Compositional Optimization of Discrete Event Systems

Hagebring, Fredrik; Lennartson, Bengt

doi:10.1109/coase.2018.8560511

2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) 2018

DOI: 10.1109/coase.2018.8560511

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Compositional Optimization of Discrete Event Systems

Fredrik Hagebring

Bengt Lennartson

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Cited by 5 publications

References 18 publications

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Time-optimal control of large-scale systems of systems using compositional optimization

Hagebring

Lennartson

2019

Discrete Event Dyn Syst

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Optimization of industrial processes such as manufacturing cells can have great impact on their performance. Finding optimal solutions to these large-scale systems is, however, a complex problem. They typically include multiple subsystems, and the search space generally grows exponentially with each subsystem. In previous work we proposed Compositional Optimization as a method to solve these type of problems. This integrates optimization with techniques from compositional supervisory control, dividing the optimization into separate sub-problems. The main purpose is to mitigate the state explosion problem, but a bonus is that the individual sub-problems can be solved using parallel computation, making the method even more scalable. This paper further improves on compositional optimization with a novel synchronization method, called partial time-weighted synchronization (PTWS), that is specifically designed for time-optimal control of asynchronous systems. The benefit is its ability to combine the behaviour of asynchronous subsystems without introducing additional states or transitions. The method also reduces the search space further by integrating an optimization heuristic that removes many nonoptimal or redundant solutions already during synchronization. Results in this paper show that compositional optimization efficiently generates global optimal solutions to large-scale realistic optimization problems, too big to solve when based on traditional monolithic models. It is also shown that the introduction of PTWS drastically decreases the total search space of the optimization compared to previous work.

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Time-optimal control of large-scale systems of systems using compositional optimization

Hagebring

Lennartson

2019

Discrete Event Dyn Syst

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Hierarchical planning in a supervisory control context with compositional abstraction

Vilela

Hill

2021

Discrete Event Dyn Syst

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Hierarchy is a tool that has been applied to improve the scalability of solving planning problems modeled using Supervisory Control Theory. In the work of Hill and Lafortune (2016), the notion of cost equivalence was employed to generate an abstraction of the supervisor that, with additional conditions, guarantees that an optimal plan generated on the abstraction is also optimal when applied to the full supervisor. Their work is able to improve their abstraction by artificially giving transitions zero cost based on the sequentially-dependent ordering of events. Here, we relax the requirement on a specific ordering of the dependent events, while maintaining the optimal relationship between upper and lower levels of the hierarchy. This present paper also extends the authors’ work (Vilela and Hill 2020) where we developed a new notion of equivalence based on cost equivalence and weak bisimulation that we term priced-observation equivalence. This equivalence allows the supervisor abstraction to be generated compositionally. This helps to avoid the explosion of the state space that arises from having to first synthesize the full supervisor before the abstraction can be applied. Here, we also show that models with artificial zero-cost transitions can be created compositionally employing the new relaxed sequential dependence definition. An example cooperative robot control application is used to demonstrate the improvements achieved by the compositional approach to abstraction proposed by this paper.

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A Compositional Approach to Abstraction for Planning Problems

Vilela

Hill

2020

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Compositional Optimization of Discrete Event Systems

Cited by 5 publications

References 18 publications

Time-optimal control of large-scale systems of systems using compositional optimization

Time-optimal control of large-scale systems of systems using compositional optimization

Hierarchical planning in a supervisory control context with compositional abstraction

A Compositional Approach to Abstraction for Planning Problems

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