The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform

Huanshui Zhang - One of the best experts on this subject based on the ideXlab platform.

  • LQG control on mixed H2/H∞ problem: the Discrete-Time Case
    International Journal of Systems Science, 2019
    Co-Authors: Wei Wang, Huanshui Zhang
    Abstract:

    ABSTRACTIn this paper, we are concerned with linear quadratic Gaussian (LQG) control on the mixed H2/H∞ problem. The mixed H2/H∞ problem can be formulated as a kind of constraint optimisation probl...

  • stackelberg game approach to mixed h 2 h problem the Discrete Time Case
    Chinese Control Conference, 2019
    Co-Authors: Wei Wang, Huanshui Zhang
    Abstract:

    In this paper, we are concerned with the mixed $H_{2}/H_{\infty}$ control problem which is formulated as a kind of constraint optimization problems where the control input is to minimize the H 2 -norm subject to the $\lt p\gt H_{\infty}$-constraint dealt with by the disturbance. The main contribution is to give the strategy in terms of three decoupled equations: two Riccati equations and one Lyapunov equation. The key technique is to apply the Stackelberg game approach by treating the disturbance as the follower and the control input as the leader respectively. A numerical example is given to verify the efficiency of the proposed approach.

  • Stackelberg Game Approach to Mixed H 2 /H∞ Problem: The Discrete-Time Case
    2019 Chinese Control Conference (CCC), 2019
    Co-Authors: Wei Wang, Huanshui Zhang
    Abstract:

    In this paper, we are concerned with the mixed $H_{2}/H_{\infty}$ control problem which is formulated as a kind of constraint optimization problems where the control input is to minimize the H 2 -norm subject to the $\lt p\gt H_{\infty}$-constraint dealt with by the disturbance. The main contribution is to give the strategy in terms of three decoupled equations: two Riccati equations and one Lyapunov equation. The key technique is to apply the Stackelberg game approach by treating the disturbance as the follower and the control input as the leader respectively. A numerical example is given to verify the efficiency of the proposed approach.

  • optimal control for mean field system Discrete Time Case
    Conference on Decision and Control, 2016
    Co-Authors: Huanshui Zhang
    Abstract:

    This paper is concerned with Discrete-Time mean-field linear-quadratic (LQ) control problem. A thorough solution to the problem is given for the first Time. The sufficient and necessary condition for the solvability of mean-field LQ control problem is firstly presented in analytical expression based on the maximum principle developed in this paper, which is compared with the results obtained in literatures where only operator type solvability conditions were given. The optimal controller is given in terms of a coupled Riccati equation which is derived from the solution to forward and backward stochastic difference equation (FBSDE). The key techniques adopted in this paper are the maximum principle and the solution to the FBSDE obtained in this paper. The derived results in this paper will provide us the insight to solve the mean-field control problem for continuous-Time systems and other related problems.

  • CDC - Optimal control for mean-field system: Discrete-Time Case
    2016 IEEE 55th Conference on Decision and Control (CDC), 2016
    Co-Authors: Huanshui Zhang
    Abstract:

    This paper is concerned with Discrete-Time mean-field linear-quadratic (LQ) control problem. A thorough solution to the problem is given for the first Time. The sufficient and necessary condition for the solvability of mean-field LQ control problem is firstly presented in analytical expression based on the maximum principle developed in this paper, which is compared with the results obtained in literatures where only operator type solvability conditions were given. The optimal controller is given in terms of a coupled Riccati equation which is derived from the solution to forward and backward stochastic difference equation (FBSDE). The key techniques adopted in this paper are the maximum principle and the solution to the FBSDE obtained in this paper. The derived results in this paper will provide us the insight to solve the mean-field control problem for continuous-Time systems and other related problems.

Zhongping Jiang - One of the best experts on this subject based on the ideXlab platform.

Xiaohui Liu - One of the best experts on this subject based on the ideXlab platform.

  • on passivity and passification of stochastic fuzzy systems with delays the Discrete Time Case
    Systems Man and Cybernetics, 2010
    Co-Authors: Jinling Liang, Zidong Wang, Xiaohui Liu
    Abstract:

    Takagi–Sugeno (T-S) fuzzy models, which are usually represented by a set of linear submodels, can be used to describe or approximate any complex nonlinear systems by fuzzily blending these subsystems, and so, significant research efforts have been devoted to the analysis of such models. This paper is concerned with the passivity and passification problems of the stochastic Discrete-Time T-S fuzzy systems with delay. We first propose the definition of passivity in the sense of expectation. Then, by utilizing the Lyapunov functional method, the stochastic analysis combined with the matrix inequality techniques, a sufficient condition in terms of linear matrix inequalities is presented, ensuring the passivity performance of the T-S fuzzy models. Finally, based on this criterion, state feedback controller is designed, and several criteria are obtained to make the closed-loop system passive in the sense of expectation. The results acquired in this paper are delay dependent in the sense that they depend on not only the lower bound but also the upper bound of the Time-varying delay. Numerical examples are also provided to demonstrate the effectiveness and feasibility of our criteria.

