3 edition of **Efficient symbolic state-space construction for asynchronous systems** found in the catalog.

Efficient symbolic state-space construction for asynchronous systems

- 320 Want to read
- 35 Currently reading

Published
**1999**
by Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, National Technical Information Service, distributor in Hampton, VA, Springfield, VA
.

Written in English

- Complex systems.,
- Systems analysis.,
- Construction.,
- Synchronism.

**Edition Notes**

Other titles | Efficient symbolic state space construction for asynchronous systems |

Statement | Gianfranco Ciardo, Gerald Lüttgen, Radu Siminiceanu. |

Series | ICASE report -- no. 99-50, [NASA contractor report] -- NASA/CR-1999-209827, NASA contractor report -- NASA CR-209827. |

Contributions | Lüttgen, Gerald., Siminiceanu, Radu., Institute for Computer Applications in Science and Engineering. |

The Physical Object | |
---|---|

Format | Microform |

Pagination | 1 v. |

ID Numbers | |

Open Library | OL18295620M |

Towards state space representation What is a state space system? A "matrix-form" representation of the dynamics of an N- order differential equation system into aFIRSTorder differential equation in a vector form of size N, which is called the state. Deﬁnition of a system state Thestateof a dynamical system is the set of variables, known as state. Fall /31 5–6 Creating State-Space Models • Most easily created from Nth order diﬀerential equations that describe the dynamics • This was the case done before. • Only issue is which set of states to use – there are many Size: KB.

The State-Space block implements a system whose behavior you define as x ˙ = A x + B u y = C x + D u x | t = t 0 = x 0, where x is the state vector, u is the input vector, y is the output vector, and x 0 is the initial condition of the state vector. Systems and Con trol Mohammed Dahleh Mun ther A. George V erghese Departmen t of Electrical Engineering and Computer Science Massac h uasetts Institute of T ec hnology 1 1 c. Chapter 7 State-Space Mo dels In tro duction A cen tral question in dealing with a causal discrete-time (DT) system input u, output y, is the follo wing: Giv en the File Size: KB.

recipes for state space models in r 3 Fitting a Local Level Model The local level model assumes that we observe a time series, yt, and that time series is the sum of another time series, mt, and random, corrupting noise, would prefer to directly observe mt, a latent variable, but cannot due to the Size: KB. The construction of neural networks requires knowledge about both ideal architectures (connectivity) and most efficient weight vectors (computational power). The fusion of neural network modeling with evolutionary strategies is therefore a natural step towards artificial neurogenetic modeling.

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Efficient Symbolic State-Space Construction for Asynchronous Systems. efficient storage of states and both distributed and symbolic state space.

The objective of this paper is to improve on the time efficiency of symbolic state-space generation techniques for a particular class of systems, namely asynchronous systems.

This (:lass is. Abstract. Many techniques for the verification of reactive systems rely on the analysis of their reachable state spaces. In this paper, a new algorithm for the symbolic generation of the state spaces of asynchronous system models, such as Petri nets, is developed.

The algorithm is based on previous work that employs Multi-valued Decision Diagrams for Cited by: Get this from a library. Efficient symbolic state-space construction for asynchronous systems.

[Gianfranco Ciardo; Gerald Lüttgen; Radu Siminiceanu; Institute for Computer Applications in Science and Engineering.].

Ciardo G., Lüttgen G., Siminiceanu R. () Saturation: An Efficient Iteration Strategy for Symbolic State—Space Generation. In: Margaria T., Yi W. (eds) Tools and Algorithms for the Construction and Analysis of Systems. TACAS Lecture Notes in Computer Science, vol Springer, Berlin, Heidelberg.

First Online 23 March Cited by: Efficient symbolic state-space construction for asynchronous systems. In M. Nielsen and D. Simpson, editors, Application and Theory of Petri NetsLecture Notes in Computer Science(Proceedings of the 21th International Conference on Applications and Theory of Petri Nets, Aarhus, Denmark), pages in explicit-state model checking can also be exploited to make bounded model checking of asynchronous systems more efficient.

The answer is positive and there have been several proposals for making BMC more efficient for asynchronous systems, roughly falling in two different categories.

Algorithms and Data Structures for Efficient Timing Analysis of Asynchronous Real-time Systems, University of South Florida, Jared Ahrens A compositional approach to asynchronous design verification with automated state space reduction, University of South Florida, Hao Zheng Specification and Compilation of Timed Systems, University.

