Intelligent control: analytical integration of hybrid system

This paper presents a novel approach for solving the grand challenging problem in intelligent control, i.e. the analytical and robust integration of low-level system sensing and simple control with high-level system behavior and perception. The proposed max-plus algebra model combined with event-based planning and control provides an advanced mechanism to efficiently integrate task scheduling, sensing, planning and real-time execution so that task scheduling, which usually deals with discrete events, as well as action planning, which usually deals with continuous events, can be treated in a unified analytical model, and the design of task synchronization becomes much easier. More importantly, the state-of-art characteristic of this approach is that interactions between discrete and continuous events can be considered in a unified framework. This characteristic allows an automated system to intelligently cope with unexpected events and uncertainties during well-scheduled tasks so that the efficiency and reliability of the task schedule and action synchronization can increase significantly. A robotic manufacturing system is used to illustrate the proposed approach. The experimental results clearly demonstrate the advantages of the proposed approach