Title :
The tracking controller of complex nonlinear systems
Author :
Qu Zifang ; Du Zhenbin
Author_Institution :
Shandong Inst. of Bus. & Technol., Coll. of Math. & Inf. Sci., Yantai, China
Abstract :
The output feedback control problem is considered for a class of nonlinear systems with unknown states and time delays, and under uncertainties. Fuzzy Takagi-Sugeno (T-S) models are used to approximate the nonlinear system, and RBF neural networks (NNs) act as a compensator to eliminate the approximating error and the uncertainties. The controller is designed to ensure that the closed-loop system satisfies the desired tracking performance. Simulation results demonstrate the effectiveness of the developed control scheme.
Keywords :
closed loop systems; compensation; control system synthesis; delays; feedback; neurocontrollers; nonlinear systems; radial basis function networks; tracking; RBF neural networks; closed loop system; compensator; complex nonlinear systems; fuzzy Takagi-Sugeno models; output feedback control problem; time delays; tracking controller design; tracking performance; unknown states; Approximation methods; Artificial neural networks; Nonlinear systems; Output feedback; Simulation; Uncertainty; Vectors; RBF NNs; fuzzy T-S model; nonlinear systems; time delays; tracking control; uncertainties;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
