Performance study of model predictive control with reference prediction for real-time hybrid simulation

TL;DR: In this paper , an improved tracking controller based on MPC controller combined with a polynomial-based forward reference prediction (MPC-RP) is proposed according to the principle of providing future data insight.

Abstract: The accuracy of real-time hybrid simulation (RTHS) is greatly influenced by the inevitable time delay and amplitude error due to the control plant dynamics. Several tracking controllers have been implemented to improve the overall performance, and among them, model predictive control (MPC) loses its prediction advantage due to the characteristic of real-time command calculation of RTHS. In this study, an improved tracking controller based on MPC controller combined with a polynomial-based forward reference prediction (MPC-RP) is proposed according to the principle of providing future data insight. First, the proposed controller is described, and the basic implementation procedure is presented. Then, validation tests were carried out to evaluate the tracking performance of the proposed controller based on the virtual RTHS benchmark problem. The results show that the MPC-RP controller has an effective delay compensation performance and a good amplitude error regulation capacity. It is also demonstrated that the MPC-RP controller has a great robust performance concerning control plant uncertainties, which ensures highly improved accuracy of RTHS.