector to linearly and proportionally control AC power being supplied to a load. The output of the voltage-to frequency converter controls the "reset" input of a R-S flip flop, while an "0" crossing detector controls the "set" input. The output of the flip flop triggers a monostable multivibrator controlling the SCR or TRIAC firing circuit connected to the load. Logic gates prevent the direct triggering of the multivibrator in the rare instance where the "reset" and "set" inputs of the flip flop are in coincidence. The control circuit can be supplemented with a control loop, providing compensation for line voltage variations.
Divide and control: split design of multi-input DNA logic gates.
Gerasimova, Yulia V; Kolpashchikov, Dmitry M
2015-01-18
Logic gates made of DNA have received significant attention as biocompatible building blocks for molecular circuits. The majority of DNA logic gates, however, are controlled by the minimum number of inputs: one, two or three. Here we report a strategy to design a multi-input logic gate by splitting a DNA construct.
40 CFR 96.142 - CAIR NOX allowance allocations.
Code of Federal Regulations, 2010 CFR
2010-07-01
... the 3 highest amounts of the unit's adjusted control period heat input for 2000 through 2004, with the adjusted control period heat input for each year calculated as follows: (A) If the unit is coal-fired... CAIR NOX Allowance Allocations § 96.142 CAIR NOX allowance allocations. (a)(1) The baseline heat input...
Lv, Yueyong; Hu, Qinglei; Ma, Guangfu; Zhou, Jiakang
2011-10-01
This paper treats the problem of synchronized control of spacecraft formation flying (SFF) in the presence of input constraint and parameter uncertainties. More specifically, backstepping based robust control is first developed for the total 6 DOF dynamic model of SFF with parameter uncertainties, in which the model consists of relative translation and attitude rotation. Then this controller is redesigned to deal with the input constraint problem by incorporating a command filter such that the generated control could be implementable even under physical or operating constraints on the control input. The convergence of the proposed control algorithms is proved by the Lyapunov stability theorem. Compared with conventional methods, illustrative simulations of spacecraft formation flying are conducted to verify the effectiveness of the proposed approach to achieve the spacecraft track the desired attitude and position trajectories in a synchronized fashion even in the presence of uncertainties, external disturbances and control saturation constraint. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
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.
NASA Technical Reports Server (NTRS)
Perri, Todd A.; Mckillip, R. M., Jr.; Curtiss, H. C., Jr.
1987-01-01
The development and methodology is presented for development of full-authority implicit model-following and explicit model-following optimal controllers for use on helicopters operating in the Nap-of-the Earth (NOE) environment. Pole placement, input-output frequency response, and step input response were used to evaluate handling qualities performance. The pilot was equipped with velocity-command inputs. A mathematical/computational trajectory optimization method was employed to evaluate the ability of each controller to fly NOE maneuvers. The method determines the optimal swashplate and thruster input histories from the helicopter's dynamics and the prescribed geometry and desired flying qualities of the maneuver. Three maneuvers were investigated for both the implicit and explicit controllers with and without auxiliary propulsion installed: pop-up/dash/descent, bob-up at 40 knots, and glideslope. The explicit controller proved to be superior to the implicit controller in performance and ease of design.
Transfer Function Control for Biometric Monitoring System
NASA Technical Reports Server (NTRS)
Chmiel, Alan J. (Inventor); Grodinsky, Carlos M. (Inventor); Humphreys, Bradley T. (Inventor)
2015-01-01
A modular apparatus for acquiring biometric data may include circuitry operative to receive an input signal indicative of a biometric condition, the circuitry being configured to process the input signal according to a transfer function thereof and to provide a corresponding processed input signal. A controller is configured to provide at least one control signal to the circuitry to programmatically modify the transfer function of the modular system to facilitate acquisition of the biometric data.
Global a priori estimates for the inhomogeneous Landau equation with moderately soft potentials
NASA Astrophysics Data System (ADS)
Cameron, Stephen; Silvestre, Luis; Snelson, Stanley
2018-05-01
We establish a priori upper bounds for solutions to the spatially inhomogeneous Landau equation in the case of moderately soft potentials, with arbitrary initial data, under the assumption that mass, energy and entropy densities stay under control. Our pointwise estimates decay polynomially in the velocity variable. We also show that if the initial data satisfies a Gaussian upper bound, this bound is propagated for all positive times.
A linear programming approach to characterizing norm bounded uncertainty from experimental data
NASA Technical Reports Server (NTRS)
Scheid, R. E.; Bayard, D. S.; Yam, Y.
1991-01-01
The linear programming spectral overbounding and factorization (LPSOF) algorithm, an algorithm for finding a minimum phase transfer function of specified order whose magnitude tightly overbounds a specified nonparametric function of frequency, is introduced. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).
Modeling Enclosure Design in Above-Grade Walls
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lstiburek, J.; Ueno, K.; Musunuru, S.
2016-03-01
This report describes the modeling of typical wall assemblies that have performed well historically in various climate zones. The WUFI (Warme und Feuchte instationar) software (Version 5.3) model was used. A library of input data and results are provided. The provided information can be generalized for application to a broad population of houses, within the limits of existing experience. The WUFI software model was calibrated or tuned using wall assemblies with historically successful performance. The primary performance criteria or failure criteria establishing historic performance was moisture content of the exterior sheathing. The primary tuning parameters (simulation inputs) were airflow andmore » specifying appropriate material properties. Rational hygric loads were established based on experience - specifically rain wetting and interior moisture (RH levels). The tuning parameters were limited or bounded by published data or experience. The WUFI templates provided with this report supply useful information resources to new or less-experienced users. The files present various custom settings that will help avoid results that will require overly conservative enclosure assemblies. Overall, better material data, consistent initial assumptions, and consistent inputs among practitioners will improve the quality of WUFI modeling, and improve the level of sophistication in the field.« less
Unified quantum no-go theorems and transforming of quantum pure states in a restricted set
NASA Astrophysics Data System (ADS)
Luo, Ming-Xing; Li, Hui-Ran; Lai, Hong; Wang, Xiaojun
2017-12-01
The linear superposition principle in quantum mechanics is essential for several no-go theorems such as the no-cloning theorem, the no-deleting theorem and the no-superposing theorem. In this paper, we investigate general quantum transformations forbidden or permitted by the superposition principle for various goals. First, we prove a no-encoding theorem that forbids linearly superposing of an unknown pure state and a fixed pure state in Hilbert space of a finite dimension. The new theorem is further extended for multiple copies of an unknown state as input states. These generalized results of the no-encoding theorem include the no-cloning theorem, the no-deleting theorem and the no-superposing theorem as special cases. Second, we provide a unified scheme for presenting perfect and imperfect quantum tasks (cloning and deleting) in a one-shot manner. This scheme may lead to fruitful results that are completely characterized with the linear independence of the representative vectors of input pure states. The upper bounds of the efficiency are also proved. Third, we generalize a recent superposing scheme of unknown states with a fixed overlap into new schemes when multiple copies of an unknown state are as input states.
