Hybrid control of a robotic manufacturing system

In this paper, a new approach for control of hybrid systems is introduced and illustrated using a robotic manufacturing system. Hybrid systems, which are used to model the physical process, and their controllers are viewed as system components of an intelligent control framework and they are modeled as set-dynamical systems. The central concept studied in hybrid system modeling is quasideterminism and it is used to address the problems that arise because of the nondeterministic nature of the discrete approximations of the continuous dynamics. Decision algorithms are derived based on supervisory control of discrete-event systems described by Petri nets. The notions of abstraction and multirate time scales play an important role in the design of decision algorithms to supervise the operation of the system.