Robust deadlock control in automated manufacturing systems with unreliable resources based on an algebraic way

Abstract

In automated manufacturing systems (AMSs), because of unpredictable failures, resources can lose functions such that the deadlock control methods, in existence, are invalidated. In this paper, a robust deadlock control approach is proposed for AMSs with multiple unreliable resources. The considered AMSs modelled by Petri nets (PNs) allow to acquire different types of resources at each processing stage. In order to visualise the fact that resource failures occur in AMSs, recovery subnets are designed for the modelling AMSs to depict the failures and recoveries of resources. Based on a siphon detection method performed by a set of integer linear programming formulations, a control specification is proposed. Control places (monitors) with their control variables are designed for the detected unmarked siphons at a marking to guarantee that they are always marked even if some unreliable resources break down. Iteratively, all unmarked siphons are detected and controlled. Therefore, a robust deadlock supervisor is synthesised to ensure the controlled system's liveness no matter there exist resource failures or not. The theoretical analyses and proof are given to verify the correctness of the proposed method. Finally, the comparative studies are presented to expound the proposed method's effectiveness and efficiency.

Keywords:

• Automated manufacturing systems (AMSs)
• linear programming
• siphon detection
• Petri nets
• robust deadlock control

Acknowledgments

The authors would like to thank the editor, associate editor, and all anonymous reviewers for their thoughtful comments and suggestions that greatly helped improve the presentation and technical quality of this paper.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article and/or its supplementary materials.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work has been supported by the National Natural Science Foundation of China [grant numbers 62103039 and 61973242], and the Fundamental Research Funds for the China Central Universities of USTB [grant number FRF-TP-20-107A1].

Notes on contributors

Nan Du

Nan Du received his B.S degree in measurement and control technology and instrumentation from Xi'an University of Architecture and Technology, Xi'an, Shaanxi, China, in 2014 and Ph.D degree in control theory and control engineering from Xidian University, Xi'an, China, in 2020. He is currently a lecture at the school of electrical and information engineering, Lanzhou University of Technology. His research interests include discrete event systems and their supervisory control techniques, Petri nets, automated manufacturing systems, and robust supervisory control. He was a recipient of the Best Automation Paper Award-Finalist of the 2016 IEEE International Conference on Robotics and Automation.

Yan Yang

Yan Yang received her B.S degree in automation from Xi'an University of Science and Technology, Xi'an, China, in 2012, and her Ph.D. degree in control theory and control engineering form Xidian University, Xi'an, China, in 2019. She is currently a Lecture at the Institute of Artificial Intelligence, University of Science and Technology Beijing. In 2016, she was a Research Assistant with the Department of Electrical Engineering, University of Notre Dame, for 12 months. Her current research interests include discrete event systems and their supervisory control techniques, Petri nets, intelligent control for robots.

Hesuan Hu

Hesuan Hu (M'11–SM'12) received the BS degree in computer engineering and the M.S and Ph.D degrees in electro-mechanical engineering from Xidian University, Xi'an, China, in 2003, 2005, and 2010, respectively. He is currently a professor with Xidian University and also with Nanyang Technological University, Singapore, and a researcher with Xi'an Jiaotong University, Xi'an. He is a holder of more than 30 issued and filed patents in his fields of expertise. His current research interests include discrete event systems and their supervisory control techniques, Petri nets, automated manufacturing systems, multimedia streaming systems, autonomous vehicles, cyber security, and artificial intelligence. He has more than 140 publications in journals, book chapters, and conference proceedings in the above areas. He was a recipient of the many national and international awards, including the Franklin V. Taylor Memorial Award for Outstanding Papers from the IEEE SMC Society in 2010 and the finalists of the Best Automation Paper from the IEEE ICRA Society in 2013, 2016, and 2017. He has been an associate editor of the IEEE Control Systems Magazine, IEEE Robotics, and Automation Magazine, IEEE Transactions on Automation Science and Engineering, and Journal of Intelligent Manufacturing. He was on the editorial board over 10 international journals.