An application of explicit model predictive control to electric power assisted steering systems

Abstract

This paper presents explicit model predictive control (MPC) for electric power assisted steering (EPAS) systems. Explicit MPC has the ability to alleviate the computational burdens of MPC, which is an online optimization technique, using multi-parametric quadratic programming (mp-QP). EPAS systems are being used more frequently for passenger cars because of their advantages over hydraulic steering systems in terms of performance and cost. The main objective of EPAS systems is to provide a desired motor torque; therefore, to handle this problem, explicit MPC is employed owing to the ability of MPC to deal with constraints on controls and states and of explicit MPC to do the same work offline. This paper summarizes a formulation of explicit MPC and introduces a straight-line boost curve, which is used to determine desired motor torques. A mechanical model, motion equations and the state-space form of a column-type EPAS system are also described in this paper. An linear-quadratic regulator (LQR) controller is designed so that the explicit MPC controller could be compared against it. The parameter values are respectively varied to demonstrate the robustness of the proposed explicit MPC controller. The proposed control strategy shows better performance than that of the LQR as well as a reduction in the required computational complexity.