Extremum seeking with bounded update rates
Scheinker, Alexander; Krstić, Miroslav
2013-11-16
In this work, we present a form of extremum seeking (ES) in which the unknown function being minimized enters the system’s dynamics as the argument of a cosine or sine term, thereby guaranteeing known bounds on update rates and control efforts. We present general n-dimensional optimization and stabilization results as well as 2D vehicle control, with bounded velocity and control efforts. For application to autonomous vehicles, tracking a source in a GPS denied environment with unknown orientation, this ES approach allows for smooth heading angle actuation, with constant velocity, and in application to a unicycle-type vehicle results in control abilitymore » as if the vehicle is fully actuated. Our stability analysis is made possible by the classic results of Kurzweil, Jarnik, Sussmann, and Liu, regarding systems with highly oscillatory terms. In our stability analysis, we combine the averaging results with a semi-global practical stability result under small parametric perturbations developed by Moreau and Aeyels.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
2012-10-03
Contains class for connecting to the Xbox 360 controller, displaying the user inputs {buttons, triggers, analog sticks), and controlling the rumble motors. Also contains classes for converting the raw Xbox 360 controller inputs into meaningful commands for the following objects: Robot arms - Provides joint control and several tool control schemes UGV's - Provides translational and rotational commands for "skid-steer" vehicles Pan-tilt units - Provides several modes of control including velocity, position, and point-tracking Head-mounted displays (HMO)- Controls the viewpoint of a HMO Umbra frames - Controls the position andorientation of an Umbra posrot objectmore » Umbra graphics window - Provides several modes of control for the Umbra OSG window viewpoint including free-fly, cursor-focused, and object following.« less
Control Board Digital Interface Input Devices – Touchscreen, Trackpad, or Mouse?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thomas A. Ulrich; Ronald L. Boring; Roger Lew
The authors collaborated with a power utility to evaluate input devices for use in the human system interface (HSI) for a new digital Turbine Control System (TCS) at a nuclear power plant (NPP) undergoing a TCS upgrade. A standalone dynamic software simulation of the new digital TCS and a mobile kiosk were developed to conduct an input device study to evaluate operator preference and input device effectiveness. The TCS software presented the anticipated HSI for the TCS and mimicked (i.e., simulated) the turbine systems’ responses to operator commands. Twenty-four licensed operators from the two nuclear power units participated in themore » study. Three input devices were tested: a trackpad, mouse, and touchscreen. The subjective feedback from the survey indicates the operators preferred the touchscreen interface. The operators subjectively rated the touchscreen as the fastest and most comfortable input device given the range of tasks they performed during the study, but also noted a lack of accuracy for selecting small targets. The empirical data suggest the mouse input device provides the most consistent performance for screen navigation and manipulating on screen controls. The trackpad input device was both empirically and subjectively found to be the least effective and least desired input device.« less
Free, esterified and residual bound sterols in Black Sea Unit I sediments
NASA Astrophysics Data System (ADS)
de Leeuw, J. W.; Rijpstra, W. Irene C.; Schenck, P. A.; Volkman, J. K.
1983-03-01
Detailed compositional data for the sterols isolated from a surface, Unit I, sediment from the Black Sea are reported. A procedure based on digitonin precipitation has been used to separate the more abundant free sterols from those occurring in esterified forms. Saponification of the solvent extracted sediment residue liberated only a small quantity of residual bound sterols in contrast to studies of other sediments. 4-Methylsterols are much more abundant than 4-desmethylsterols in both the free and esterified sterol fractions which we attribute to a major dinoflagellate input, as in deeper Unit II sediment. The desmethylsterol fraction appears to derive from a variety of sources including dinoflagellates, coccolithophores, diatoms, terrigenous detritus and perhaps invertebrates. 5α(H)-Stanols are particularly abundant in the free sterol fraction. An analysis of the stanol/stenol ratios suggests that the 4-desmethyl-5α(H)-stanols are the result of specific microbial reductions of Δ 5-sterols and/or the reflection of a contribution of stanol containing source organisms.
Capacity planning of a wide-sense nonblocking generalized survivable network
NASA Astrophysics Data System (ADS)
Ho, Kwok Shing; Cheung, Kwok Wai
2006-06-01
Generalized survivable networks (GSNs) have two interesting properties that are essential attributes for future backbone networks--full survivability against link failures and support for dynamic traffic demands. GSNs incorporate the nonblocking network concept into the survivable network models. Given a set of nodes and a topology that is at least two-edge connected, a certain minimum capacity is required for each edge to form a GSN. The edge capacity is bounded because each node has an input-output capacity limit that serves as a constraint for any allowable traffic demand matrix. The GSN capacity planning problem is nondeterministic polynomial time (NP) hard. We first give a rigorous mathematical framework; then we offer two different solution approaches. The two-phase approach is fast, but the joint optimization approach yields a better bound. We carried out numerical computations for eight networks with different topologies and found that the cost of a GSN is only a fraction (from 52% to 89%) more than that of a static survivable network.
The Spacing of Strongly Meandering Jets in Quasigeostrophic Turbulence
NASA Astrophysics Data System (ADS)
Scott, R.
2017-12-01
Based on an assumption of inhomogeneous potential vorticity mixing,estimates are obtained for kinetic and potential energies inquasigeostrophic β -plane turbulence with strongly meanderingjets and in the limit of small Rossby deformation length. Theestimates provide, inter alia, a means to predict the jetspacing based on knowledge of either the kinetic or potential energy,which, in situations where the flow is forced with a uniform totalenergy input, are known a priori in the case of frictional orthermal damping, respectively. The estimates are lower bounds for thejet spacing, achieved in the limit of perfect mixing between regularlyspaced jets with simple meanders. These lower bounds are sharp in astrict mathematical sense but are likely to substantiallyunderestimate jet spacing in actual flows, which exhibit a remarkablediversity of structures and irregularities. The latter areillustrated numerically in direct integrations of the forced system.A convenient description of the forced system is presented in terms ofa number of independent length scales of the problem, anddimensionless ratios of these.
NASA Astrophysics Data System (ADS)
Abdullah, Dahlan; Suwilo, Saib; Tulus; Mawengkang, Herman; Efendi, Syahril
2017-09-01
The higher education system in Indonesia can be considered not only as an important source of developing knowledge in the country, but also could create positive living conditions for the country. Therefore it is not surprising that enrollments in higher education continue to expand. However, the implication of this situation, the Indonesian government is necessarily to support more funds. In the interest of accountability, it is essential to measure the efficiency for this higher institution. Data envelopment analysis (DEA) is a method to evaluate the technical efficiency of production units which have multiple input and output. The higher learning institution considered in this paper is Malikussaleh University located in Lhokseumawe, a city in Aceh province of Indonesia. This paper develops a method to evaluate efficiency for all departments in Malikussaleh University using DEA with bounded output. Accordingly, we present some important differences in efficiency of those departments. Finally we discuss the effort should be done by these departments in order to become efficient.
