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Benedetto Intrigila, Daniele Magazzeni, Igor Melatti, and Enrico Tronci. "A Model Checking Technique for the Verification of Fuzzy Control Systems." In CIMCA '05: Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06), 536–542. Washington, DC, USA: IEEE Computer Society, 2005. ISSN: 0-7695-2504-0-01. DOI: 10.1109/CIMCA.2005.1631319.
Abstract: Fuzzy control is well known as a powerful technique for designing and realizing control systems. However, statistical evidence for their correct behavior may be not enough, even when it is based on a large number of samplings. In order to provide a more systematic verification process, the cell-to-cell mapping technology has been used in a number of cases as a verification tool for fuzzy control systems and, more recently, to assess their optimality and robustness. However, cell-to-cell mapping is typically limited in the number of cells it can explore. To overcome this limitation, in this paper we show how model checking techniques may be instead used to verify the correct behavior of a fuzzy control system. To this end, we use a modified version of theMurphi verifier, which ease the modeling phase by allowing to use finite precision real numbers and external C functions. In this way, also already designed simulators may be used for the verification phase. With respect to the cell mapping technique, our approach appears to be complementary; indeed, it explores a much larger number of states, at the cost of being less informative on the global dynamic of the system.
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Giuseppe Della Penna, Daniele Magazzeni, Alberto Tofani, Benedetto Intrigila, Igor Melatti, and Enrico Tronci. "Automatic Synthesis of Robust Numerical Controllers." In Icas '07, 4. IEEE Computer Society, 2007. ISSN: 0-7695-2859-5. DOI: 10.1109/CONIELECOMP.2007.59.
Abstract: A major problem of numerical controllers is their robustness, i.e. the state read from the plant may not be in the controller table, although it may be close to some states in the table. For continuous systems, this problem is typically handled by interpolation techniques. Unfortunately, when the plant contains both continuous and discrete variables, the interpolation approach does not work well. To cope with this kind of systems, we propose a general methodology that exploits explicit model checking in an innovative way to automatically synthesize a (time-) optimal numerical controller from a plant specification and apply an optimized strengthening algorithm only on the most significant states, in order to reach an acceptable robustness degree. We implemented all the algorithms within our CGMurphi tool, an extension of the well-known CMurphi verifier, and tested the effectiveness of our approach by applying it to the well-known truck and trailer obstacles avoidance problem.
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Francesco Brizzolari, Igor Melatti, Enrico Tronci, and Giuseppe Della Penna. "Disk Based Software Verification via Bounded Model Checking." In APSEC '07: Proceedings of the 14th Asia-Pacific Software Engineering Conference, 358–365. Washington, DC, USA: IEEE Computer Society, 2007. ISSN: 0-7695-3057-5. DOI: 10.1109/APSEC.2007.43.
Abstract: One of the most successful approach to automatic software verification is SAT based bounded model checking (BMC). One of the main factors limiting the size of programs that can be automatically verified via BMC is the huge number of clauses that the backend SAT solver has to process. In fact, because of this, the SAT solver may easily run out of RAM. We present two disk based algorithms that can considerably decrease the number of clauses that a BMC backend SAT solver has to process in RAM. Our experimental results show that using our disk based algorithms we can automatically verify programs that are out of reach for RAM based BMC.
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B. Leeners, T. Krueger, K. Geraedts, E. Tronci, T. Mancini, F. Ille, M. Egli, S. Roeblitz, D. Wunder, L. Saleh et al. "Cognitive function in association with high estradiol levels resulting from fertility treatment." Hormones and Behavior 130 (2021): 104951. ISSN: 0018-506x. DOI: 10.1016/j.yhbeh.2021.104951.
