Identification and adaptive control for electro-hydraulic servo system using neural networks

It is reasonable for an electro-hydraulic servo system (EHSS), which is inherently nonlinear and time variable, to employ adaptive control. This paper studies neural identification and adaptive control for a practical EHSS, and designs the performance index tracker in quadratic form successfully. The optimal tracker, identification and adaptive control are simulated. The obtained results show that it is feasible for neural networks to be used for identification and adaptive control of electro-hydraulic servo systems. They can overcome the inherent nonlinearities and conduct nonlinear control in EHSS, enhance adaptability, robustness and improve stable state accuracy of the system.