Automatic Synthesis of Robust and Optimal Controllers – An Industrial Case Study

Cassez, Franck; Jessen, Jan Jakob; Larsen, Kim Guldstrand; Raskin, Jean-François; Reynier, Pierre-Alain

doi:10.1007/978-3-642-00602-9_7

Cited by 50 publications

(75 citation statements)

References 5 publications

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“…The work of Cassez et al [33] shows that controllers for industrial equipment can be synthesized using tools like UPPAAL. Through modeling the system and the requirements, a robust controller is synthesized, verified, and used in an industrial setup.…”

Section: Related Workmentioning

confidence: 99%

Optimizing schedules for adaptable manufacturing systems

Keddis

Javed

Igna

et al. 2015

2015 IEEE 20th Conference on Emerging Technologies &Amp; Factory Automation (ETFA)

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Adaptability and changeability are becoming the key features of future manufacturing. With adaptability comes a need to dynamically and frequently change factory topologies throughout the life-cycle of manufacturing systems. These changes are necessary to respond to changes in markets that result in new products, production volumes, and product variants. In addition to flexibly switching between different setups, the resulting schedules still have to be optimal to a certain extent to stay profitable. In this paper, we extend a capability-based planning approach to generate timed automata models that are used to solve the scheduling problem. The capability-based approach automatically generates an action sequence that defines all necessary production resources and operations for a product. The action sequence is then automatically transformed into models in UPPAAL -a model-checker for timed automata -and used to generate a schedule for production orders. The result can then be executed on the different production resources. An example scenario based on an industrial production system used for educational purposes shows the suitability of this approach.

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Section: Related Workmentioning

confidence: 99%

Optimizing schedules for adaptable manufacturing systems

Keddis

Javed

Igna

et al. 2015

2015 IEEE 20th Conference on Emerging Technologies &Amp; Factory Automation (ETFA)

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“…The extension of controller synthesis to timed and hybrid games started in the 90s with the seminal work of Pnueli et al [1,14] on controller synthesis for timed games where the synthesis problem was proven decidable by a symbolic dynamic programming technique. In Uppaal Tiga [2,5] an efficient on-the-fly algorithm for synthesis of reachability and safety objectives for timed games has been implemented, with a number of successful industrial applications having been made including zonebased climate control for pig-stables [12] and controllers for hydraulic pumps with 60% improvement in energy-consumption compared with industrial practice at the time [6,15].…”

Section: Introductionmentioning

confidence: 99%

Uppaal Stratego

David

Jensen

Larsen

et al. 2015

Lecture Notes in Computer Science

144

112

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Abstract. Uppaal Stratego is a novel tool which facilitates generation, optimization, comparison as well as consequence and performance exploration of strategies for stochastic priced timed games in a user-friendly manner. The tool allows for efficient and flexible "strategy-space" exploration before adaptation in a final implementation by maintaining strategies as first class objects in the model-checking query language. The paper describes the strategies and their properties, construction and transformation algorithms and a typical tool usage scenario.

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“…The objective of the Quasimodo project is to develop theory, techniques and tool components for handling quantitative (e.g. real-time, hybrid and stochastic) constraints in model-driven development of 1 The academic partners of Quasimodo are Aalborg University, Denmark (coordinator), Embedded Systems Institute, the Netherlands, Radboud University, the Netherlands, Universiteit Twente, the Netherlands, RWTH Aachen University, Germany, Saarland University, Germany, Université Libre de Bruxelles, Belgium, and ENS-Cachan/CNRS, France.…”

Section: Introductionmentioning

confidence: 99%