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Amedeo Cesta, Alberto Finzi, Simone Fratini, Andrea Orlandini, and Enrico Tronci. "Flexible Timeline-Based Plan Verification." In KI 2009: Advances in Artificial Intelligence, 32nd Annual German Conference on AI, Paderborn, Germany, September 15-18, 2009. Proceedings, edited by B. Ã. ¤rbel Mertsching, M. Hund and M. Z. Aziz, 49–56. Lecture Notes in Computer Science 5803. Springer, 2009. ISSN: 978-3-642-04616-2. DOI: 10.1007/978-3-642-04617-9_7.
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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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"Charme." In Lecture Notes in Computer Science, edited by D. Geist and E. Tronci. Vol. 2860. Springer, 2003. ISSN: 3-540-20363-X. DOI: 10.1007/b93958.
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Marco Gribaudo, Andras Horváth, Andrea Bobbio, Enrico Tronci, Ester Ciancamerla, and Michele Minichino. "Fluid Petri Nets and hybrid model checking: a comparative case study." Int. Journal on: Reliability Engineering & System Safety 81, no. 3 (2003): 239–257. Elsevier. DOI: 10.1016/S0951-8320(03)00089-9.
Abstract: The modeling and analysis of hybrid systems is a recent and challenging research area which is actually dominated by two main lines: a functional analysis based on the description of the system in terms of discrete state (hybrid) automata (whose goal is to ascertain conformity and reachability properties), and a stochastic analysis (whose aim is to provide performance and dependability measures). This paper investigates a unifying view between formal methods and stochastic methods by proposing an analysis methodology of hybrid systems based on Fluid Petri Nets (FPNs). FPNs can be analyzed directly using appropriate tools. Our paper shows that the same FPN model can be fed to different functional analyzers for model checking. In order to extensively explore the capability of the technique, we have converted the original FPN into languages for discrete as well as hybrid as well as stochastic model checkers. In this way, a first comparison among the modeling power of well known tools can be carried out. Our approach is illustrated by means of a ’real world’ hybrid system: the temperature control system of a co-generative plant.
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V. Alimguzhin, F. Mari, I. Melatti, I. Salvo, and E. Tronci. "Linearising Discrete Time Hybrid Systems." IEEE Transactions on Automatic Control 62, no. 10 (2017): 5357–5364. ISSN: 0018-9286. DOI: 10.1109/TAC.2017.2694559.
Abstract: Model Based Design approaches for embedded systems aim at generating correct-by-construction control software, guaranteeing that the closed loop system (controller and plant) meets given system level formal specifications. This technical note addresses control synthesis for safety and reachability properties of possibly non-linear discrete time hybrid systems. By means of syntactical transformations that require non-linear terms to be Lipschitz continuous functions, we over-approximate non-linear dynamics with a linear system whose controllers are guaranteed to be controllers of the original system. We evaluate performance of our approach on meaningful control synthesis benchmarks, also comparing it to a state-of-the-art tool.
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Enrico Tronci. "Defining Data Structures via Böhm-Out." J. Funct. Program. 5, no. 1 (1995): 51–64. DOI: 10.1017/S0956796800001234.
Abstract: We show that any recursively enumerable subset of a data structure can be regarded as the solution set to a B??hm-out problem.
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Corrado Böhm, and Enrico Tronci. "About Systems of Equations, X-Separability, and Left-Invertibility in the lambda-Calculus." Inf. Comput. 90, no. 1 (1991): 1–32. DOI: 10.1016/0890-5401(91)90057-9.
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Adolfo Piperno, and Enrico Tronci. "Regular Systems of Equations in λ-calculus." Int. J. Found. Comput. Sci. 1, no. 3 (1990): 325–340. DOI: 10.1142/S0129054190000230.
Abstract: Many problems arising in equational theories like Lambda-calculus and Combinatory Logic can be expressed by combinatory equations or systems of equations. However, the solvability problem for an arbitrarily given class of systems is in general undecidable. In this paper we shall focus our attention on a decidable class of systems, which will be called regular systems, and we shall analyse some classical problems and well-known properties of Lambda-calculus that can be described and solved by means of regular systems. The significance of such class will be emphasized showing that for slight extensions of it the solvability problem turns out to be undecidable.
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Giuseppe Della Penna, Daniele Magazzeni, Alberto Tofani, Benedetto Intrigila, Igor Melatti, and Enrico Tronci. "Automated Generation of Optimal Controllers through Model Checking Techniques." In Icinco-Icso, edited by J. Andrade-Cetto, J. - L. Ferrier, J. M. C. D. Pereira and J. Filipe, 26–33. INSTICC Press, 2006. ISSN: 972-8865-59-7. DOI: 10.1007/978-3-540-79142-3.
Abstract: We present a methodology for the synthesis of controllers, which exploits (explicit) model checking techniques. That is, we can cope with the systematic exploration of a very large state space. This methodology can be applied to systems where other approaches fail. In particular, we can consider systems with an highly non-linear dynamics and lacking a uniform mathematical description (model). We can also consider situations where the required control action cannot be specified as a local action, and rather a kind of planning is required. Our methodology individuates first a raw optimal controller, then extends it to obtain a more robust one. A case study is presented which considers the well known truck-trailer obstacle avoidance parking problem, in a parking lot with obstacles on it. The complex non-linear dynamics of the truck-trailer system, within the presence of obstacles, makes the parking problem extremely hard. We show how, by our methodology, we can obtain optimal controllers with different degrees of robustness.
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