Near-Optimal Online Control of Dynamic Discrete-Event Systems

A class of time-varying discrete-event systems, named dynamic discrete-event systems, is defined. The goal of this paper is to provide a method which is modular and can be applied in real solutions for the optimization of the online control of such systems. First, a simple control algorithm is presented, followed by illustrative examples of different issues that can arise if it is used. Afterward, a more complicated near-optimal online control algorithm with normalization of string values is proposed. The time variability of the systems is accounted for and the average computational time is drastically reduced. This is demonstrated with a set of simulations of the performance of the new algorithm.

[1]  Nejib Ben Hadj-Alouane,et al.  Variable lookahead supervisory control with state information , 1994 .

[2]  Robi Malik,et al.  Incremental verification and synthesis of discrete-event systems guided by counter examples , 2004, IEEE Transactions on Control Systems Technology.

[3]  Ratnesh Kumar,et al.  A computer implementable algorithm for the synthesis of an optimal controller for acyclic discrete event processes , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[4]  W. M. Wonham,et al.  Online supervision of discrete event systems , 2003, Proceedings of the 2003 American Control Conference, 2003..

[5]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[6]  Karen Rudie,et al.  ISSUES IN OPTIMAL CONTROL OF DYNAMIC DISCRETE-EVENT SYSTEMS , 2005 .

[7]  Ratnesh Kumar,et al.  Extension based Limited Lookahead Supervision of Discrete Event Systems , 1998, Autom..

[8]  Richard E. Korf,et al.  Depth-First Iterative-Deepening: An Optimal Admissible Tree Search , 1985, Artif. Intell..

[9]  Christos G. Cassandras,et al.  Introduction to Discrete Event Systems , 1999, The Kluwer International Series on Discrete Event Dynamic Systems.

[10]  C SIAMJ.,et al.  AN OPTIMAL CONTROL THEORY FOR DISCRETE EVENT SYSTEMS , 1998 .

[11]  Michael Heymann,et al.  On optimal attraction in discrete-event processes , 1993, Inf. Sci..

[12]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[13]  Stéphane Lafortune,et al.  Supervisory control using variable lookahead policies , 1993, 1993 American Control Conference.

[14]  Fag Lin,et al.  Robust and Adaptive Supervisory Control of Discrete Event Systems , 1992, 1992 American Control Conference.

[15]  Feng Lin,et al.  How to reuse supervisors when discrete event system models evolve , 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

[16]  F. Lin,et al.  An optimal effective controller for discrete event systems , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[17]  K. Kiriakidis,et al.  Adaptive supervisory control of interconnected discrete event systems , 2000, Proceedings of the 2000. IEEE International Conference on Control Applications. Conference Proceedings (Cat. No.00CH37162).

[18]  Lenko Grigorov Control of Dynamic Discrete-Event Systems , 2004 .

[19]  M.H. de Queiroz,et al.  Modular control of composed systems , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[20]  S. Chung,et al.  Limited lookahead policies in supervisory control of discrete event systems , 1992 .

[21]  Vijay K. Garg,et al.  Model Uncertainty in Discrete Event Systems , 1995 .

[22]  Feng Lin,et al.  On-line control of partially observed discrete event systems , 1994, Discret. Event Dyn. Syst..

[23]  Nejib Ben Hadj-Alouane,et al.  Centralized and distributed algorithms for on-line synthesis of maximal control policies under partial observation , 1996, Discret. Event Dyn. Syst..

[24]  P. Ramadge,et al.  Supervisory control of a class of discrete event processes , 1987 .

[25]  Vijay K. Garg,et al.  Optimal Supervisory Control of Discrete Event DynamicalSystems , 1995 .

[26]  Vijay K. Garg,et al.  Control of stochastic discrete event systems modeled by probabilistic languages , 2001, IEEE Trans. Autom. Control..