An Iterative Learning Controller for Hydraulic Servo-Systems Subjected to Unknown Disturbances

Abstract

Many processes such as machining, injection-moulding and metal-forming are usually operated by hydraulic servo-systems. The dynamic characteristics of these systems are complex and highly non-linear and are often subjected to the uncertain external disturbances associated with the processes. Consequently, the conventional approach to the controller design for these systems may not guarantee accurate tracking-control performance. Taking into account the repetitive nature of the operations in those processes, a discrete iterative learning control algorithm is proposed to realize an accurate hydraulic servo-system regardless of the uncertainties and the external disturbances. In the algorithm, the control input sequence for the next operation is determined by utilizing the tracking error, as well as information on the dynamic characteristics obtained from the past operations, so that the output trajectory tracks the given the desired trajectory as closely as possible. To investigate a gradual improvement of tracking performance in consecutive operations, the proposed algorithm was implemented on a hydraulic servo-system. A series of experiments was performed for the position-tracking control of the system subjected to external disturbances. The experimental results show that, regardless of inherent non-linearities and disturbances, an accurate tracking-control performance is obtained using the proposed learning control algorithm characterized by recursive operations.