Improved Model Predictive Control of Discrete-Time Hybrid Systems with Mixed Inputs

Abstract

This paper suggests an improved method for predictive control of hybrid systems with mixed inputs. The algorithm takes into account the real nonlinear system as a model of a hybrid system, which is based on building a tree of evolution. Where the branch & bound (B&B) technique is applied for discrete controls in which an embedded nonlinear programming approach (Pattern search) is associated with each node of the tree in order to provide the continuous controls and explore the tree. Once the whole nodes of the tree are explored, the corresponding input is exploited to the system and the procedure is repeated. The performance of the resulting predictive control system is demonstrated on a motorboat simulation case study.