Abstract: The putative association between hormones and cognitive performance is controversial. While there is evidence that estradiol plays a neuroprotective role, hormone treatment has not been shown to improve cognitive performance. Current research is flawed by the evaluation of combined hormonal effects throughout the menstrual cycle or in the menopausal transition. The stimulation phase of a fertility treatment offers a unique model to study the effect of estradiol on cognitive function. This quasi-experimental observational study is based on data from 44 women receiving IVF in Zurich, Switzerland. We assessed visuospatial working memory, attention, cognitive bias, and hormone levels at the beginning and at the end of the stimulation phase of ovarian superstimulation as part of a fertility treatment. In addition to inter-individual differences, we examined intra-individual change over time (within-subject effects). The substantial increases in estradiol levels resulting from fertility treatment did not relate to any considerable change in cognitive functioning. As the tests applied represent a broad variety of cognitive functions on different levels of complexity and with various brain regions involved, we can conclude that estradiol does not show a significant short-term effect on cognitive function.
Keywords: Cognition, Estrogen, Estradiol, Fertility treatment, Attention, Cognitive bias
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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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T. Mancini, F. Mari, A. Massini, I. Melatti, and E. Tronci. "Anytime system level verification via parallel random exhaustive hardware in the loop simulation." Microprocessors and Microsystems 41 (2016): 12–28. ISSN: 0141-9331. DOI: 10.1016/j.micpro.2015.10.010.
Abstract: Abstract System level verification of cyber-physical systems has the goal of verifying that the whole (i.e., software + hardware) system meets the given specifications. Model checkers for hybrid systems cannot handle system level verification of actual systems. Thus, Hardware In the Loop Simulation (HILS) is currently the main workhorse for system level verification. By using model checking driven exhaustive HILS, System Level Formal Verification (SLFV) can be effectively carried out for actual systems. We present a parallel random exhaustive HILS based model checker for hybrid systems that, by simulating all operational scenarios exactly once in a uniform random order, is able to provide, at any time during the verification process, an upper bound to the probability that the System Under Verification exhibits an error in a yet-to-be-simulated scenario (Omission Probability). We show effectiveness of the proposed approach by presenting experimental results on SLFV of the Inverted Pendulum on a Cart and the Fuel Control System examples in the Simulink distribution. To the best of our knowledge, no previously published model checker can exhaustively verify hybrid systems of such a size and provide at any time an upper bound to the Omission Probability.
Keywords: Model Checking of Hybrid Systems; Model checking driven simulation; Hardware in the loop simulation
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "On-the-Fly Control Software Synthesis." In Proceedings of International SPIN Symposium on Model Checking of Software (SPIN 2013), 61–80. Lecture Notes in Computer Science 7976. Springer - Verlag, 2013. ISSN: 0302-9743. ISBN: 978-3-642-39175-0. DOI: 10.1007/978-3-642-39176-7_5.
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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." In Proc. of International SPIN Symposium on Model Checking of Software (SPIN 2013), 43–60. Lecture Notes in Computer Science 7976. Springer - Verlag, 2013. ISSN: 0302-9743. ISBN: 978-3-642-39175-0. DOI: 10.1007/978-3-642-39176-7_4.
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Toni Mancini, Federico Mari, Annalisa Massini, Igor Melatti, Fabio Merli, and Enrico Tronci. "System Level Formal Verification via Model Checking Driven Simulation." In Proceedings of the 25th International Conference on Computer Aided Verification. July 13-19, 2013, Saint Petersburg, Russia, 296–312. Lecture Notes in Computer Science 8044. Springer - Verlag, 2013. ISSN: 0302-9743. ISBN: 978-3-642-39798-1. DOI: 10.1007/978-3-642-39799-8_21.
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Giuseppe Della Penna, Benedetto Intrigila, Daniele Magazzeni, Igor Melatti, and Enrico Tronci. "CGMurphi: Automatic synthesis of numerical controllers for nonlinear hybrid systems." European Journal of Control 19, no. 1 (2013): 14–36. Elsevier North-Holland, Inc.. ISSN: 0947-3580. DOI: 10.1016/j.ejcon.2013.02.001.
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