Intelligent planning and control for hybrid system

The analytical and robust integration of low-level system sensing and simple control with high-level system behavior and perception is critical technology in the intelligent control of modern manufacturing systems. The paper presents a novel approach by using a max-plus algebra model and a newly designed event-based planning and control scheme to provide an advanced mechanism to efficiently integrate manufacturing systems, so that task scheduling, which usually deals with discrete events, as well as action planning/control, which usually deals with continuous dynamics, can be treated in a unified analytical model. More importantly, the interactions between discrete event systems and continuous dynamics are achieved so that manufacturing systems are allowed to intelligently cope with unexpected system faults and uncertainties during well-scheduled tasks. A robotic manufacturing system is used to illustrate the proposed approach. The experimental results clearly demonstrate the advantages of the proposed approach