Neural network based adaptive I-PD controller for pneumatic cylinder

Abstract

This paper describes a method of self-tuning the I-PD controller for pneumatic cylinder using neural networks. As it is well known I-PD controllers are widely used for process control, because they have good performance. However, it is very difficult to determine I-PD gains in case of controlled object with deadtime. Here, we propose a self-tuning I-PD controller and show the simulation and experimental results to demonstrate the effectiveness of our method.