Offset-free energy-optimal model predictive control for point-to-point motions with high positioning accuracy

Abstract

This paper discusses Offset-free Energy-optimal Model Predictive Control (offset-free EOMPC) which is a MPC algorithm to realize time-constrained energy-optimal point-topoint motion control with high positioning accuracy for linear time-invariant (LTI) systems. The offset-free EOMPC approach is developed based on our previous research -Energy-optimal Model Predictive Control (EOMPC) -which aims at performing energy-optimal point-to-point motions within a given motion time. A drawback of the EOMPC method is that it cannot achieve high positioning accuracy in the presence of unmodelled disturbances or model-plant mismatch. In order to cope with this problem, a 'disturbance model' strategy is adopted: the system state is augmented with disturbance variables. Based on the 'disturbance model', the disturbances are estimated and the effect of which is cancelled. Numerical validation of the offsetfree EOMPC using a model of a linear motor with coulomb friction and cogging disturbances has been performed and the results show that time-constrained energy-optimal pointto-point motion with high positioning accuracy is achieved.