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Author |
Tronci, Enrico |
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Title |
Formally Modeling a Metal Processing Plant and its Closed Loop Specifications |
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Conference Article |
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Year |
1999 |
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4th IEEE International Symposium on High-Assurance Systems Engineering (HASE) |
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151 |
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We present a case study on automatic synthesis of control software from formal specifications for an industrial automation control system. Our aim is to compare the effectiveness (i.e. design effort and controller quality) of automatic controller synthesis from closed loop formal specifications with that of manual controller design followed by automatic verification. The system to be controlled (plant) models a metal processing facility near Karlsruhe. We succeeded in automatically generating C code implementing a (correct by construction) embedded controller for such a plant from closed loop formal specifications. Our experimental results show that for industrial automation control systems automatic synthesis is a viable and profitable (especially as far as design effort is concerned) alternative to manual design followed by automatic verification. |
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IEEE Computer Society |
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Washington, D.C, USA |
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0-7695-0418-3 |
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yes |
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Call Number |
Sapienza @ mari @ hase99 |
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50 |
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Author |
Tronci, Enrico |
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Title |
On Computing Optimal Controllers for Finite State Systems |
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Conference Article |
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Year |
1997 |
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CDC '97: Proceedings of the 36th IEEE International Conference on Decision and Control |
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IEEE Computer Society |
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Washington, DC, USA |
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yes |
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Call Number |
Sapienza @ mari @ cdc97 |
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66 |
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Author |
Tronci, Enrico |
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Title |
Optimal Finite State Supervisory Control |
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Conference Article |
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Year |
1996 |
Publication |
CDC '96: Proceedings of the 35th IEEE International Conference on Decision and Control |
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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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IEEE Computer Society |
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Washington, DC, USA |
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yes |
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Sapienza @ mari @ cdc96 |
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67 |
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Author |
Intrigila, Benedetto; Magazzeni, Daniele; Melatti, Igor; Tronci, Enrico |
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Title |
A Model Checking Technique for the Verification of Fuzzy Control Systems |
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Conference Article |
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Year |
2005 |
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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) |
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536-542 |
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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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IEEE Computer Society |
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Washington, DC, USA |
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0-7695-2504-0-01 |
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yes |
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Call Number |
Sapienza @ mari @ Immt05 |
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75 |
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Author |
Brizzolari, Francesco; Melatti, Igor; Tronci, Enrico; Della Penna, Giuseppe |
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Title |
Disk Based Software Verification via Bounded Model Checking |
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Conference Article |
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2007 |
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APSEC '07: Proceedings of the 14th Asia-Pacific Software Engineering Conference |
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358-365 |
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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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IEEE Computer Society |
Place of Publication |
Washington, DC, USA |
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0-7695-3057-5 |
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yes |
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Call Number |
Sapienza @ mari @ Bmtd07 |
Serial |
76 |
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Author |
Martinelli, Marco; Tronci, Enrico; Dipoppa, Giovanni; Balducelli, Claudio |
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Title |
Electric Power System Anomaly Detection Using Neural Networks |
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Conference Article |
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Year |
2004 |
Publication |
8th International Conference on: Knowledge-Based Intelligent Information and Engineering Systems (KES) |
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1242-1248 |
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The aim of this work is to propose an approach to monitor and protect Electric Power System by learning normal system behaviour at substations level, and raising an alarm signal when an abnormal status is detected; the problem is addressed by the use of autoassociative neural networks, reading substation measures. Experimental results show that, through the proposed approach, neural networks can be used to learn parameters underlaying system behaviour, and their output processed to detecting anomalies due to hijacking of measures, changes in the power network topology (i.e. transmission lines breaking) and unexpected power demand trend. |
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Springer |
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Wellington, New Zealand |
Editor |
Negoita, M.G.; Howlett, R.J.; Jain, L.C. |
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Lecture Notes in Computer Science |
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Series Volume |
3213 |
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3-540-23318-0 |
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yes |
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Call Number |
Sapienza @ mari @ kes04 |
Serial |
35 |
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