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020 ▼a 9780691189581 ▼q (electronic bk.)
020 ▼a 0691189587 ▼q (electronic bk.)
020 ▼z 9780691181301
035 ▼a 1941226 ▼b (N$T)
035 ▼a (OCoLC)1085493238
037 ▼a 22573/ctv827psq ▼b JSTOR
040 ▼a N$T ▼b eng ▼e rda ▼e pn ▼c N$T ▼d N$T ▼d EBLCP ▼d OCLCF ▼d N$T ▼d DEGRU ▼d JSTOR ▼d 248032
049 ▼a MAIN
050 4 ▼a TJ225
072 7 ▼a TEC ▼x 009000 ▼2 bisacsh
072 7 ▼a MAT ▼x 003000 ▼2 bisacsh
072 7 ▼a MAT ▼x 007000 ▼2 bisacsh
072 7 ▼a MAT ▼x 017000 ▼2 bisacsh
072 7 ▼a MAT ▼x 041000 ▼2 bisacsh
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08204 ▼a 629.8 ▼2 23
1001 ▼a Garoche, Pierre-Loi?c, ▼e author.
24510 ▼a Formal Verification of Control System Software / ▼c Pierre-Lo ?캇c Garoche. ▼h [electronic resource]
260 1 ▼a Princeton, New Jersey : ▼b Princeton University Press, ▼c [2019]
300 ▼a 1 online resource.
336 ▼a text ▼b txt ▼2 rdacontent
337 ▼a computer ▼b c ▼2 rdamedia
338 ▼a online resource ▼b cr ▼2 rdacarrier
4901 ▼a Princeton series in applied mathematics
504 ▼a Includes bibliographical references and index.
5050 ▼a Cover; Contents; I. Need and Tools to Verify Critical Cyber-Physical Systems; 1. Critical Embedded Software: Control Software Development and V 2. Formal Methods: Different Approaches for Verification; 2.1 Semantics and Properties; 2.2 A Formal Verification Methods Overview; 2.3 Deductive Methods; 2.4 SMT-based Model-checking; 2.5 Abstract Interpretation (of Collecting Semantics); 2.6 Need for Inductive Invariants; 3. Control Systems; 3.1 Controllers' Development Process; 3.2 A Simple Linear System: Spring-mass Damper
5058 ▼a II. Invariant Synthesis: Convex-optimization Based Abstract Interpretation4. Definitions-Background; 4.1 Discrete Dynamical Systems; 4.2 Elements of (Applied) Convex Optimization; 5. Invariants Synthesis via Convex Optimization: Postfixpoint Computation as Semialgebraic Constraints; 5.1 Invariants, Lyapunov Functions, and Convex Optimization; 5.2 Quadratic Invariants; 5.3 Piecewise Quadratic Invariants; 5.4 k-inductive Quadratic Invariants; 5.5 Polynomial Invariants; 5.6 Image Measure Method; 5.7 Related Works; 6. Template-based Analyses and Min-policy Iteration
5058 ▼a 6.1 Template-based Abstract Domains6.2 Template Abstraction Fixpoint as an Optimization Problem; 6.3 SOS-relaxed Semantics; 6.4 Example; 6.5 Related Works; III. System-level Analysis at Model and Code Level; 7. System-level Properties as Numerical Invariants; 7.1 Open-loop and Closed-loop Stability; 7.2 Robustness with Vector Margin; 7.3 Related Work; 8. Validation of System-level Properties at Code Level; 8.1 Axiomatic Semantics of Control Properties through Synchronous Observers and Hoare Triples; 8.2 Generating Annotations: A Strongest Postcondition Propagation Algorithm
5058 ▼a 8.3 Discharging Proof Objectives using PVSIV. Numerical Issues; 9. Floating-point Semantics of Analyzed Programs; 9.1 Floating-point Semantics; 9.2 Revisiting Inductiveness Constraints; 9.3 Bound Floating-point Errors: Taylor-based Abstractions aka Zonotopic Abstract Domains; 9.4 Related Works; 10. Convex Optimization and Numerical Issues; 10.1 Convex Optimization Algorithms; 10.2 Guaranteed Feasible Solutions with Floats; Bibliography; Index; Acknowledgments
520 ▼a An essential introduction to the analysis and verification of control systems softwareThe verification of control systems software is critical to a host of technologies and industries, from aeronautics and medical technology to the cars we drive--the failure of controller software can cost people their lives. In this authoritative and accessible book, Pierre-Loi?c Garoche provides control engineers and computer scientists with an indispensable introduction to the formal techniques for analyzing and verifying this important class of software.Too often, control engineers are unaware of the issues surrounding the verification of software, while computer scientists tend to be unfamiliar with the specificities of controller software. Garoche provides a unified approach especially geared to graduate students in both fields, covering formal verification methods as well as the design and verification of controllers. He presents a wealth of new verification techniques for performing exhaustive analysis of controller software. These include new means to compute nonlinear invariants, the use of convex optimization tools, and methods for dealing with numerical imprecisions such as floating point computations occurring in the analyzed software.As the autonomy of these systems continues to increase--such as in autonomous cars, drones, and satellites and landers--the numerical functions in critical systems are growing ever more advanced. The techniques presented here are essential to support the formal analysis of the controller software being used in these new and emerging technologies.
5880 ▼a Online resource; title from PDF title page (EBSCO, viewed February 13, 2019).
590 ▼a Master record variable field(s) change: 072
650 0 ▼a Automatic control.
650 0 ▼a Computer software.
650 7 ▼a TECHNOLOGY & ENGINEERING / Engineering (General) ▼2 bisacsh
650 7 ▼a Automatic control. ▼2 fast ▼0 (OCoLC)fst00822702
650 7 ▼a Computer software. ▼2 fast ▼0 (OCoLC)fst00872527
650 7 ▼a MATHEMATICS / Applied ▼2 bisacsh
655 4 ▼a Electronic books.
830 0 ▼a Princeton series in applied mathematics.
85640 ▼3 EBSCOhost ▼u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1941226
938 ▼a De Gruyter ▼b DEGR ▼n 9780691189581
938 ▼a EBL - Ebook Library ▼b EBLB ▼n EBL5695063
938 ▼a EBSCOhost ▼b EBSC ▼n 1941226
990 ▼a 관리자
994 ▼a 92 ▼b N$T