Title :
Predictive sliding mode controller design for nonlinear systems
Author :
Moeini, A. ; Nariman-Zadeh, N. ; Hajiloo, A. ; Samadi, M. ; Barootiha, A.
Author_Institution :
Dept. of Eng. Sci., Univ. of Tehran, Tehran, Iran
Abstract :
In this paper, a new method is proposed to design a sliding mode controller with variable boundary layer for a nonlinear system. In this method, model predictive control (MPC) is used to predict the future boundary layer thickness. In order to predict the behavior of the nonlinear system, a neural network model is used as an internal model. The simulation results show the supremacy of this method in comparison with the conventional method.
Keywords :
control system synthesis; neurocontrollers; nonlinear control systems; predictive control; variable structure systems; model predictive control; neural network model; nonlinear systems; sliding mode controller design; variable boundary layer; Artificial neural networks; Nonlinear systems; Predictive control; Predictive models; Simulation; Trajectory; boundary layer thickness; model predicte control; nonlinear systems; sliding mode control;
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-1-61284-919-5
DOI :
10.1109/INISTA.2011.5946048