Maximum likelihood decoding of Reed Solomon Codes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sudan, M.
We present a randomized algorithm which takes as input n distinct points ((x{sub i}, y{sub i})){sup n}{sub i=1} from F x F (where F is a field) and integer parameters t and d and returns a list of all univariate polynomials f over F in the variable x of degree at most d which agree with the given set of points in at least t places (i.e., y{sub i} = f (x{sub i}) for at least t values of i), provided t = {Omega}({radical}nd). The running time is bounded by a polynomial in n. This immediately provides a maximum likelihoodmore » decoding algorithm for Reed Solomon Codes, which works in a setting with a larger number of errors than any previously known algorithm. To the best of our knowledge, this is the first efficient (i.e., polynomial time bounded) algorithm which provides some maximum likelihood decoding for any efficient (i.e., constant or even polynomial rate) code.« less
Variable strategy model of the human operator
NASA Astrophysics Data System (ADS)
Phillips, John Michael
Human operators often employ discontinuous or "bang-bang" control strategies when performing large-amplitude acquisition tasks. The current study applies Variable Structure Control (VSC) techniques to model human operator behavior during acquisition tasks. The result is a coupled, multi-input model replicating the discontinuous control strategy. In the VSC formulation, a switching surface is the mathematical representation of the operator's control strategy. The performance of the Variable Strategy Model (VSM) is evaluated by considering several examples, including the longitudinal control of an aircraft during the visual landing task. The aircraft landing task becomes an acquisition maneuver whenever large initial offsets occur. Several different strategies are explored in the VSM formulation for the aircraft landing task. First, a switching surface is constructed from literal interpretations of pilot training literature. This approach yields a mathematical representation of how a pilot is trained to fly a generic aircraft. This switching surface is shown to bound the trajectory response of a group of pilots performing an offset landing task in an aircraft simulator study. Next, front-side and back-side landing strategies are compared. A back-side landing strategy is found to be capable of landing an aircraft flying on either the front side or back side of the power curve. However, the front-side landing strategy is found to be insufficient for landing an aircraft flying on the back side. Finally, a more refined landing strategy is developed that takes into the account the specific aircraft's dynamic characteristics. The refined strategy is translated back into terminology similar to the existing pilot training literature.
Robust Control of Uncertain Systems via Dissipative LQG-Type Controllers
NASA Technical Reports Server (NTRS)
Joshi, Suresh M.
2000-01-01
Optimal controller design is addressed for a class of linear, time-invariant systems which are dissipative with respect to a quadratic power function. The system matrices are assumed to be affine functions of uncertain parameters confined to a convex polytopic region in the parameter space. For such systems, a method is developed for designing a controller which is dissipative with respect to a given power function, and is simultaneously optimal in the linear-quadratic-Gaussian (LQG) sense. The resulting controller provides robust stability as well as optimal performance. Three important special cases, namely, passive, norm-bounded, and sector-bounded controllers, which are also LQG-optimal, are presented. The results give new methods for robust controller design in the presence of parametric uncertainties.
De Kumar, Bony; Parker, Hugo J.; Paulson, Ariel; Parrish, Mark E.; Pushel, Irina; Singh, Narendra Pratap; Zhang, Ying; Slaughter, Brian D.; Unruh, Jay R.; Florens, Laurence; Zeitlinger, Julia; Krumlauf, Robb
2017-01-01
Hoxa1 has diverse functional roles in differentiation and development. We identify and characterize properties of regions bound by HOXA1 on a genome-wide basis in differentiating mouse ES cells. HOXA1-bound regions are enriched for clusters of consensus binding motifs for HOX, PBX, and MEIS, and many display co-occupancy of PBX and MEIS. PBX and MEIS are members of the TALE family and genome-wide analysis of multiple TALE members (PBX, MEIS, TGIF, PREP1, and PREP2) shows that nearly all HOXA1 targets display occupancy of one or more TALE members. The combinatorial binding patterns of TALE proteins define distinct classes of HOXA1 targets, which may create functional diversity. Transgenic reporter assays in zebrafish confirm enhancer activities for many HOXA1-bound regions and the importance of HOX-PBX and TGIF motifs for their regulation. Proteomic analyses show that HOXA1 physically interacts on chromatin with PBX, MEIS, and PREP family members, but not with TGIF, suggesting that TGIF may have an independent input into HOXA1-bound regions. Therefore, TALE proteins appear to represent a wide repertoire of HOX cofactors, which may coregulate enhancers through distinct mechanisms. We also discover extensive auto- and cross-regulatory interactions among the Hoxa1 and TALE genes, indicating that the specificity of HOXA1 during development may be regulated though a complex cross-regulatory network of HOXA1 and TALE proteins. This study provides new insight into a regulatory network involving combinatorial interactions between HOXA1 and TALE proteins. PMID:28784834
Propulsion/flight control integration technology (PROFIT) software system definition
NASA Technical Reports Server (NTRS)
Carlin, C. M.; Hastings, W. J.
1978-01-01
The Propulsion Flight Control Integration Technology (PROFIT) program is designed to develop a flying testbed dedicated to controls research. The control software for PROFIT is defined. Maximum flexibility, needed for long term use of the flight facility, is achieved through a modular design. The Host program, processes inputs from the telemetry uplink, aircraft central computer, cockpit computer control and plant sensors to form an input data base for use by the control algorithms. The control algorithms, programmed as application modules, process the input data to generate an output data base. The Host program formats the data for output to the telemetry downlink, the cockpit computer control, and the control effectors. Two applications modules are defined - the bill of materials F-100 engine control and the bill of materials F-15 inlet control.
Noise screen for attitude control system
NASA Technical Reports Server (NTRS)
Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Hong, David P. (Inventor); Hirschberg, Philip C. (Inventor)
2002-01-01
An attitude control system comprising a controller and a noise screen device coupled to the controller. The controller is adapted to control an attitude of a vehicle carrying an actuator system that is adapted to pulse in metered bursts in order to generate a control torque to control the attitude of the vehicle in response to a control pulse. The noise screen device is adapted to generate a noise screen signal in response to the control pulse that is generated when an input attitude error signal exceeds a predetermined deadband attitude level. The noise screen signal comprises a decaying offset signal that when combined with the attitude error input signal results in a net attitude error input signal away from the predetermined deadband level to reduce further control pulse generation.
