COMPACTLY SUPPORTED RADIAL BASIS FUNCTIONS FOR ADAPTIVE PROCESS-CONTROL

An adaptive nonlinear control strategy based on networks of compactly supported radial basis functions is proposed. The local influence of t he basis functions allows efficient on-line adaptation that is perform ed using a gradient law, and new basis functions are added to the netw ork only when new regions in state space are encountered and the predi ction error exceeds a pre-specified tolerance. The approximate model i s used to construct an input-output linearizing control law. The adapt ive control strategy is applied to a nonlinear chemical reactor model. (C) 1997 Published by Elsevier Science Ltd.