TY - JOUR
T1 - A Survey on Robust Deadlock Control Policies for Automated Manufacturing Systems with Unreliable Resources
AU - Du, Nan
AU - Hu, Hesuan
AU - Zhou, Mengchu
N1 - Funding Information:
Manuscript received January 21, 2019; revised May 26, 2019; accepted June 24, 2019. Date of publication September 9, 2019; date of current version January 9, 2020. This article was recommended for publication by Associate Editor L. Zhang and Editor Y. Ding upon evaluation of the reviewers’ comments. This work was supported in part by the National Natural Science Foundation of China under Grant 61203037, Grant 51305321, Grant 61573265, and Grant 61973242, in part by the Fundamental Research Funds for the Central Universities under Grant K7215581201, Grant K5051304021, and Grant K5051304004, in part by the New Century Excellent Talents in University under Grant NCET-12-0921, in part by the Major Fundamental Research Program of the Natural Science Foundation of Shaanxi Province under Grant 2017ZDJC-34, in part by the Academic Research Fund Tier 1 by Ministry of Education in Singapore under Grant 2014-T1-001-147, and in part by the Academic Research Fund Tier 2 by Ministry of Education in Singapore under Grant MOE2015-T2-2-049. (Corresponding Author: Hesuan Hu.) N. Du is with the School of Electro-Mechanical Engineering, Xidian University, Xi’an 710071, China (e-mail: dun@stu.xidian.edu.cn).
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - Deadlock is a rather undesirable case in automated manufacturing systems (AMSs). The appearance of deadlock can cause the partial or total stagnation of a system. So far, a large number of deadlock control policies have been developed; nevertheless, the majority are dependent on the assumption that allocated resources cannot break down. In the real world, an AMS consists of a set of concurrent production routes that share and compete for a limited number of resources, such as automated material/component handling devices, buffers, robots, and machines. Resource failures occur unexpectedly. If reasonable control does not exist, a simple resource failure can lead an entire system to stagnation, which can cause enormous economic loss. Therefore, researchers have gradually paid attention to AMSs allowing resource failures in recent years. In this paper, we focus on reviewing and comparing various robust supervisory control policies from the perspective of their structural complexity, behavioral permissiveness, and computational complexity. Some potential future directions are explored. This paper provides a reference source of robust supervisory control of AMSs for researchers and practitioners in this area. Note to Practitioners - In automated manufacturing systems (AMSs), resource failures are common. Their occurrences can lead a system to stagnation, which can cause unnecessary downtime and bring vast economic loss for enterprises. To resolve such stagnation issues, a great number of robust supervisory control policies have been proposed for AMSs with unreliable resources. These policies guarantee that a controlled system can continue to progress without deadlock and blocking states even if some unreliable resources fail to work. By a thorough review of existing robust supervisory control policies for AMSs with unreliable resources, this paper compares and analyzes these policies in terms of their structural complexity, behavioral permissiveness, and computational complexity. The goal of this paper is to provide a reference source in the area to help researchers and practitioners choose a suitable method for solving industrial application problems that are subject to resource failures.
AB - Deadlock is a rather undesirable case in automated manufacturing systems (AMSs). The appearance of deadlock can cause the partial or total stagnation of a system. So far, a large number of deadlock control policies have been developed; nevertheless, the majority are dependent on the assumption that allocated resources cannot break down. In the real world, an AMS consists of a set of concurrent production routes that share and compete for a limited number of resources, such as automated material/component handling devices, buffers, robots, and machines. Resource failures occur unexpectedly. If reasonable control does not exist, a simple resource failure can lead an entire system to stagnation, which can cause enormous economic loss. Therefore, researchers have gradually paid attention to AMSs allowing resource failures in recent years. In this paper, we focus on reviewing and comparing various robust supervisory control policies from the perspective of their structural complexity, behavioral permissiveness, and computational complexity. Some potential future directions are explored. This paper provides a reference source of robust supervisory control of AMSs for researchers and practitioners in this area. Note to Practitioners - In automated manufacturing systems (AMSs), resource failures are common. Their occurrences can lead a system to stagnation, which can cause unnecessary downtime and bring vast economic loss for enterprises. To resolve such stagnation issues, a great number of robust supervisory control policies have been proposed for AMSs with unreliable resources. These policies guarantee that a controlled system can continue to progress without deadlock and blocking states even if some unreliable resources fail to work. By a thorough review of existing robust supervisory control policies for AMSs with unreliable resources, this paper compares and analyzes these policies in terms of their structural complexity, behavioral permissiveness, and computational complexity. The goal of this paper is to provide a reference source in the area to help researchers and practitioners choose a suitable method for solving industrial application problems that are subject to resource failures.
KW - Automated manufacturing system (AMS)
KW - deadlock control
KW - resource failure
KW - robust supervisory control
UR - http://www.scopus.com/inward/record.url?scp=85074834818&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074834818&partnerID=8YFLogxK
U2 - 10.1109/TASE.2019.2926758
DO - 10.1109/TASE.2019.2926758
M3 - Article
AN - SCOPUS:85074834818
SN - 1545-5955
VL - 17
SP - 389
EP - 406
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 1
M1 - 8827303
ER -