The Experts below are selected from a list of 48663 Experts worldwide ranked by ideXlab platform
Matthew R. James - One of the best experts on this subject based on the ideXlab platform.
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L∞-bounded Robust Control of nonlinear cascade systems☆
Systems & Control Letters, 2005Co-Authors: Shoudong Huang, Matthew R. James, Zhong-ping JiangAbstract:In this paper, we consider the L ∞ -bounded Robust Control Problem for a class of nonlinear cascade systems with disturbances. Sufficient conditions are providedunder which a hardboundis imposedon the system performance measure. The backstepping approach is used for Controller design. A practical example is provided to illustrate the method. © 2004 Elsevier B.V. All rights reserved.
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l/sup /spl infin//-bounded Robustness for nonlinear systems: analysis and synthesis
IEEE Transactions on Automatic Control, 2003Co-Authors: Shoudong Huang, Matthew R. JamesAbstract:The purpose of this paper is to describe systematic analysis and design tools for Robust Control Problems with l/sup /spl infin// criteria. We first generalize the Hill-Moylan-Willems framework for dissipative systems to accommodate l/sup /spl infin// criteria, and then derive state feedback and measurement feedback synthesis procedures for l/sup /spl infin// Robust Control Problems. The information state framework is used for the measurement feedback Robust Control Problem. Necessary and sufficient conditions are proved, and new synthesis procedures using dynamic programming are presented.
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Robust output feedback Control for discrete-time nonlinear systems: the finite-time case
Proceedings of 32nd IEEE Conference on Decision and Control, 1Co-Authors: John S. Baras, Matthew R. JamesAbstract:Presents an approach to the solution of the output feedback Robust Control Problem. The authors employ the concept of information state for output feedback dynamic games, and obtain necessary and sufficient conditions for the solution to the Robust Control Problem expressed in terms of the information state. The resulting Controller is an information state feedback Controller, and is intrinsically infinite dimensional. >
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l/sup /spl infin//-bounded Robust Control for nonlinear discrete time systems
Proceedings of the 41st IEEE Conference on Decision and Control 2002., 1Co-Authors: Matthew R. James, Shoudong HuangAbstract:In this paper we solve a measurement feedback disturbance rejection Robust Control Problem for nonlinear systems based on a l/sup /spl infin// criterion. Information state techniques are employed to obtain necessary and sufficient conditions and the Controller synthesis procedure. The results are consistent with the separation structure in Shamma-Tu (1999).
Shoudong Huang - One of the best experts on this subject based on the ideXlab platform.
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L∞-bounded Robust Control of nonlinear cascade systems☆
Systems & Control Letters, 2005Co-Authors: Shoudong Huang, Matthew R. James, Zhong-ping JiangAbstract:In this paper, we consider the L ∞ -bounded Robust Control Problem for a class of nonlinear cascade systems with disturbances. Sufficient conditions are providedunder which a hardboundis imposedon the system performance measure. The backstepping approach is used for Controller design. A practical example is provided to illustrate the method. © 2004 Elsevier B.V. All rights reserved.
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L/sup /spl infin//-bounded Robust Control of nonlinear cascade systems
2004Co-Authors: Shoudong Huang, M.r. James, Zhong-ping JiangAbstract:In this paper, we consider the L/sup /spl infin//-bounded Robust Control Problem for a class of nonlinear cascade systems with disturbances. Sufficient conditions are provided under which a hard bound is imposed on the system performance measure. The backstepping approach is used for Controller design. Examples are provided to illustrate the method.
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l/sup /spl infin//-bounded Robustness for nonlinear systems: analysis and synthesis
IEEE Transactions on Automatic Control, 2003Co-Authors: Shoudong Huang, Matthew R. JamesAbstract:The purpose of this paper is to describe systematic analysis and design tools for Robust Control Problems with l/sup /spl infin// criteria. We first generalize the Hill-Moylan-Willems framework for dissipative systems to accommodate l/sup /spl infin// criteria, and then derive state feedback and measurement feedback synthesis procedures for l/sup /spl infin// Robust Control Problems. The information state framework is used for the measurement feedback Robust Control Problem. Necessary and sufficient conditions are proved, and new synthesis procedures using dynamic programming are presented.
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l/sup /spl infin//-bounded Robust Control for nonlinear discrete time systems
Proceedings of the 41st IEEE Conference on Decision and Control 2002., 1Co-Authors: Matthew R. James, Shoudong HuangAbstract:In this paper we solve a measurement feedback disturbance rejection Robust Control Problem for nonlinear systems based on a l/sup /spl infin// criterion. Information state techniques are employed to obtain necessary and sufficient conditions and the Controller synthesis procedure. The results are consistent with the separation structure in Shamma-Tu (1999).
