Title :
Adaptive Fast Terminal Sliding Mode Control for a Class of Uncertain System
Author :
Min Jianqing ; Fang Yingguo ; Xu Zibin
Author_Institution :
Coll. of Biol. & Environ. Eng., Zhejiang Shuren Univ., Hangzhou, China
Abstract :
Based on neural networks, an adaptive fast terminal sliding mode (FTSM) control strategy is presented for a class of high-order uncertain nonlinear system. The radial basis function (RBF) neural network is used to online approach uncertainties of system. The mathematical relationship between the neighborhood of each sliding mode surface and the system uncertainty is derived. It is strictly proved that the system tracking error can reach to a very small region in finite time, and the robustness of the controller is established using the Lyapunov stability theory. Theoretical analysis and simulation results show the good tracking performance of the designed controller.
Keywords :
Lyapunov methods; adaptive control; control system synthesis; neurocontrollers; nonlinear control systems; radial basis function networks; robust control; tracking; uncertain systems; variable structure systems; Lyapunov stability theory; RBF; adaptive fast terminal sliding mode control; control design; high-order uncertain nonlinear system; radial basis function neural network; robust control; system tracking error; Adaptive control; Adaptive systems; Control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Sliding mode control; Uncertain systems; Uncertainty; FTSM; adaptive control; neural networks; uncertain nonlinear system;
Conference_Titel :
Industrial and Information Systems, 2009. IIS '09. International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-3618-7
DOI :
10.1109/IIS.2009.17
