Technical Briefs

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

[+] Author and Article Information
Lifeng Ma1

School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China

Zidong Wang2

School of Information Science and Technology, Donghua University, Shanghai 200051, China; Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, UKzidong.wang@brunel.ac.uk

Yuming Bo, Zhi Guo

School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China


Ma’s work was carried out when he visited the Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex UB8 3PH, UK.


Corresponding author.

J. Dyn. Sys., Meas., Control 132(4), 044501 (Jun 15, 2010) (6 pages) doi:10.1115/1.4001276 History: Received October 09, 2008; Revised September 20, 2009; Published June 15, 2010; Online June 15, 2010

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.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Single degree-of-freedom structure with active tendon control

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Figure 2

The state responses of the uncontrolled system

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Figure 3

The state variance evolution of the controlled system



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