Title :
NN robustness design of nonlinear structure systems
Author :
Yeh, K. ; Chen, C.W. ; Chen, C.Y.
Author_Institution :
Dept. of Civil Eng., De-Lin Inst. of Technol., Taipei
Abstract :
The neural-network (NN) model is adopted to overcome the modeling error problem of nonlinear systems. According to the controlled system, the H infinity criterion is derived based on the Lyapunov method. Based on the stability criterion, the nonlinear systems are guaranteed to be stable. The control problem can be reformulated into the linear matrix inequality (LMI) problem.
Keywords :
Hinfin control; Lyapunov methods; linear matrix inequalities; neurocontrollers; nonlinear control systems; stability; H infinity criterion; Lyapunov method; linear matrix inequality; neural-network; nonlinear structure system; stability criterion; Control systems; Fuzzy control; Fuzzy systems; Linear matrix inequalities; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Robustness; Stability criteria; NN-based approach; T-S fuzzy systems;
Conference_Titel :
SICE Annual Conference, 2008
Conference_Location :
Tokyo
Print_ISBN :
978-4-907764-30-2
Electronic_ISBN :
978-4-907764-29-6
DOI :
10.1109/SICE.2008.4654752
