Control Design of Elementary Hybrid Petri Nets via Model Predictive Control

This paper addresses the control design of Hybrid Dynamic Systems (HDS) modeled by Hybrid Petri Net (HPN) systems. The resolution of the problem is based on Model Predictive Control (MPC). Our goal is to drive a HPN to reach a desired marking. Since HDS incorporates both discrete and continues processes, the proposed control strategy, called Hybrid Predictive Control, is composed of a discrete and a continuous predictive control. At each sampling period, the discrete predictive control selects a set of feasible sequences constituted of discrete immediate enabled transitions, while the continuous procedure computes the continuous constant control action over a variable prediction horizon.