Tracking Control for Petri Nets based on Monte-Carlo Tree Search

In this paper, an approach for tracking control of Petri nets based on Monte-Carlo Tree Search (MCTS) is proposed. The goal is to find a feasible firing sequence from an initial marking to a desired destination marking. The MCTS is a search algorithm based on random sampling of the search space. It has already gained interest in many game related applications. One of the best-known examples is AlphaGo. This paper shows the adaption of the MCTS algorithm to Petri nets and how MCTS can efficiently solve the tracking control problem. Additional methods for deadlock avoidance, supervisory control with forbidden markings and handling of uncontrollable transitions are shown. The proposed approach has a wide range of application like scheduling in flexible manufacturing systems or reachability analysis. An example illustrates the application of the MCTS tracking control to a flexible manufacturing system.

[1]  Alessandro Giua,et al.  Generalized mutual exclusion contraints on nets with uncontrollable transitions , 1992, [Proceedings] 1992 IEEE International Conference on Systems, Man, and Cybernetics.

[2]  Ahmed Tarek,et al.  Optimal Legal Firing Sequence of Petri Nets Using Linear Programming , 2004 .

[3]  Dimitri Lefebvre.  Near-Optimal Scheduling for Petri Net Models With Forbidden Markings , 2018, IEEE Transactions on Automatic Control.

[4]  ZhiWu Li,et al.  Local and global deadlock prevention policies for resource allocation systems using partially generated reachability graphs , 2009, Comput. Ind. Eng..

[5]  Ping Zhang,et al.  Tracking control for Petri nets with forbidden states , 2018, 2018 European Control Conference (ECC).

[6]  Zhongdong Wang,et al.  Hybrid Heuristic Search Based on Petri Net for FMS Scheduling , 2012 .

[7]  MengChu Zhou,et al.  Robust control reconfiguration of resource allocation systems with Petri nets and integer programming , 2014, Autom..

[8]  MengChu Zhou,et al.  Deadlock-Free Genetic Scheduling Algorithm for Automated Manufacturing Systems Based on Deadlock Control Policy , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[9]  Dimitri Lefebvre,et al.  Control Design for Trajectory Tracking With Untimed Petri Nets , 2015, IEEE Transactions on Automatic Control.

[10]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[11]  Simon M. Lucas,et al.  A Survey of Monte Carlo Tree Search Methods , 2012, IEEE Transactions on Computational Intelligence and AI in Games.

[12]  Ping Zhang,et al.  Fault-tolerant tracking control of petri nets , 2018, Autom..

[13]  Demis Hassabis,et al.  Mastering the game of Go with deep neural networks and tree search , 2016, Nature.

[14]  Hang Lei,et al.  Deadlock-free scheduling for flexible manufacturing systems using Petri nets and heuristic search , 2014, Comput. Ind. Eng..

[15]  Panos J. Antsaklis,et al.  Petri net supervisors for DES with uncontrollable and unobservable transitions , 2000, IEEE Trans. Autom. Control..

[16]  Yang Liu,et al.  A robust control approach to automated manufacturing systems allowing failures and reworks with Petri nets , 2017, 2017 13th IEEE Conference on Automation Science and Engineering (CASE).

[17]  Alessandro Giua,et al.  Basis Marking Representation of Petri Net Reachability Spaces and Its Application to the Reachability Problem , 2017, IEEE Transactions on Automatic Control.

[18]  Frank DiCesare,et al.  Scheduling flexible manufacturing systems using Petri nets and heuristic search , 1994, IEEE Trans. Robotics Autom..