Abstract
The purpose of this study is to improve performance of hydraulic servo systems using a state feedback Neural Network and observer. It is generally not easy to acquire high control performance in hydraulic servo systems, since they have an intense non-linearity. The state feedback Neural Network compensator is one of the available options to get over this inherent problem. However, to measure the entire state variables of the actual control object is generally difficult. Using an observer is an effective method for estimating missing state variables of the control object. In this paper, a state feedback Neural Network control system with observer is proposed for improving the control performance of hydraulic servo systems under the condition of reduced state variables. At first, two Neural Network control systems with observer are designed, and they are incorporated into the hydraulic motor system. Then, the angular velocity and position control performance of the two control systems are experimentally compared to determine the optimum structure of the control system. From the experimental result, suitable structure of the Neural Network with observer is confirmed. Finally, it is clarified that the proposed Neural Network control system has excellent performance.
