Designing a novel structure of explicit model predictive control with application in a buck converter system

This paper proposes a novel structure of model predictive control algorithm for piecewise affine systems as a particular class of hybrid systems. Due to the time consuming and computational complexity of online optimization problem in MPC algorithm, the explicit form of MPC which is called Explicit MPC (EMPC) is applied in order to control of buck converter. Since the EMPC solves the optimization problem only once and in offline manner, this strategy is suitable for hybrid systems with fast dynamics. As opposed to typical EMPC that is uses only the first element of optimal input vector, the proposed strategy uses all entries of the control sequence with optimal weighting factors. In proposed EMPC, two separate optimization problems are solved at each algorithm step. The first one is related to EMPC optimization problem and the second optimization problem is concerned to finding optimal weighting factors so as to minimize the error signal at each step. The convergence property of the proposed EMPC towards to the desired value has been proved and the simulation results shows the better performance of the proposed EMPC strategy than the typical one, if the weighting factors and control horizons are adjusted properly.