Model predictive control of hybrid systems with applications to supply chain management

摘要: Hybrid systems are dynamical whose behavior is determined by the interaction of continuous and discrete dynamics. Such arise in many real contexts, including automotive systems, chemical processes, communication networks, supply chain management. A chain, goal to transform ideas raw materials into delivered products services, an example a heterogeneous interconnection between dynamics (inventory levels, material flows, etc.) (connection graphs, precedences, priorities, etc.). In general, order maximize certain benefit or minimize costs, we have optimally control all components hybrid system. Model predictive (MPC) well-known technique used industry (sub)optimally usually based on linear models. This paper presents overview MPC techniques for systems. After giving brief introduction system models, model control, standard computation techniques, summarizes recent results using symbolic event-based formulations that exploit particular structure process come up with improved numerical schemes. The concepts illustrated through application examples centralized management chains.