The states space is a directed graph where each possible state of a dynamical system is represented by a vertex, and there is a directed edge from a to b if and only if ƒ(a) = b where the function f defines the dynamical system. State spaces are useful in computer science as a simple model of machines.

Formally, a state space can be defined as a tuple [N, A, S, G] where. Bauer K and Schneider K From synchronous programs to symbolic representations of hybrid systems Proceedings of the 13th ACM international conference on Hybrid systems: computation and control, () Correct-by-Construction Asynchronous Implementation of Modular Synchronous Weil D, Bertin V, Closse E, Poize M, Venier P and Pulou J.

Ganai M, Wang C and Li W Efficient state space exploration Proceedings of the International Conference on Computer-Aided Design, () Abed S, Mohamed O and Al-Sammane G () An abstract reachability approach by combining HOL induction and multiway decision graphs, Journal of Computer Science and Technology,(), Online.

In state-determined systems, the state variables may always be taken as the outputs of integrator blocks. A system of order n has n integrators in its block Size: KB. The PROSPER Toolkit.- CASL: From Semantics to Tools.- Timed and Hybrid Systems.- On the Construction of Live Timed Systems.- On Memory-Block Traversal Problems in Model-Checking Timed Systems.- Symbolic Model Checking for Rectangular Hybrid Systems.- Efficient Data Structure for Fully Symbolic Verification of Real-Time Software Systems Using State Space Exploration and a Natural Deduction Style Message Derivation Engine to Verify Security Protocols Clarke, E.M., Jha, S.

& Marrero, W. Proceedings of the IFIP Working Conference on Programming Concepts and Methods (PROCOMET),Shelter Island, New York, pp. On the Semantic Foundations of Probabilistic VERUS.

Tools and Algorithms for the Construction and Analysis of Systems 13th International Conference, TACAS Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS Braga, Portugal, March 24 - April 1, Proceedings. Robust Control System Design: Advanced State Space Techniques, Second Edition expands upon a groundbreaking and combinatorial approach to state space control system design that fully realizes the critical loop transfer function and robustness properties of state/generalized state feedback : Hardcover.

State-space analysis of control systems: Part I Why a different approach. • Using a state-variable approach gives us a straightforward way to analyze MIMO (multiple-input, multiple output) systems.

• A state variable model helps us understand some complex general concepts about control systems, such as controllability and observability. A state-space model is Observable i↵any two di↵erent initial states x 0 6= x 0 2 Rn lead to a di↵erent output {y s} s0 of the state-space model in the future when the inputs are switched o↵ henceforth (autonomous mode).

Deﬁne the Observability matrix O2Rqn⇥n as O = 2 6 6 6 4 C CA CAn 1 3 7 7 7 5 () Hence, a state-space model. This volume contains the proceedings of the International Conference on Computer Aided Veri?cation (CAV), held in Edinburgh, Scotland, July 6–10, CAV was the seventeenth in a series of conferences dedicated to the advancement of the theory and practice of computer-assisted formal an.

ECE H - Systems Control - M. Maggiore State-space approach to linear system theory. Mathematical background in linear algebra, state space equations vs transfer functions, solutions of linear ODE's, state transition matrix, Jordan form, controllability, eigenvalue assignment using state feedback, observability, designing observers, separation principle, Kalman filters.

“Efficient On-the-Fly Model Checking for CTL*”, LICS’ W. Damm, O. Grumberg, H. Hungar: “What if Model Checking Must be Truly Symbolic“, workshop on Tools and Algorithms for the Construction and Analysis of Systems (TACAS’95), Aarhus, Denmark, May E.M.

Clarke, O. Grumberg, S. Jha.Design of Digital Control Systems Using State-Space Methods INTRODUCTION In Chapter 5, we discussed how to design digital controllers using transform techniques, methods now commonly designated as "classical design." The goal of this chapter is to solve the identical problem using the state-space Size: 5MB.We illustrate symbolic execution with the example program shown in Fig.

1, where the method compute has three integer inputs: curr (current), thresh (threshold), and step; it calculates the relationship between the current and the threshold, in increments given by the step corresponding symbolic execution tree is shown in Fig.

path condition PC is initialized Author: Guowei Yang, Antonio Filieri, Mateus Borges, Donato Clun, Junye Wen.