Computational Issues in Intelligent Control: Discrete-Event and Hybrid Systems

Intelligent control methodologies are being developed to address the control needs of complex systems that exhibit complicated dynamical behaviors. The design, simulation, and verification of intelligent control systems is highly nontrivial and typically involves significant amount of computations. In this paper, we identify and discuss several computational issues that are central in intelligent control. In particular, we discuss how the design, simulation, and verification of discrete-event and hybrid systems, which are central in intelligent control, requires the development of computationally efficient algorithms and approaches. Petri net models are used to describe discrete event and hybrid systems. Computational issues of various problems and algorithms concerning the analysis and synthesis of such systems are discussed. In view of hybrid systems, we also review basic computational issues for hybrid automata. Finally, we present a parallel computing architecture for intelligent control systems and we illustrate its advantages by considering parallel discrete event simulations.