An Adaptive Control Using Multiple Neural Networks for the Position Control in Hydraulic Servo System

A model following adaptive control based on neural network for the electro-hydraulic servo system (EHSS) subjected to varied load is proposed. This proposed control utilizes multiple neural networks including a neural controller, a neural emulator and a neural tuner. The neural controller with specialized learning architecture utilizes a linear combination of error and the error's derivative to approximate the back propagation error for weights update. The neural tuner is designed to adjust the parameters of the linear combination. The neural emulator is used to approximate the Jacobian of plant. The control of the hydraulic servo actuator is investigated by simulation and experiment, and a favorable model-following characteristic is achieved.

[1]  Sigeru Omatu,et al.  Self-tuning neuro-PID control and applications , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[2]  Michifumi Yoshioka,et al.  Neuro-PID control for inverted single and double pendulums , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[3]  Wu Pingdong,et al.  A fuzzy neural network controller in the electrohydraulic position control system , 1997, 1997 IEEE International Conference on Intelligent Processing Systems (Cat. No.97TH8335).

[4]  Yao Zhang,et al.  An on-line trained adaptive neural controller , 1995 .

[5]  Faa-Jeng Lin,et al.  Hybrid controller using a neural network for a PM synchronous servo-motor drive , 1998 .

[6]  Ming-Hui Chu,et al.  Model-Following Controller Based on Neural Network for Variable Displacement Pump , 2003 .

[7]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.