A supervisory fuzzy neural network controller for slider-crank mechanism

A supervisory fuzzy neural network (FNN) controller is proposed to control a nonlinear slider-crank mechanism in this study. The control system is com posed of a permanent magnet (PM) synchronous servo motor drive coupled with a slider-crank mechanism and a supervisory FNN position controller. The su pervisory FNN controller comprises a sliding mode FNN controller and a supe rvisory controller. The sliding mode FNN controller combines the advantages of the sliding mode control with robust characteristics and the FNN with o n-line learning ability. The supervisory controller is designed to stabiliz e the system states around a defined bound region. The theoretical and stab ility analyses of the supervisory FNN controller are discussed in detail. S imulation and experimental results are provided to show that the proposed c ontrol system is robust with regard to plant parameter variations and exter nal load disturbance. (C) 2000 Elsevier Science Ltd. All rights reserved.