STOMPC: Stochastic Model-Predictive Control with Uppaal Stratego

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Abstract

We present the new co-simulation and synthesis integrated-framework STOMPC for stochastic model-predictive control (MPC) with Uppaal Stratego. The framework allows users to easily set up MPC designs, a widely accepted method for designing software controllers in industry, with Uppaal Stratego as the controller synthesis engine, which provides a powerful tool to synthesize safe and optimal strategies for hybrid stochastic systems. STOMPC provides the user freedom to connect it to external simulators, making the framework applicable across multiple domains.

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Goorden, M. A., Jensen, P. G., Larsen, K. G., Samusev, M., Srba, J., & Zhao, G. (2022). STOMPC: Stochastic Model-Predictive Control with Uppaal Stratego. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13505 LNCS, pp. 327–333). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-19992-9_21

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