NASA Astrophysics Data System (ADS)
Kojima, Hirohisa; Ieda, Shoko; Kasai, Shinya
2014-08-01
Underactuated control problems, such as the control of a space robot without actuators on the main body, have been widely investigated. However, few studies have examined attitude control problems of underactuated space robots equipped with a flexible appendage, such as solar panels. In order to suppress vibration in flexible appendages, a zero-vibration input-shaping technique was applied to the link motion of an underactuated planar space robot. However, because the vibrational frequency depends on the link angles, simple input-shaping control methods cannot sufficiently suppress the vibration. In this paper, the dependency of the vibrational frequency on the link angles is measured experimentally, and the time-delay interval of the input shaper is then tuned based on the frequency estimated from the link angles. The proposed control method is referred to as frequency-tuning input-shaped manifold-based switching control (frequency-tuning IS-MBSC). The experimental results reveal that frequency-tuning IS-MBSC is capable of controlling the link angles and the main body attitude to maintain the target angles and that the vibration suppression performance of the proposed frequency-tuning IS-MBSC is better than that of a non-tuning IS-MBSC, which does not take the frequency variation into consideration.
NASA Astrophysics Data System (ADS)
Sun, Jingliang; Liu, Chunsheng
2018-01-01
In this paper, the problem of intercepting a manoeuvring target within a fixed final time is posed in a non-linear constrained zero-sum differential game framework. The Nash equilibrium solution is found by solving the finite-horizon constrained differential game problem via adaptive dynamic programming technique. Besides, a suitable non-quadratic functional is utilised to encode the control constraints into a differential game problem. The single critic network with constant weights and time-varying activation functions is constructed to approximate the solution of associated time-varying Hamilton-Jacobi-Isaacs equation online. To properly satisfy the terminal constraint, an additional error term is incorporated in a novel weight-updating law such that the terminal constraint error is also minimised over time. By utilising Lyapunov's direct method, the closed-loop differential game system and the estimation weight error of the critic network are proved to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated by using a simple non-linear system and a non-linear missile-target interception system, assuming first-order dynamics for the interceptor and target.
Development of DBD plasma actuators: The double encapsulated electrode
NASA Astrophysics Data System (ADS)
Erfani, Rasool; Zare-Behtash, Hossein; Hale, Craig; Kontis, Konstantinos
2015-04-01
Plasma actuators are electrical devices that generate a wall bounded jet without the use of any moving parts. For aerodynamic applications they can be used as flow control devices to delay separation and augment lift on a wing. The standard plasma actuator consists of a single encapsulated (ground) electrode. The aim of this project is to investigate the effect of varying the number and distribution of encapsulated electrodes in the dielectric layer. Utilising a transformer cascade, a variety of input voltages are studied for their effect. In the quiescent environment of a Faraday cage the velocity flow field is recorded using particle image velocimetry. Through understanding of the mechanisms involved in producing the wall jet and the importance of the encapsulated electrode a novel actuator design is proposed. The actuator design distributes the encapsulated electrode throughout the dielectric layer. The experiments have shown that actuators with a shallow initial encapsulated electrode induce velocities greater than the baseline case at the same voltage. Actuators with a deep initial encapsulated electrode are able to induce the highest velocities as they can operate at higher voltages without breakdown of the dielectric.
Transient Ejector Analysis (TEA) code user's guide
NASA Technical Reports Server (NTRS)
Drummond, Colin K.
1993-01-01
A FORTRAN computer program for the semi analytic prediction of unsteady thrust augmenting ejector performance has been developed, based on a theoretical analysis for ejectors. That analysis blends classic self-similar turbulent jet descriptions with control-volume mixing region elements. Division of the ejector into an inlet, diffuser, and mixing region allowed flexibility in the modeling of the physics for each region. In particular, the inlet and diffuser analyses are simplified by a quasi-steady-analysis, justified by the assumption that pressure is the forcing function in those regions. Only the mixing region is assumed to be dominated by viscous effects. The present work provides an overview of the code structure, a description of the required input and output data file formats, and the results for a test case. Since there are limitations to the code for applications outside the bounds of the test case, the user should consider TEA as a research code (not as a production code), designed specifically as an implementation of the proposed ejector theory. Program error flags are discussed, and some diagnostic routines are presented.
Synchronization Control of Neural Networks With State-Dependent Coefficient Matrices.
Zhang, Junfeng; Zhao, Xudong; Huang, Jun
2016-11-01
This brief is concerned with synchronization control of a class of neural networks with state-dependent coefficient matrices. Being different from the existing drive-response neural networks in the literature, a novel model of drive-response neural networks is established. The concepts of uniformly ultimately bounded (UUB) synchronization and convex hull Lyapunov function are introduced. Then, by using the convex hull Lyapunov function approach, the UUB synchronization design of the drive-response neural networks is proposed, and a delay-independent control law guaranteeing the bounded synchronization of the neural networks is constructed. All present conditions are formulated in terms of bilinear matrix inequalities. By comparison, it is shown that the neural networks obtained in this brief are less conservative than those ones in the literature, and the bounded synchronization is suitable for the novel drive-response neural networks. Finally, an illustrative example is given to verify the validity of the obtained results.
Local area network with fault-checking, priorities, and redundant backup
NASA Technical Reports Server (NTRS)
Morales, Sergio (Inventor); Friedman, Gary L. (Inventor)
1989-01-01
This invention is a redundant error detecting and correcting local area networked computer system having a plurality of nodes each including a network connector board within the node for connecting to an interfacing transceiver operably attached to a network cable. There is a first network cable disposed along a path to interconnect the nodes. The first network cable includes a plurality of first interfacing transceivers attached thereto. A second network cable is disposed in parallel with the first cable and, in like manner, includes a plurality of second interfacing transceivers attached thereto. There are a plurality of three position switches each having a signal input, three outputs for individual selective connection to the input, and a control input for receiving signals designating which of the outputs is to be connected to the signal input. Each of the switches includes means for designating a response address for responding to addressed signals appearing at the control input and each of the switches further has its signal input connected to a respective one of the input/output lines from the nodes. Also, one of the three outputs is connected to a repective one of the plurality of first interfacing transceivers. There is master switch control means having an output connected to the control inputs of the plurality of three position switches and an input for receiving directive signals for outputting addressed switch position signals to the three position switches as well as monitor and control computer means having a pair of network connector boards therein connected to respective ones of one of the first interfacing transceivers and one of the second interfacing transceivers and an output connected to the input of the master switch means for monitoring the status of the networked computer system by sending messages to the nodes and receiving and verifying messages therefrom and for sending control signals to the master switch to cause the master switch to cause respective ones of the nodes to use a desired one of the first and second cables for transmitting and receiving messages and for disconnecting desired ones of the nodes from both cables.
