Identification and control of nonlinear servo system

Abstract

The paper is focused on identification and control of nonlinear servo system Amira DR300. The identification is performed using a black box approach. Several types of nonlinearities, which are present in the servo system, are described and presented. Results of several identification methods are compared and combined to obtain an optimal model for control design. The control algorithm is designed to cope with disturbance while respecting low expenses required for hardware and software equipments. A suboptimal control of a nonlinear servo system is proposed in the contribution. It is based on polynomial theory and was applied to laboratory servo system in realtime conditions.