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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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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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Enrico Tronci. "Optimal Finite State Supervisory Control." In CDC '96: Proceedings of the 35th IEEE International Conference on Decision and Control. Washington, DC, USA: IEEE Computer Society, 1996. DOI: 10.1109/CDC.1996.572981.
Abstract: Supervisory Controllers are Discrete Event Dynamic Systems (DEDSs) forming the discrete core of a Hybrid Control System. We address the problem of automatic synthesis of Optimal Finite State Supervisory Controllers (OSCs). We show that Boolean First Order Logic (BFOL) and Binary Decision Diagrams (BDDs) are an effective methodological and practical framework for Optimal Finite State Supervisory Control. Using BFOL programs (i.e. systems of boolean functional equations) and BDDs we give a symbolic (i.e. BDD based) algorithm for automatic synthesis of OSCs. Our OSC synthesis algorithm can handle arbitrary sets of final states as well as plant transition relations containing loops and uncontrollable events (e.g. failures). We report on experimental results on the use of our OSC synthesis algorithm to synthesize a C program implementing a minimum fuel OSC for two autonomous vehicles moving on a 4 x 4 grid.
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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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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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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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Toni Mancini, Federico Mari, Annalisa Massini, Igor Melatti, and Enrico Tronci. "System Level Formal Verification via Distributed Multi-Core Hardware in the Loop Simulation." In Proc. of the 22nd Euromicro International Conference on Parallel, Distributed and Network-Based Processing. IEEE Computer Society, 2014. DOI: 10.1109/PDP.2014.32.
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Vadim Alimguzhin, Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Automatic Control Software Synthesis for Quantized Discrete Time Hybrid Systems." In Proceedings of the 51th IEEE Conference on Decision and Control, CDC 2012, December 10-13, 2012, Maui, HI, USA, 6120–6125. IEEE, 2012. ISBN: 978-1-4673-2065-8. Notes: Techreport version can be found at http://arxiv.org/abs/1207.4098. DOI: 10.1109/CDC.2012.6426260.
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Synthesizing Control Software from Boolean Relations." International Journal on Advances in Software vol. 5, nr 3&4 (2012): 212–223. IARIA. ISSN: 1942-2628.
Abstract: Many software as well digital hardware automatic
synthesis methods define the set of
implementations meeting the given system
specifications with a boolean relation K. In
such a context a fundamental step in the software
(hardware) synthesis process is finding effective
solutions to the functional equation defined by
K. This entails finding a (set of) boolean
function(s) F (typically represented using
OBDDs, Ordered Binary Decision Diagrams)
such that: 1) for all x for which K is
satisfiable, K(x, F(x)) = 1 holds; 2) the
implementation of F is efficient with respect
to given implementation parameters such as code
size or execution time. While this problem has
been widely studied in digital hardware synthesis,
little has been done in a software synthesis
context. Unfortunately, the approaches developed
for hardware synthesis cannot be directly used in
a software context. This motivates investigation
of effective methods to solve the above problem
when F has to be implemented with software. In
this paper, we present an algorithm that, from an
OBDD representation for K, generates a C code
implementation for F that has the same size as
the OBDD for F and a worst case execution time
linear in nr, being n = |x| the number of
input arguments for functions in F and r the
number of functions in F. Moreover, a formal
proof of the proposed algorithm correctness is
also shown. Finally, we present experimental
results showing effectiveness of the proposed
algorithm.
Keywords: Control Software Synthesis; Embedded Systems; Model Checking
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Federico Mari, Igor Melatti, Ivano Salvo, and Enrico Tronci. "Linear Constraints and Guarded Predicates as a Modeling Language for Discrete Time Hybrid Systems." International Journal on Advances in Software vol. 6, nr 1&2 (2013): 155–169. IARIA. ISSN: 1942-2628.
Abstract: Model based design is particularly appealing in
software based control systems (e.g., embedded
software) design, since in such a case system
level specifications are much easier to define
than the control software behavior itself. In
turn, model based design of embedded systems
requires modeling both continuous subsystems
(typically, the plant) as well as discrete
subsystems (the controller). This is typically
done using hybrid systems. Mixed Integer Linear
Programming (MILP) based abstraction techniques
have been successfully applied to automatically
synthesize correct-by-construction control
software for discrete time linear hybrid systems,
where plant dynamics is modeled as a linear
predicate over state, input, and next state
variables. Unfortunately, MILP solvers require
such linear predicates to be conjunctions of
linear constraints, which is not a natural way of
modeling hybrid systems. In this paper we show
that, under the hypothesis that each variable
ranges over a bounded interval, any linear
predicate built upon conjunction and disjunction
of linear constraints can be automatically
translated into an equivalent conjunctive
predicate. Since variable bounds play a key role
in this translation, our algorithm includes a
procedure to compute all implicit variable bounds
of the given linear predicate. Furthermore, we
show that a particular form of linear predicates,
namely guarded predicates, are a natural and
powerful language to succinctly model discrete
time linear hybrid systems dynamics. Finally, we
experimentally show the feasibility of our
approach on an important and challenging case
study taken from the literature, namely the
multi-input Buck DC-DC Converter. As an example,
the guarded predicate that models (with 57
constraints) a 6-inputs Buck DC-DC Converter is
translated in a conjunctive predicate (with 102
linear constraints) in about 40 minutes.
Keywords: Model-based software design; Linear predicates; Hybrid systems
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