Nonlinear Model Predictive Motion Control of Linear Motor Drive for Micro/Nano-Positioning Applications

Abstract

This paper presents an offset-free nonlinear model predictive controller (NMPC) for linear motor drive system which have been proposed to address the challenges of their rotary counterparts in precision linear motion control. The main challenges associated with the linear motors is that they are more sensitive to disturbances and parameter variations. The frictional force which affects the drive system is nonlinear and discontinuous. Since it is not possible to generate a discontinuous motor force to achieve desired tracking control, a continuous friction model is used to approximate the actual discontinuous friction model. Extant studies [1], [2] proposed predictive control of linear motors but focused on positioning in the meter range. Here, we propose an offset-free NMPC for micro-positioning applications in which the unmodelled nonlinear functions and the external disturbances are modelled as the integrating disturbance state that is estimated using an extended Kalman filter while the inherent robustness of NMPC is relied on to handle the parametric uncertainties. Numerical simulations are used to show the effectiveness of NMPC in controlling the linear drive system for precise motion tracking in the micrometer range.