Title :
Self-Organizing CMAC Control for a Class of MIMO Uncertain Nonlinear Systems
Author :
Lin, Chih-Min ; Chen, Te-Yu
Author_Institution :
Dept. of Electr. Eng., Yuan Ze Univ., Chungli, Taiwan
Abstract :
This paper presents a self-organizing control system based on cerebellar model articulation controller (CMAC) for a class of multiple-input-multiple-output (MIMO) uncertain nonlinear systems. The proposed control system merges a CMAC and sliding-mode control (SMC), so the input space dimension of CMAC can be simplified. The structure of CMAC will be self-organized; that is, the layers of CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The control system consists of a self-organizing CMAC (SOCM) and a robust controller. SOCM containing a CMAC uncertainty observer is used as the principal controller and the robust controller is designed to dispel the effect of approximation error. The gradient-descent method is used to online tune the parameters of CMAC and the Lyapunov function is applied to guarantee the stability of the system. A simulation study of inverted double pendulums system and an experimental result of linear ultrasonic motor motion control show that favorable tracking performance can be achieved by using the proposed control system.
Keywords :
Lyapunov methods; MIMO systems; cerebellar model arithmetic computers; gradient methods; neurocontrollers; nonlinear systems; robust control; self-adjusting systems; uncertain systems; variable structure systems; CMAC uncertainty observer; Lyapunov function; MIMO uncertain nonlinear system; cerebellar model articulation controller; gradient descent method; inverted double pendulums system; linear ultrasonic motor motion control; multiple input multiple output system; robust controller; self-organizing CMAC control; self-organizing control system; sliding mode control; Cerebellar model articulation controller (CMAC); Lyapunov stability theorem; gradient-descent method; self-organizing; uncertain nonlinear systems; Algorithms; Artificial Intelligence; Cerebellum; Computer Simulation; Humans; Linear Models; Motion; Neural Networks (Computer); Nonlinear Dynamics; Normal Distribution; Time Factors; Ultrasonics; Uncertainty;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2009.2013852