Hydrogeologic controls on summer stream temperatures in the McKenzie River basin, Oregon
Christina Tague; Michael Farrell; Gordon Grant; Sarah Lewis; Serge Rey
2007-01-01
Stream temperature is a complex function of energy inputs including solar radiation and latent and sensible heat transfer. In streams where groundwater inputs are significant, energy input through advection can also be an important control on stream temperature. For an individual stream reach, models of stream temperature can take advantage of direct measurement or...
A Secure and Reliable High-Performance Field Programmable Gate Array for Information Processing
2012-03-01
receives a data token from its control input (shown as a horizontal arrow above). The value of this data token is used to select an input port. The input...dual of a merge. It receives a data token from its control input (shown as a horizontal arrow above). The value of this data token is used to select...Transactions on Computer-Aided Design of Intergrated Circuits and Systems, Vol. 26, No. 2, February 2007. [12] Cadence Design Systems, “Clock Domain
Wireless, relative-motion computer input device
Holzrichter, John F.; Rosenbury, Erwin T.
2004-05-18
The present invention provides a system for controlling a computer display in a workspace using an input unit/output unit. A train of EM waves are sent out to flood the workspace. EM waves are reflected from the input unit/output unit. A relative distance moved information signal is created using the EM waves that are reflected from the input unit/output unit. Algorithms are used to convert the relative distance moved information signal to a display signal. The computer display is controlled in response to the display signal.
Comparison of gesture and conventional interaction techniques for interventional neuroradiology.
Hettig, Julian; Saalfeld, Patrick; Luz, Maria; Becker, Mathias; Skalej, Martin; Hansen, Christian
2017-09-01
Interaction with radiological image data and volume renderings within a sterile environment is a challenging task. Clinically established methods such as joystick control and task delegation can be time-consuming and error-prone and interrupt the workflow. New touchless input modalities may have the potential to overcome these limitations, but their value compared to established methods is unclear. We present a comparative evaluation to analyze the value of two gesture input modalities (Myo Gesture Control Armband and Leap Motion Controller) versus two clinically established methods (task delegation and joystick control). A user study was conducted with ten experienced radiologists by simulating a diagnostic neuroradiological vascular treatment with two frequently used interaction tasks in an experimental operating room. The input modalities were assessed using task completion time, perceived task difficulty, and subjective workload. Overall, the clinically established method of task delegation performed best under the study conditions. In general, gesture control failed to exceed the clinical input approach. However, the Myo Gesture Control Armband showed a potential for simple image selection task. Novel input modalities have the potential to take over single tasks more efficiently than clinically established methods. The results of our user study show the relevance of task characteristics such as task complexity on performance with specific input modalities. Accordingly, future work should consider task characteristics to provide a useful gesture interface for a specific use case instead of an all-in-one solution.
Neuromuscular mechanisms and neural strategies in the control of time-varying muscle contractions.
Erimaki, Sophia; Agapaki, Orsalia M; Christakos, Constantinos N
2013-09-01
The organization of the neural input to motoneurons that underlies time-varying muscle force is assumed to depend on muscle transfer characteristics and neural strategies or control modes utilizing sensory signals. We jointly addressed these interlinked, but previously studied individually and partially, issues for sinusoidal (range 0.5-5.0 Hz) force-tracking contractions of a human finger muscle. Using spectral and correlation analyses of target signal, force signal, and motor unit (MU) discharges, we studied 1) patterns of such discharges, allowing inferences on the motoneuronal input; 2) transformation of MU population activity (EMG) into quasi-sinusoidal force; and 3) relation of force oscillation to target, carrying information on the input's organization. A broad view of force control mechanisms and strategies emerged. Specifically, synchronized MU and EMG modulations, reflecting a frequency-modulated motoneuronal input, accompanied the force variations. Gain and delay drops between EMG modulation and force oscillation, critical for the appropriate organization of this input, occurred with increasing target frequency. According to our analyses, gain compensation was achieved primarily through rhythmical activation/deactivation of higher-threshold MUs and secondarily through the adaptation of the input's strength expected during tracking tasks. However, the input's timing was not adapted to delay behaviors and seemed to depend on the control modes employed. Thus, for low-frequency targets, the force oscillation was highly coherent with, but led, a target, this timing error being compatible with predictive feedforward control partly based on the target's derivatives. In contrast, the force oscillation was weakly coherent, but in phase, with high-frequency targets, suggesting control mainly based on a target's rhythm.
TRIAC/SCR proportional control circuit
Hughes, W.J.
1999-04-06
A power controller device is disclosed which uses a voltage-to-frequency converter in conjunction with a zero crossing detector to linearly and proportionally control AC power being supplied to a load. The output of the voltage-to frequency converter controls the ``reset`` input of a R-S flip flop, while an ``0`` crossing detector controls the ``set`` input. The output of the flip flop triggers a monostable multivibrator controlling the SCR or TRIAC firing circuit connected to the load. Logic gates prevent the direct triggering of the multivibrator in the rare instance where the ``reset`` and ``set`` inputs of the flip flop are in coincidence. The control circuit can be supplemented with a control loop, providing compensation for line voltage variations. 9 figs.
Slyter, Leonard L.
1975-01-01
An artifical rumen continuous culture with pH control, automated input of water-soluble and water-insoluble substrates, controlled mixing of contents, and a collection system for gas is described. Images PMID:16350029
Control assembly for controlling a fuel cell system during shutdown and restart
Venkataraman, Ramki; Berntsen, George; Carlson, Glenn L.; Farooque, Mohammad; Beachy, Dan; Peterhans, Stefan; Bischoff, Manfred
2010-06-15
A fuel cell system and method in which the fuel cell system receives and an input oxidant gas and an input fuel gas, and in which a fuel processing assembly is provided and is adapted to at least humidify the input fuel gas which is to be supplied to the anode of the fuel cell of the system whose cathode receives the oxidant input gas via an anode oxidizing assembly which is adapted to couple the output of the anode of the fuel cell to the inlet of the cathode of the fuel cell during normal operation, shutdown and restart of the fuel cell system, and in which a control assembly is further provided and is adapted to respond to shutdown of the fuel cell system during which input fuel gas and input oxidant gas cease to be received by the fuel cell system, the control assembly being further adapted to, when the fuel cell system is shut down: control the fuel cell system so as to enable a purging gas to be able to flow through the fuel processing assembly to remove humidified fuel gas from the processing assembly and to enable a purging gas to be able to flow through the anode of the fuel cell.
NASA Technical Reports Server (NTRS)
Lewis, Robert Michael; Patera, Anthony T.; Peraire, Jaume
1998-01-01
We present a Neumann-subproblem a posteriori finite element procedure for the efficient and accurate calculation of rigorous, 'constant-free' upper and lower bounds for sensitivity derivatives of functionals of the solutions of partial differential equations. The design motivation for sensitivity derivative error control is discussed; the a posteriori finite element procedure is described; the asymptotic bounding properties and computational complexity of the method are summarized; and illustrative numerical results are presented.