Yang Shi - One of the best experts on this subject based on the ideXlab platform.
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Consensus for Linear Multiagent Systems With Time-Varying Delays: A Frequency Domain Perspective
IEEE transactions on cybernetics, 2016Co-Authors: Yuanye Chen, Yang ShiAbstract:This paper investigates the consensus Problem for multiagent systems with time-varying delays. The bounded delays can be arbitrarily fast time-varying. The communication topology is assumed to be undirected and fixed. With general linear dynamics under average state feedback protocols, the consensus Problem is then transformed into the Robust Control Problem. Further, sufficient frequency domain criteria are established in terms of small gain theorem by analyzing the delay dependent gains for both continuous-time and discrete-time systems. The Controller synthesis Problems can be solved by applying the frequency domain design methods. Numerical examples are demonstrated to verify the effectiveness of the proposed approaches.
Liying Sun - One of the best experts on this subject based on the ideXlab platform.
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Observer-based finite-time Robust Control of nonlinear time-delay systems via Hamiltonian function method
International Journal of Control, 2020Co-Authors: Renming Yang, Guangyuan Zhang, Liying SunAbstract:This paper investigates the observer-based finite-time Robust Control Problem of a general class of nonlinear time-delay systems via Hamiltonian function method, and proposes some new finite-time r...
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Finite-time Robust Control of a class of nonlinear time-delay systems via Lyapunov functional method
Journal of the Franklin Institute, 2019Co-Authors: Renming Yang, Liying SunAbstract:Abstract This paper investigates the finite-time Robust Control Problem of a class of nonlinear time-delay systems with general form, and proposes some new delay-independent and delay-dependent conditions on the issue. First, by developing an equivalent form, the paper studies finite-time stabilization Problem, and presents some delay-dependent stabilization results by constructing suitable Lyapunov functionals. Then, based on the stabilization results, we study the finite-time Robust Control Problem for the systems, and give a Robust Control design procedure. Finally, the study of two illustrative examples shows that the results obtained of the paper work well in the finite-time stabilization and Robust stabilization for the systems. It is shown that, by using the method in the paper, the obtained results do not contain delay terms, which can avoid solving nonlinear mixed matrix inequalities and reduce effectively computational burden. Moreover, different from existing finite-time results, the paper also presents delay-dependent sufficient conditions on the finite-time Control Problem for the systems.
Derong Liu - One of the best experts on this subject based on the ideXlab platform.
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Event-Triggered Adaptive Dynamic Programming for Unmatched Uncertain Nonlinear Continuous-Time Systems.
IEEE transactions on neural networks and learning systems, 2020Co-Authors: Shan Xue, Biao Luo, Derong LiuAbstract:In this article, an event-triggered adaptive dynamic programming (ADP) method is proposed to solve the Robust Control Problem of unmatched uncertain systems. First, the Robust Control Problem with unmatched uncertainties is transformed into the optimal Control design for an auxiliary system. Subsequently, to reduce Controller executions and save computational and communication resources, an event-triggering mechanism is introduced. By using a critic neural network (NN) to approximate the value function, novel concurrent learning is developed to learn NN weights, which avoids the requirement of an initial admissible Control and the persistence of excitation condition. Moreover, it is proven that the developed event-triggered ADP Controller guarantees the Robustness of the uncertain system and the uniform ultimate boundedness of the NN weight estimation error. Finally, by using the F-16 aircraft and the inverted pendulum with unmatched uncertainties as examples, the simulation results show the effectiveness of the developed event-triggered ADP method.
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policy iteration algorithm for online design of Robust Control for a class of continuous time nonlinear systems
IEEE Transactions on Automation Science and Engineering, 2014Co-Authors: Ding Wang, Derong Liu, Hongliang LiAbstract:In this paper, a novel strategy is established to design the Robust Controller for a class of continuous-time nonlinear systems with uncertainties based on the online policy iteration algorithm. The Robust Control Problem is transformed into the optimal Control Problem by properly choosing a cost function that reflects the uncertainties, regulation, and Control. An online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman (HJB) equation by constructing a critic neural network. The approximate expression of the optimal Control policy can be derived directly. The closed-loop system is proved to possess the uniform ultimate boundedness. The equivalence of the neural-network-based HJB solution of the optimal Control Problem and the solution of the Robust Control Problem is established as well. Two simulation examples are provided to verify the effectiveness of the present Robust Control scheme.