  • Correspondence On Passivity and Passification of Stochastic Fuzzy Systems With Delays: The Discrete-Time Case
    2010
    Co-Authors: Jinling Liang, Zidong Wang, Xiaohui Liu
    Abstract:

    Takagi-Sugeno (T-S) fuzzy models, which are usually repre- sented by a set of linear submodels, can be used to describe or approximate any complex nonlinear systems by fuzzily blending these subsystems, and so, significant research efforts have been devoted to the analysis of such models. This paper is concerned with the passivity and passification problems of the stochastic Discrete-Time T-S fuzzy systems with delay. We first propose the definition of passivity in the sense of expectation. Then, by utilizing the Lyapunov functional method, the stochastic analysis combined with the matrix inequality techniques, a sufficient condition in terms of linear matrix inequalities is presented, ensuring the passivity performance of the T-S fuzzy models. Finally, based on this criterion, state feedback controller is designed, and several criteria are obtained to make the closed-loop system passive in the sense of expectation. The results acquired in this paper are delay dependent in the sense that they depend on not only the lower bound but also the upper bound of the Time-varying delay. Numerical examples are also provided to demonstrate the effectiveness and feasibility of our criteria.

  • asymptotic stability for neural networks with mixed Time delays the Discrete Time Case
    Neural Networks, 2009
    Co-Authors: Yurong Liu, Zidong Wang, Xiaohui Liu
    Abstract:

    This paper is concerned with the stability analysis problem for a new class of Discrete-Time recurrent neural networks with mixed Time-delays. The mixed Time-delays that consist of both the Discrete and distributed Time-delays are addressed, for the first Time, when analyzing the asymptotic stability for Discrete-Time neural networks. The activation functions are not required to be differentiable or strictly monotonic. The existence of the equilibrium point is first proved under mild conditions. By constructing a new Lyapnuov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the Discrete-Time neural networks to be globally asymptotically stable. As an extension, we further consider the stability analysis problem for the same class of neural networks but with state-dependent stochastic disturbances. All the conditions obtained are expressed in terms of LMIs whose feasibility can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition.

Natasa A. Kablar - One of the best experts on this subject based on the ideXlab platform.

  • Dissipativity theory for singular systems. Part II: Discrete-Time Case
    2010 15th International Conference on Methods and Models in Automation and Robotics, 2010
    Co-Authors: Natasa A. Kablar
    Abstract:

    In this paper we develop dissipativity results for Discrete nonlinear and linear singular systems. To the best knowledge of author results are nonexistent. We generalize dissipativity theory to Discrete nonlinear singular dynamical systems. Specifically, the classical concepts of system storage functions and supply rates are extended to singular dynamical systems providing a generalized system energy interpretation in terms of stored energy and dissipated energy over the Discrete-Time system dynamics. For the class of Discrete singular systems we present Kalman-Yakubovich-Popov conditions in terms of the Discrete singular system dynamics characterizing dissipativeness via system storage function. The framework is specialized to passive and nonexpansive Discrete singular systems to provide a generalization of the classical notions of passivity and nonexpansivity for nonlinear Discrete singular systems.

  • CDC - Dissipativity theory for singular systems. Part II: Discrete-Time Case
    49th IEEE Conference on Decision and Control (CDC), 2010
    Co-Authors: Natasa A. Kablar
    Abstract:

    In this paper we develop dissipativity results for Discrete nonlinear and linear singular systems. To the best knowledge of author results are nonexistent. We generalize dissipativity theory to Discrete nonlinear singular dynamical systems. Specifically, the classical concepts of system storage functions and supply rates are extended to singular dynamical systems providing a generalized system energy interpretation in terms of stored energy and dissipated energy over the Discrete-Time system dynamics. For the class of Discrete singular systems we present Kalman-Yakubovich-Popov conditions in terms of the Discrete singular system dynamics characterizing dissipativeness via system storage function. The framework is specialized to passive and nonexpansive Discrete singular systems to provide a generalization of the classical notions of passivity and nonexpansivity for nonlinear Discrete singular systems.

Robert E. Skelton - One of the best experts on this subject based on the ideXlab platform.

  • Mean-square small gain theorem for stochastic control: Discrete-Time Case
    IEEE Transactions on Automatic Control, 2002
    Co-Authors: Robert E. Skelton
    Abstract:

    This paper presents a small gain theorem in the mean square sense for multiple (interconnected) linear systems with multiplicative noises. The small-gain theorem is proposed in terms of the spectral radius of a matrix, whose elements are the squares of H/sub 2/ norms of the involved transfer functions. Both robust stability and performance conditions are characterized by the new small-gain theorem.

  • A Computational Algorithm for Covariance Control: Discrete-Time Case
    1993 American Control Conference, 1993
    Co-Authors: Tetsuya Iwasaki, Robert E. Skelton, Martin Corless
    Abstract:

    A new controller design method for linear Discrete-Time systems is proposed via covariance assignment. The primary contributions of this paper are twofold. First, the set of all closed loop plant state covariances which a linear Discrete-Time system may possess is characterized. The set is shown to be convex. Secondly, a finite step algorithm for constructing an assignable plant state covariance is presented.