System and methods for reducing harmonic distortion in electrical converters
Kajouke, Lateef A; Perisic, Milun; Ransom, Ray M
2013-12-03
Systems and methods are provided for delivering energy using an energy conversion module. An exemplary method for delivering energy from an input interface to an output interface using an energy converison module coupled between the input interface and the output interface comprises the steps of determining an input voltage reference for the input interface based on a desired output voltage and a measured voltage and the output interface, determining a duty cycle control value based on a ratio of the input voltage reference and the measured voltage, operating one or more switching elements of the energy conversion module to deliver energy from the input interface to the output interface to the output interface with a duty cycle influenced by the dute cycle control value.
Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control.
Kotz, Kaylee; Cinar, Ali; Mei, Yong; Roggendorf, Amy; Littlejohn, Elizabeth; Quinn, Laurie; Rollins, Derrick K
2014-11-26
The ability to accurately develop subject-specific, input causation models, for blood glucose concentration (BGC) for large input sets can have a significant impact on tightening control for insulin dependent diabetes. More specifically, for Type 1 diabetics (T1Ds), it can lead to an effective artificial pancreas (i.e., an automatic control system that delivers exogenous insulin) under extreme changes in critical disturbances. These disturbances include food consumption, activity variations, and physiological stress changes. Thus, this paper presents a free-living, outpatient, multiple-input, modeling method for BGC with strong causation attributes that is stable and guards against overfitting to provide an effective modeling approach for feedforward control (FFC). This approach is a Wiener block-oriented methodology, which has unique attributes for meeting critical requirements for effective, long-term, FFC.
Dual control active superconductive devices
Martens, Jon S.; Beyer, James B.; Nordman, James E.; Hohenwarter, Gert K. G.
1993-07-20
A superconducting active device has dual control inputs and is constructed such that the output of the device is effectively a linear mix of the two input signals. The device is formed of a film of superconducting material on a substrate and has two main conduction channels, each of which includes a weak link region. A first control line extends adjacent to the weak link region in the first channel and a second control line extends adjacent to the weak link region in the second channel. The current flowing from the first channel flows through an internal control line which is also adjacent to the weak link region of the second channel. The weak link regions comprise small links of superconductor, separated by voids, through which the current flows in each channel. Current passed through the control lines causes magnetic flux vortices which propagate across the weak link regions and control the resistance of these regions. The output of the device taken across the input to the main channels and the output of the second main channel and the internal control line will constitute essentially a linear mix of the two input signals imposed on the two control lines. The device is especially suited to microwave applications since it has very low input capacitance, and is well suited to being formed of high temperature superconducting materials since all of the structures may be formed coplanar with one another on a substrate.
NASA Astrophysics Data System (ADS)
Wu, Bing-Fei; Ma, Li-Shan; Perng, Jau-Woei
This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.
Randomness Amplification under Minimal Fundamental Assumptions on the Devices
NASA Astrophysics Data System (ADS)
Ramanathan, Ravishankar; Brandão, Fernando G. S. L.; Horodecki, Karol; Horodecki, Michał; Horodecki, Paweł; Wojewódka, Hanna
2016-12-01
Recently, the physically realistic protocol amplifying the randomness of Santha-Vazirani sources producing cryptographically secure random bits was proposed; however, for reasons of practical relevance, the crucial question remained open regarding whether this can be accomplished under the minimal conditions necessary for the task. Namely, is it possible to achieve randomness amplification using only two no-signaling components and in a situation where the violation of a Bell inequality only guarantees that some outcomes of the device for specific inputs exhibit randomness? Here, we solve this question and present a device-independent protocol for randomness amplification of Santha-Vazirani sources using a device consisting of two nonsignaling components. We show that the protocol can amplify any such source that is not fully deterministic into a fully random source while tolerating a constant noise rate and prove the composable security of the protocol against general no-signaling adversaries. Our main innovation is the proof that even the partial randomness certified by the two-party Bell test [a single input-output pair (u* , x* ) for which the conditional probability P (x*|u*) is bounded away from 1 for all no-signaling strategies that optimally violate the Bell inequality] can be used for amplification. We introduce the methodology of a partial tomographic procedure on the empirical statistics obtained in the Bell test that ensures that the outputs constitute a linear min-entropy source of randomness. As a technical novelty that may be of independent interest, we prove that the Santha-Vazirani source satisfies an exponential concentration property given by a recently discovered generalized Chernoff bound.
Myers, Casey A.; Laz, Peter J.; Shelburne, Kevin B.; Davidson, Bradley S.
2015-01-01
Uncertainty that arises from measurement error and parameter estimation can significantly affect the interpretation of musculoskeletal simulations; however, these effects are rarely addressed. The objective of this study was to develop an open-source probabilistic musculoskeletal modeling framework to assess how measurement error and parameter uncertainty propagate through a gait simulation. A baseline gait simulation was performed for a male subject using OpenSim for three stages: inverse kinematics, inverse dynamics, and muscle force prediction. A series of Monte Carlo simulations were performed that considered intrarater variability in marker placement, movement artifacts in each phase of gait, variability in body segment parameters, and variability in muscle parameters calculated from cadaveric investigations. Propagation of uncertainty was performed by also using the output distributions from one stage as input distributions to subsequent stages. Confidence bounds (5–95%) and sensitivity of outputs to model input parameters were calculated throughout the gait cycle. The combined impact of uncertainty resulted in mean bounds that ranged from 2.7° to 6.4° in joint kinematics, 2.7 to 8.1 N m in joint moments, and 35.8 to 130.8 N in muscle forces. The impact of movement artifact was 1.8 times larger than any other propagated source. Sensitivity to specific body segment parameters and muscle parameters were linked to where in the gait cycle they were calculated. We anticipate that through the increased use of probabilistic tools, researchers will better understand the strengths and limitations of their musculoskeletal simulations and more effectively use simulations to evaluate hypotheses and inform clinical decisions. PMID:25404535
Multi-element stochastic spectral projection for high quantile estimation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ko, Jordan, E-mail: jordan.ko@mac.com; Garnier, Josselin
2013-06-15
We investigate quantile estimation by multi-element generalized Polynomial Chaos (gPC) metamodel where the exact numerical model is approximated by complementary metamodels in overlapping domains that mimic the model’s exact response. The gPC metamodel is constructed by the non-intrusive stochastic spectral projection approach and function evaluation on the gPC metamodel can be considered as essentially free. Thus, large number of Monte Carlo samples from the metamodel can be used to estimate α-quantile, for moderate values of α. As the gPC metamodel is an expansion about the means of the inputs, its accuracy may worsen away from these mean values where themore » extreme events may occur. By increasing the approximation accuracy of the metamodel, we may eventually improve accuracy of quantile estimation but it is very expensive. A multi-element approach is therefore proposed by combining a global metamodel in the standard normal space with supplementary local metamodels constructed in bounded domains about the design points corresponding to the extreme events. To improve the accuracy and to minimize the sampling cost, sparse-tensor and anisotropic-tensor quadratures are tested in addition to the full-tensor Gauss quadrature in the construction of local metamodels; different bounds of the gPC expansion are also examined. The global and local metamodels are combined in the multi-element gPC (MEgPC) approach and it is shown that MEgPC can be more accurate than Monte Carlo or importance sampling methods for high quantile estimations for input dimensions roughly below N=8, a limit that is very much case- and α-dependent.« less
Six axis force feedback input device
NASA Technical Reports Server (NTRS)
Ohm, Timothy (Inventor)
1998-01-01
The present invention is a low friction, low inertia, six-axis force feedback input device comprising an arm with double-jointed, tendon-driven revolute joints, a decoupled tendon-driven wrist, and a base with encoders and motors. The input device functions as a master robot manipulator of a microsurgical teleoperated robot system including a slave robot manipulator coupled to an amplifier chassis, which is coupled to a control chassis, which is coupled to a workstation with a graphical user interface. The amplifier chassis is coupled to the motors of the master robot manipulator and the control chassis is coupled to the encoders of the master robot manipulator. A force feedback can be applied to the input device and can be generated from the slave robot to enable a user to operate the slave robot via the input device without physically viewing the slave robot. Also, the force feedback can be generated from the workstation to represent fictitious forces to constrain the input device's control of the slave robot to be within imaginary predetermined boundaries.
