Supervisor synthesis and throughput optimization of partially-controllable manufacturing systems
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Supervisor synthesis and throughput optimization of partially-controllable manufacturing systems Berend Jan Christiaan van Putten1 · Bram van der Sanden1,2 · Michel Reniers1 Jeroen Voeten1,2 · Ramon Schiffelers1,3
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Received: 24 June 2018 / Accepted: 23 August 2020 / © The Author(s) 2020
Abstract One of the challenges in the design of supervisors with optimal throughput for manufacturing systems is the presence of behavior outside the control of the supervisor. Uncontrollable behavior is typically encountered in the presence of (user) inputs, external disturbances, and exceptional behavior. This paper introduces an approach for the modeling and synthesis of a throughput-optimal supervisor for manufacturing systems with partially-controllable behavior on two abstraction levels. Extended finite automata are used to model the high abstraction level in terms of system activities, where uncontrollability is modeled by the presence of uncontrollable activities. In the lower abstraction level, activities are modeled as directed acyclic graphs that define the constituent actions and dependencies between them. System feedback from the lower abstraction level, including timing, is captured using variables in the extended finite automata of the higher abstraction level. For throughput optimization, game-theoretic methods are employed on the state space of the synthesized supervisor to determine a guarantee to the lower-bound system performance. This result is also used in a new method to automatically compute a throughput-optimal controller that is robust to the uncontrollable behavior. Keywords Supervisory control · Throughput-optimal controller · Uncontrollable behaviour
1 Introduction Over the past decades, increasing complexity of manufacturing systems has driven the development of model-based systems engineering (MBSE) and supervisory control methods to aid in the design process (Estefan 2008; Steimer et al. 2017). Executable models created by these methods allow engineers to test and adjust the system before it is built. This
This article belongs to the Topical Collection: Topical Collection on Smart Manufacturing - A New DES Frontier Guest Editors: Rong Su and Bengt Lennartson Michel Reniers
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Discrete Event Dynamic Systems
increases design flexibility and reduces time-to-market, and has the potential to improve system performance. In controller design, the developed models can be used for automatic generation of supervisory controllers using controller synthesis techniques (Baeten et al. 2016). These controllers must ensure functional correctness with respect to the specifications, and provide optimal control decisions in terms of relevant performance criteria. A challenge in the construction and analysis of models in these methods is the inclusion of system behavior outside the influence of the controller. For example, products may enter the manufacturing system with varying time intervals, or actions on a different con
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