Advanced nonlinear control for electrical drive systems

Abstract

The research project focuses on the development of advanced controllers for single and multi-dimensional servomechanisms to enhance their robustness to parameter disturbances, dynamic nonlinearities and load variations. Servomechanisms are always assumed and identified as linear systems. Friction in the system is often simplified and represented as a constant plus linear damping term in previous work. Nevertheless, highly nonlinear friction is present and it can be vital for the performance of such systems. Friction compensation technique which is usually used as a part of control scheme is firstly introduced in system identification process in the report. Moreover, the Kalman filter based radial basis function (RBF) network is designed to fit and compensate the nonlinear friction in servomechanisms. The servomechanism with nonlinear friction compensation approximates a linear system to a great extent. The proposed compensation method is simple to be applied to the servomechanisms. Compared with the math model based friction fitting method, the RBF network realizes a much better fitting error result. Correspondingly, the identified linear system model is very close to the measured frequency response data as well.