NASA Technical Reports Server (NTRS)
Deutschmann, Julie; Sanner, Robert M.
2001-01-01
A nonlinear control scheme for attitude control of a spacecraft is combined with a nonlinear gyro bias observer for the case of constant gyro bias, in the presence of gyro noise. The observer bias estimates converge exponentially to a mean square bound determined by the standard deviation of the gyro noise. The resulting coupled, closed loop dynamics are proven to be globally stable, with asymptotic tracking which is also mean square bounded. A simulation of the proposed observer-controller design is given for a rigid spacecraft tracking a specified, time-varying attitude sequence to illustrate the theoretical claims.
NASA Technical Reports Server (NTRS)
Cheng, W.; Wen, J. T.
1992-01-01
A novel fast learning rule with fast weight identification is proposed for the two-time-scale neural controller, and a two-stage learning strategy is developed for the proposed neural controller. The results of the stability analysis show that both the tracking error and the fast weight error will be uniformly bounded and converge to a bounded region which depends only on the accuracy of the slow learning if the system is sufficiently excited. The efficiency of the two-stage learning is also demonstrated by a simulation of a two-link arm.
AU-FREDI - AUTONOMOUS FREQUENCY DOMAIN IDENTIFICATION
NASA Technical Reports Server (NTRS)
Yam, Y.
1994-01-01
The Autonomous Frequency Domain Identification program, AU-FREDI, is a system of methods, algorithms and software that was developed for the identification of structural dynamic parameters and system transfer function characterization for control of large space platforms and flexible spacecraft. It was validated in the CALTECH/Jet Propulsion Laboratory's Large Spacecraft Control Laboratory. Due to the unique characteristics of this laboratory environment, and the environment-specific nature of many of the software's routines, AU-FREDI should be considered to be a collection of routines which can be modified and reassembled to suit system identification and control experiments on large flexible structures. The AU-FREDI software was originally designed to command plant excitation and handle subsequent input/output data transfer, and to conduct system identification based on the I/O data. Key features of the AU-FREDI methodology are as follows: 1. AU-FREDI has on-line digital filter design to support on-orbit optimal input design and data composition. 2. Data composition of experimental data in overlapping frequency bands overcomes finite actuator power constraints. 3. Recursive least squares sine-dwell estimation accurately handles digitized sinusoids and low frequency modes. 4. The system also includes automated estimation of model order using a product moment matrix. 5. A sample-data transfer function parametrization supports digital control design. 6. Minimum variance estimation is assured with a curve fitting algorithm with iterative reweighting. 7. Robust root solvers accurately factorize high order polynomials to determine frequency and damping estimates. 8. Output error characterization of model additive uncertainty supports robustness analysis. The research objectives associated with AU-FREDI were particularly useful in focusing the identification methodology for realistic on-orbit testing conditions. Rather than estimating the entire structure, as is typically done in ground structural testing, AU-FREDI identifies only the key transfer function parameters and uncertainty bounds that are necessary for on-line design and tuning of robust controllers. AU-FREDI's system identification algorithms are independent of the JPL-LSCL environment, and can easily be extracted and modified for use with input/output data files. The basic approach of AU-FREDI's system identification algorithms is to non-parametrically identify the sampled data in the frequency domain using either stochastic or sine-dwell input, and then to obtain a parametric model of the transfer function by curve-fitting techniques. A cross-spectral analysis of the output error is used to determine the additive uncertainty in the estimated transfer function. The nominal transfer function estimate and the estimate of the associated additive uncertainty can be used for robust control analysis and design. AU-FREDI's I/O data transfer routines are tailored to the environment of the CALTECH/ JPL-LSCL which included a special operating system to interface with the testbed. Input commands for a particular experiment (wideband, narrowband, or sine-dwell) were computed on-line and then issued to respective actuators by the operating system. The operating system also took measurements through displacement sensors and passed them back to the software for storage and off-line processing. In order to make use of AU-FREDI's I/O data transfer routines, a user would need to provide an operating system capable of overseeing such functions between the software and the experimental setup at hand. The program documentation contains information designed to support users in either providing such an operating system or modifying the system identification algorithms for use with input/output data files. It provides a history of the theoretical, algorithmic and software development efforts including operating system requirements and listings of some of the various special purpose subroutines which were developed and optimized for Lahey FORTRAN compilers on IBM PC-AT computers before the subroutines were integrated into the system software. Potential purchasers are encouraged to purchase and review the documentation before purchasing the AU-FREDI software. AU-FREDI is distributed in DEC VAX BACKUP format on a 1600 BPI 9-track magnetic tape (standard media) or a TK50 tape cartridge. AU-FREDI was developed in 1989 and is a copyrighted work with all copyright vested in NASA.
Combined input shaping and feedback control for double-pendulum systems
NASA Astrophysics Data System (ADS)
Mar, Robert; Goyal, Anurag; Nguyen, Vinh; Yang, Tianle; Singhose, William
2017-02-01
A control system combining input shaping and feedback is developed for double-pendulum systems subjected to external disturbances. The proposed control method achieves fast point-to-point response similar to open-loop input-shaping control. It also minimizes transient deflections during the motion of the system, and disturbance-induced residual swing using the feedback control. Effects of parameter variations such as the mass ratio of the double pendulum, the suspension length ratio, and the move distance were studied via numerical simulation. The most important results were also verified with experiments on a small-scale crane. The controller effectively suppresses the disturbances and is robust to modelling uncertainties and task variations.
