Quantized stabilization of stochastic systems with multiplicative noise under Markovian switching

2019 ◽  
Vol 37 (3) ◽  
pp. 458-472
Author(s):  
S. Sathananthan ◽  
Mohammad Habibi ◽  
Netra Dahal
Keyword(s):  
Multiplicative Noise ◽  
Stochastic Systems ◽  
Markovian Switching

scholarly journals Finite-TimeH∞Control for Time-Delayed Stochastic Systems with Markovian Switching

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Wenhua Gao ◽  
Feiqi Deng ◽  
Ruiqiu Zhang ◽  
Wenhui Liu
Keyword(s):  
Finite Time ◽  
State Feedback ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Markovian Switching ◽  
Time Stability ◽  
Finite Time Stability ◽  
Weighting Matrix ◽  
Simulation Results ◽  
Dependent State

This paper studies the problem of finite-timeH∞control for time-delayed Itô stochastic systems with Markovian switching. By using the appropriate Lyapunov-Krasovskii functional and free-weighting matrix techniques, some sufficient conditions of finite-time stability for time-delayed stochastic systems with Markovian switching are proposed. Based on constructing new Lyapunov-Krasovskii functional, the mode-dependent state feedback controller for the finite-timeH∞control is obtained. Simulation results illustrate the effectiveness of the proposed 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.

scholarly journals pth Mean Practical Stability for Large-Scale Itô Stochastic Systems with Markovian Switching

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Yan Yun ◽  
Huisheng Shu ◽  
Yan Che
Keyword(s):  
Comparison Principle ◽  
Large Scale ◽  
Stochastic Systems ◽  
Markovian Switching ◽  
Practical Stability ◽  
Nonlinear Stochastic Systems ◽  
Deterministic Systems ◽  
The One

Motivated by the study of a class of large-scale stochastic systems with Markovian switching, this correspondence paper is concerned with the practical stability in thepth mean. By investigating Lyapunov-like functions and the basic comparison principle, some criteria are derived for various types of practical stability in thepth mean of nonlinear stochastic systems. The main contribution of these results is to convert the problem of practical stability in thepth mean of stochastic systems into the one of practical stability of the comparative deterministic systems.

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