A Covariance Controller Design Incorporating Optimal Estimation for Nonlinear Stochastic Systems

1996 ◽  
Vol 118 (2) ◽  
pp. 346-349 ◽  
Author(s):  
Wen-Jer Chang ◽  
Hung-Yuan Chung
Keyword(s):  
Cost Function ◽  
Stochastic Systems ◽  
Controller Design ◽  
Optimal Estimation ◽  
Nonlinear Stochastic Systems ◽  
Numerical Example ◽  
Describing Functions ◽  
Covariance Control ◽  
Variance Design

This note addresses the problem of constrained variance design with minimizing LQG cost function via the method of covariance control incorporating the optimal estimation for nonlinear stochastic systems. The nonlinear stochastic systems are first linearized and then are examined by way of the technique of describing functions. Finally, an application of this approach to a position servomechanism is illustrated by a numerical example.

Robust Fault-Tolerant Control for a Class of Nonlinear Stochastic Systems With Variance Constraints

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Lifeng Ma ◽  
Zidong Wang ◽  
Yuming Bo ◽  
Zhi Guo
Keyword(s):  
Design Problem ◽  
Stochastic Systems ◽  
Controller Design ◽  
Fault Tolerant ◽  
Linear Matrix ◽  
Actuator Faults ◽  
Nonlinear Stochastic Systems ◽  
Single Degree Of Freedom ◽  
Actuator Failures ◽  
Special Cases

This paper is concerned with the variance-constrained controller design problem for a class of uncertain nonlinear stochastic systems with possible actuator faults. The stochastic nonlinearities described by statistical means are quite general that include several well-studied classes of nonlinearities as special cases. A model of actuator failures is adopted, which is more practical than the traditional outage one. A linear matrix inequality (LMI) approach is proposed to solve the multiobjective fault-tolerant controller design problem, where both the exponential stability and the steady-state state variance indices are simultaneously guaranteed. Within the developed LMI framework, a sufficient condition for the solvability of the robust control problem is obtained. The explicit expression of the desired controllers is also parameterized and a single degree-of-freedom model is used to demonstrate the effectiveness and applicability of the proposed design approach.

scholarly journals A Covariance Feedback Approach to Covariance Control of Nonlinear Stochastic Systems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Salman Baroumand ◽  
Amir Reza Zaman ◽  
Mohammad Reza Mahmoudi
Keyword(s):  
Nonlinear Systems ◽  
Linear Approximation ◽  
Feedback Linearization ◽  
Control Algorithm ◽  
Stochastic Systems ◽  
Control Method ◽  
Nonlinear Case ◽  
Nonlinear Stochastic Systems ◽  
Covariance Control ◽  
Feedback Algorithm

In this paper, the covariance control algorithm for nonlinear stochastic systems using covariance feedback is studied. Covariance control of nonlinear systems scenario involves the theory of covariance control based on the idea of the covariance feedback. Therefore, the proposed covariance control algorithm is derived for our case, firstly by applying the covariance control method and linear approximation of nonlinear systems, and then it is achieved by adopting this method for a class of nonlinear stochastic systems by using feedback linearization idea and a covariance feedback controller. The effectiveness of the proposed covariance feedback algorithm is studied using numerous simulations concerning different nonlinear case studies.

scholarly journals EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems

2018 ◽  
Vol 63 (4) ◽  
pp. 1155-1162 ◽  
Author(s):  
Yuyang Zhou ◽  
Qichun Zhang ◽  
Hong Wang ◽  
Ping Zhou ◽  
Tianyou Chai
Keyword(s):  
Stochastic Systems ◽  
Controller Design ◽  
Nonlinear Stochastic Systems
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