Paper Info
Title
State variance constrained fuzzy controller design for nonlinear TORA systems with minimizing control input energy
Abstract
This paper presents a model-based fuzzy control of translational oscillations with a proof mass actuator (TORA), which is well known as a nonlinear control benchmark problem. In this paper, the nonlinear TORA system is modeled by the Takagi-Sugeno (T-S) fuzzy stochastic system. For this TS type fuzzy model, we design the T-S fuzzy controller which not only ensure the stability of the closed-loop system, but also minimize the control input energy with state variance constraints. The present method uses Linear Matrix Inequalities (LMI) approach to find the common positive definite covariance matrix and feedback gains for each rule of the TORA TS fuzzy stochastic systems.
Year
DOI
Venue
2003
10.1109/ROBOT.2003.1241987
ICRA
Keywords
Field
DocType
lmi,feedback gains,nonlinear control,control input energy minimization,stochastic systems,takagi-sugeno fuzzy stochastic system,control system synthesis,translational oscillations,closed loop system,proof mass actuator,state variance,nonlinear control systems,linear matrix inequalities,fuzzy control,stability,closed loop systems,covariance matrix,nonlinear tora systems,positive definite,oscillations,linear matrix inequality
Control theory,Mathematical optimization,Nonlinear system,Nonlinear control,Control theory,Matrix (mathematics),Fuzzy logic,Control engineering,Fuzzy control system,Covariance matrix,Fuzzy number,Mathematics
Conference
Volume
Issue
ISSN
2
1
1050-4729
ISBN
Citations 
PageRank 
0-7803-7736-2
7
0.69
References 
Authors
5
2
Name
Order
Citations
PageRank
Wen-Jer Chang117522.68
Sheng-Ming Wu2143.14