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.
Model-free adaptive control of supercritical circulating fluidized-bed boilers
Cheng, George Shu-Xing; Mulkey, Steven L
2014-12-16
A novel 3-Input-3-Output (3.times.3) Fuel-Air Ratio Model-Free Adaptive (MFA) controller is introduced, which can effectively control key process variables including Bed Temperature, Excess O2, and Furnace Negative Pressure of combustion processes of advanced boilers. A novel 7-input-7-output (7.times.7) MFA control system is also described for controlling a combined 3-Input-3-Output (3.times.3) process of Boiler-Turbine-Generator (BTG) units and a 5.times.5 CFB combustion process of advanced boilers. Those boilers include Circulating Fluidized-Bed (CFB) Boilers and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.
Extended H2 synthesis for multiple degree-of-freedom controllers
NASA Technical Reports Server (NTRS)
Hampton, R. David; Knospe, Carl R.
1992-01-01
H2 synthesis techniques are developed for a general multiple-input-multiple-output (MIMO) system subject to both stochastic and deterministic disturbances. The H2 synthesis is extended by incorporation of anticipated disturbances power-spectral-density information into the controller-design process, as well as by frequency weightings of generalized coordinates and control inputs. The methodology is applied to a simple single-input-multiple-output (SIMO) problem, analogous to the type of vibration isolation problem anticipated in microgravity research experiments.
Tool actuation and force feedback on robot-assisted microsurgery system
NASA Technical Reports Server (NTRS)
Das, Hari (Inventor); Ohm, Tim R. (Inventor); Boswell, Curtis D. (Inventor); Steele, Robert D. (Inventor)
2002-01-01
An input control device with force sensors is configured to sense hand movements of a surgeon performing a robot-assisted microsurgery. The sensed hand movements actuate a mechanically decoupled robot manipulator. A microsurgical manipulator, attached to the robot manipulator, is activated to move small objects and perform microsurgical tasks. A force-feedback element coupled to the robot manipulator and the input control device provides the input control device with an amplified sense of touch in the microsurgical manipulator.
NASA Astrophysics Data System (ADS)
Graymer, R. W.; Simpson, R. W.
2014-12-01
Graymer and Simpson (2013, AGU Fall Meeting) showed that in a simple 2D multi-fault system (vertical, parallel, strike-slip faults bounding blocks without strong material property contrasts) slip rate on block-bounding faults can be reasonably estimated by the difference between the mean velocity of adjacent blocks if the ratio of the effective locking depth to the distance between the faults is 1/3 or less ("effective" locking depth is a synthetic parameter taking into account actual locking depth, fault creep, and material properties of the fault zone). To check the validity of that observation for a more complex 3D fault system and a realistic distribution of observation stations, we developed a synthetic suite of GPS velocities from a dislocation model, with station location and fault parameters based on the San Francisco Bay region. Initial results show that if the effective locking depth is set at the base of the seismogenic zone (about 12-15 km), about 1/2 the interfault distance, the resulting synthetic velocity observations, when clustered, do a poor job of returning the input fault slip rates. However, if the apparent locking depth is set at 1/2 the distance to the base of the seismogenic zone, or about 1/4 the interfault distance, the synthetic velocity field does a good job of returning the input slip rates except where the fault is in a strong restraining orientation relative to block motion or where block velocity is not well defined (for example west of the northern San Andreas Fault where there are no observations to the west in the ocean). The question remains as to where in the real world a low effective locking depth could usefully model fault behavior. Further tests are planned to define the conditions where average cluster-defined block velocities can be used to reliably estimate slip rates on block-bounding faults. These rates are an important ingredient in earthquake hazard estimation, and another tool to provide them should be useful.
Vertical accretion and shallow subsidence in a mangrove forest of southwestern Florida, U.S.A
Cahoon, D.R.; Lynch, J.C.
1997-01-01
Simultaneous measurements of vertical accretion from artificial soil marker horizons and soil elevation change from sedimentation-erosion table (SET) plots were used to evaluate the processes related to soil building in range, basin, and overwash mangrove forests located in a low-energy lagoon which recieves minor inputs of terregenous sediments. Vertical accretion measures reflect the contribution of surficial sedimentation (sediment deposition and surface root growth). Measures of elevation change reflect not only the contributions of vertical accretion but also those of subsurface processes such as compaction, decomposition and shrink-swell. The two measures were used to calculate amounts of shallow subsidence (accretion minus elevation change) in each mangrove forest. The three forest types represent different accretionary envrionments. The basin forest was located behind a natural berm. Hydroperiod here was controlled primarily by rainfall rather than tidal exchange, although the basin flooded during extreme tidal events. Soil accretion here occurred primarily by autochthonous organic matter inputs, and elevation was controlled by accretion and shrink-swell of the substrate apparently related to cycles of flooding-drying and/or root growth-decomposition. This hydrologically-restricted forest did not experience an accretion or elevation deficit relative to sea-level rise. The tidally dominated fringe and overwash island forests accreted through mineral sediment inputs bound in place by plant roots. Filamentous turf algae played an important role in stabilizing loose muds in the fringe forest where erosion was prevalent. Elevation in these high-energy environments was controlled not only by accretion but also by erosion and/or shallow subsidence. The rate of shallow subsidence was consistently 3-4 mm y-1 in the fringe and overwash island forests but was negligible in the basin forest. Hence, the vertical development of mangrove soils was influenced by both surface and subsurface processes and the procces controlling soil elevation differed among forest types. The mangrove ecosystem at Rookery Bay has remained stable as sea level has risen during the past 70 years. Yet, lead-210 accretion data suggest a substantial accretion deficit has occurred in the past century (accretion was 10-20 cm < sea-level rise from 1930 to 1990) in the fringe and island forests at Rookery Bay. In contrast, our measures of elevation change mostly equalled the estimates of sea-level rise and shallow subsidence. These data suggest that (1) vertical accretion in this system is driven by local sea-level rise and shallow subsidence, and (2) the mangrove forests are mostly keeping pace with sea-level rise. Thus, the vulnerability of this mangrove ecosystem to sea-level rise is best described in terms of an elevation deficit (elevation change minus sea-level rise) based on annual measures rather than an accretion deficit (accretion minus sea-level rise) based on decadal measures.
Automated manual transmission clutch controller
Lawrie, Robert E.; Reed, Jr., Richard G.; Rausen, David J.
1999-11-30
A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.
Automated manual transmission shift sequence controller
Lawrie, Robert E.; Reed, Richard G.; Rausen, David J.
2000-02-01
A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both, an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.
Automated manual transmission mode selection controller
Lawrie, Robert E.
1999-11-09
A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.