Adaptive fuzzy finite-time control of stochastic nonlinear systems with actuator faults

2021 ◽  
Vol 104 (1) ◽  
pp. 523-536
Author(s):  
Libin Wang ◽  
Huanqing Wang ◽  
Peter Xiaoping Liu
Keyword(s):  
Nonlinear Systems ◽  
Finite Time ◽  
Stochastic Nonlinear Systems ◽  
Actuator Faults ◽  
Adaptive Fuzzy ◽  
Time Control

Adaptive Fuzzy Finite-Time Control of Nonlinear Systems With Actuator Faults

2020 ◽  
Vol 50 (5) ◽  
pp. 1786-1797 ◽  
Author(s):  
Huanqing Wang ◽  
Peter Xiaoping Liu ◽  
Xudong Zhao ◽  
Xiaoping Liu
Keyword(s):  
Nonlinear Systems ◽  
Finite Time ◽  
Actuator Faults ◽  
Adaptive Fuzzy ◽  
Time Control

Neural network-based finite-time control of quantized stochastic nonlinear systems

2019 ◽  
Vol 362 ◽  
pp. 195-202 ◽  
Author(s):  
Fang Wang ◽  
LiLi Zhang ◽  
Shaowei Zhou ◽  
Yuanyuan Huang
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Finite Time ◽  
Stochastic Nonlinear Systems ◽  
Time Control

scholarly journals Resilient Finite-Time Controller Design of a Class of Stochastic Nonlinear Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Zhiguo Yan
Keyword(s):  
Nonlinear Systems ◽  
Finite Time ◽  
State Feedback ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Stochastic Nonlinear Systems ◽  
Matrix Inequalities ◽  
Annular Domain ◽  
Stabilizing Controller ◽  
Time Control

This paper deals with the problem of resilient finite-time control for a class of stochastic nonlinear systems. The notion of finite-time annular domain stability of stochastic nonlinear systems is first introduced. Then, some sufficient conditions are given for the existence of resilient state feedback finite-time annular domain stabilizing controller, which are expressed in terms of matrix inequalities. A double-parameter searching algorithm is proposed to solve these obtained matrix inequalities. Finally, an example is given to illustrate the effectiveness of the developed method.

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