title: Self-organizing CMAC control for a class of MIMO uncertain nonlinear systems.
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.
authors.affiliation: Department of Electrical Engineering, Yuan Ze University, Chung-Li, Tao-Yuan 320, Taiwan. cml@saturn.yzu.edu.tw
authors.forename: Chih-Min
authors.initials: CM
authors.lastname: Lin
authors.forename: Te-Yu
authors.initials: TY
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002531:Cerebellum; D003198:Computer Simulation; D006801:Humans; D016014:Linear Models; D009038:Motion; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D013997:Time Factors; D014465:Ultrasonics; D035501:Uncertainty