On parameter estimation of partly observed bilinear discrete-time stochastic systems

Metrika ◽  
2010 ◽  
Vol 75 (3) ◽  
pp. 403-424 ◽  
Author(s):  
A. Malyarenko ◽  
V. Vasiliev
Keyword(s):  
Parameter Estimation ◽  
Discrete Time ◽  
Stochastic Systems

DECOMPOSITION OF NONLINEAR DISCRETE-TIME STOCHASTIC SYSTEMS

1985 ◽  
Vol 5 (4) ◽  
pp. 399-413
Author(s):  
Chongzhao Han
Keyword(s):  
Discrete Time ◽  
Stochastic Systems

pth moment $${\cal D}$$-stability/stabilization of linear discrete-time stochastic systems

2021 ◽  
Vol 65 (3) ◽  
Author(s):  
Huasheng Zhang ◽  
Jianwei Xia ◽  
Yining Zhang ◽  
Hao Shen ◽  
Zhen Wang
Keyword(s):  
Discrete Time ◽  
Stochastic Systems

scholarly journals Fuzzy Stabilization for Nonlinear Discrete Ship Steering Stochastic Systems Subject to State Variance and Passivity Constraints

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Wen-Jer Chang ◽  
Bo-Jyun Huang ◽  
Po-Hsun Chen
Keyword(s):  
Linear Matrix Inequality ◽  
Discrete Time ◽  
Stochastic Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Control Technique ◽  
Linear Matrix ◽  
Matrix Inequality ◽  
Ship Steering

For nonlinear discrete-time stochastic systems, a fuzzy controller design methodology is developed in this paper subject to state variance constraint and passivity constraint. According to fuzzy model based control technique, the nonlinear discrete-time stochastic systems considered in this paper are represented by the discrete-time Takagi-Sugeno fuzzy models with multiplicative noise. Employing Lyapunov stability theory, upper bound covariance control theory, and passivity theory, some sufficient conditions are derived to find parallel distributed compensation based fuzzy controllers. In order to solve these sufficient conditions, an iterative linear matrix inequality algorithm is applied based on the linear matrix inequality technique. Finally, the fuzzy stabilization problem for nonlinear discrete ship steering stochastic systems is investigated in the numerical example to illustrate the feasibility and validity of proposed fuzzy controller design method.

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