Recurrent Neuro-Fuzzy Modeling and Fuzzy MDPP Control for Flexible Servomechanisms

Authors:
Chorng-Shyan Lin;Tachung Yang;Yeong-Chau Jou;Lih-Chang Lin
Affiliations:
Chung-Shan Institute of Science and Technology;Department of Mechanical Engineering, Yuan-Ze University;Department of Mechanical Engineering, National Chung Hsing University, Taiwan, R.O.C;Department of Mechanical Engineering, National Chung Hsing University, Taiwan, R.O.C
Venue:
Journal of Intelligent and Robotic Systems
Year:
2003

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Abstract

This paper considers the nonlinear system identification and control for flexible servomechanisms. A multi-step-ahead recurrent neuro-fuzzy model consisting of local linear ARMA (autoregressive moving average) models with bias terms is suggested for approximating the dynamic behavior of a servomechanism including the effects of flexibility and friction. The RLS (recursive least squares) algorithm is adopted for obtaining the optimal consequent parameters of the rules. Within each fuzzy operating region, a local MDPP (minimum degree pole placement) control law with integral action can be constructed based on the estimated local model. Then a fuzzy controller composed of these local MDPP controls can be easily constructed for the servomechanism. The techniques are illustrated using computer simulations.