scholarly journals H∞Control for Nonlinear Stochastic Systems with Time-Delay and Multiplicative Noise

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Ming Gao ◽  
Weihai Zhang ◽  
Zhengmao Zhu
Keyword(s):  
Time Delay ◽  
General Class ◽  
Multiplicative Noise ◽  
Stochastic Systems ◽  
Design Method ◽  
Infinite Horizon ◽  
Control Design ◽  
Mean Square ◽  
Nonlinear Stochastic Systems ◽  
Numerical Examples

This paper studies the infinite horizonH∞control problem for a general class of nonlinear stochastic systems with time-delay and multiplicative noise. The exponential/asymptotic mean squareH∞control design of delayed nonlinear stochastic systems is presented by solving Hamilton-Jacobi inequalities. Two numerical examples are provided to show the effectiveness of the proposed design method.

scholarly journals H∞ Control for Nonlinear Infinite Markov Jump Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yueying Liu ◽  
Ting Hou
Keyword(s):  
Stochastic Systems ◽  
Design Method ◽  
Infinite Horizon ◽  
Mean Square ◽  
State Control ◽  
Markov Jump ◽  
Nonlinear Stochastic Systems ◽  
Markov Jump Systems ◽  
Jump Systems ◽  
Infinite State

In this paper, we discuss the infinite horizon H∞ control problem for a class of nonlinear stochastic systems with state, control, and disturbance dependent noise. The jumping parameters are modelled as an infinite-state Markov chain. Based on the solvability of a set of coupled Hamilton-Jacobi inequalities (HJIs), the exponential mean square H∞ controller for the considered nonlinear stochastic systems is obtained. A numerical example is given to show the effectiveness of the proposed design method.

scholarly journals A tracking error–based fully probabilistic control for stochastic discrete-time systems with multiplicative noise

2020 ◽  
Vol 26 (23-24) ◽  
pp. 2329-2339
Author(s):  
Randa Herzallah ◽  
Yuyang Zhou
Keyword(s):  
Error Control ◽  
Multiplicative Noise ◽  
Stochastic Systems ◽  
Design Method ◽  
Tracking Error ◽  
Flexible Beam ◽  
System Control ◽  
Probabilistic Design ◽  
Leibler Divergence ◽  
Tracking Error Control

This article proposes the exploitation of the Kullback–Leibler divergence to characterise the uncertainty of the tracking error for general stochastic systems without constraints of certain distributions. The general solution to the fully probabilistic design of the tracking error control problem is first stated. Further development then focuses on the derivation of a randomised controller for a class of linear stochastic Gaussian systems that are affected by multiplicative noise. The derived control solution takes the multiplicative noise of the controlled system into consideration in the derivation of the randomised controller. The proposed fully probabilistic design of the tracking error of the system dynamics is a more legitimate approach than the conventional fully probabilistic design method. It directly characterises the main objective of system control. The efficiency of the proposed method is then demonstrated on a flexible beam example where the vibration quenching in flexible beams is shown to be effectively suppressed.

A New Controller of Stochastic Delay Systems

2011 ◽  
Vol 63-64 ◽  
pp. 974-977
Author(s):  
Yun Chen ◽  
Qing Qing Li
Keyword(s):  
Time Delay ◽  
Closed Loop ◽  
Stochastic Systems ◽  
Delay Systems ◽  
Mean Square ◽  
Closed Loop System ◽  
Stochastic Delay ◽  
Numerical Example ◽  
Mean Square Stability ◽  
Delay Dependent

By introducing an additional vector, a new delay-dependent controller is designed for stochastic systems with time delay in this paper. The presented controller is formulated by means of LMI, and it guarantees robust asymptotical mean-square stability of the resulting closed-loop system. Our result shows advantage over some existing ones, which is demonstrated by a numerical example.

scholarly journals Delay-Dependent RobustH∞Filtering of the Takagi-Sugeno Fuzzy Stochastic Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Ze Li ◽  
Xin-Hao Yang
Keyword(s):  
Stochastic Systems ◽  
Design Method ◽  
Linear Matrix ◽  
Mean Square ◽  
Matrix Inequalities ◽  
Parameter Uncertainties ◽  
Mean Square Stability ◽  
Error System ◽  
Delay Dependent ◽  
Takagi Sugeno

This paper is concerned with the problem of the robustH∞filtering for the Takagi-Sugeno (T-S) fuzzy stochastic systems with bounded parameter uncertainties. For a given T-S fuzzy stochastic system, this paper focuses on the stochastically mean-square stability of the filtering error system and theH∞performance level of the output error and the disturbance input. The design method for delay-dependent filter is developed based on linear matrix inequalities. Finally, the effectiveness of the proposed methods is substantiated with an illustrative example.

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