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Silvia Mazzini, Stefano Puri, Federico Mari, Igor Melatti, and Enrico Tronci. "Formal Verification at System Level." In In: DAta Systems In Aerospace (DASIA), Org. EuroSpace, Canadian Space Agency, CNES, ESA, EUMETSAT. Instanbul, Turkey, EuroSpace., 2009.
Abstract: System Level Analysis calls for a language comprehensible to experts with different background and yet precise enough to support meaningful analyses. SysML is emerging as an effective balance between such conflicting goals. In this paper we outline some the results obtained as for SysML based system level functional formal verification by an ESA/ESTEC study, with a collaboration among INTECS and La Sapienza University of Roma. The study focuses on SysML based system level functional requirements techniques.
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Amedeo Cesta, Alberto Finzi, Simone Fratini, Andrea Orlandini, and Enrico Tronci. "Flexible Plan Verification: Feasibility Results." In 16th RCRA International Workshop on “Experimental evaluation of algorithms for solving problems with combinatorial explosion” (RCRA). Proceedings., 2009.
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Andrea Bobbio, Ester Ciancamerla, Michele Minichino, and Enrico Tronci. "Functional analysis of a telecontrol system and stochastic measures of its GSM/GPRS connections." Archives of Transport – International Journal of Transport Problems 17, no. 3-4 (2005).
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Corrado Böhm, Adolfo Piperno, and Enrico Tronci. "Solving Equations in λ-calculus." In Proc. of: Logic Colloquium 88. Padova - Italy, 1989.
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Corrado Böhm, and Enrico Tronci. "X-Separability and Left-Invertibility in lambda-calculus." In Symposium on Logic in Computer Science (LICS), 320–328. Ithaca, New York, USA: IEEE Computer Society, 1987.
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Corrado Böhm, and Enrico Tronci. "X-separability and left-invertibility in the λ-calculus (extended abstract, invited paper)." In Proceedings of: Temi e prospettive della Logica e della Filosofia della Scienza contemporanea. Cesena - Italy, 1987.
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Enrico Tronci. "On Computing Optimal Controllers for Finite State Systems." In CDC '97: Proceedings of the 36th IEEE International Conference on Decision and Control. Washington, DC, USA: IEEE Computer Society, 1997.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Linear Constraints as a Modeling Language for Discrete Time Hybrid Systems." In Proceedings of ICSEA 2012, The Seventh International Conference on Software Engineering Advances, 664–671. ThinkMind, 2012.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Control Software Visualization." In Proceedings of INFOCOMP 2012, The Second International Conference on Advanced Communications and Computation, 15–20. ThinkMind, 2012. ISSN: 978-1-61208-226-4.
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. A Map-Reduce Parallel Approach to Automatic Synthesis of Control Software. Vol. abs/1210.2276. CoRR, Technical Report, 2012. http://arxiv.org/abs/1210.2276 (accessed May 6, 2024).
Abstract: Many Control Systems are indeed Software Based Control Systems, i.e. control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of control software.
Available algorithms and tools (e.g., QKS) may require weeks or even months of computation to synthesize control software for large-size systems. This motivates search for parallel algorithms for control software synthesis.
In this paper, we present a map-reduce style parallel algorithm for control software synthesis when the controlled system (plant) is modeled as discrete time linear hybrid system. Furthermore we present an MPI-based implementation PQKS of our algorithm. To the best of our knowledge, this is the first parallel approach for control software synthesis.
We experimentally show effectiveness of PQKS on two classical control synthesis problems: the inverted pendulum and the multi-input buck DC/DC converter. Experiments show that PQKS efficiency is above 65%. As an example, PQKS requires about 16 hours to complete the synthesis of control software for the pendulum on a cluster with 60 processors, instead of the 25 days needed by the sequential algorithm in QKS.
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