ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

This paper presents algorithms for the automatic synthesis of real-time controllers by finding a winning strategy for certain games defined by the timed-automata of Alur and Dill. In such games, the outcome depends on the players' actions as well as on their timing. We believe that these results will pave the way for the application of program synthesis techniques to the construction of real-time embedded systems from their specifications.

On the synthesis of discrete controllers for timed systems

This article focuses on synthesizing control policies for discrete-time stochastic control systems together with a lower bound on the probability that the systems satisfy the complex temporal properties. The desired properties of the system are expressed as linear temporal logic specifications over finite traces. In particular, our approach decomposes the given specification into simpler reachability tasks based on its automata representation. We, then, propose the use of so-called control barrier certificate to solve those simpler reachability tasks along with computing the corresponding controllers and probability bounds. Finally, we combine those controllers to obtain a hybrid control policy solving the considered problem. Under some assumptions, we also provide two systematic approaches for uncountable and finite input sets to search for control barrier certificates. We demonstrate the effectiveness of the proposed approach on a room temperature control and lane keeping of a vehicle modeled as a four-dimensional single-track kinematic model. We compare our results with the discretization-based methods in the literature.

Formal Synthesis of Stochastic Systems via Control Barrier Certificates

This paper reviews motor techniques for reducing the cost of electric vehicles (EVs) and improving their range. In recent years, environmental issues, energy crises and the greenhouse effect have urged the popularization of clean energy EVs. In order to achieve this goal, it is necessary to overcome technical difficulties in vehicle cost and range. As a key component of an EV, the motor occupies a large proportion of the overall vehicle cost, and its efficiency directly affects the mileage. In this context, this article discusses the merits and challenges of three mainstream EV motors: permanent magnet synchronous motor (PMSM), induction motor (IM), and switched reluctance motor (SRM) in terms of vehicle cost and range. Then this paper compares the advanced techniques of these motors in terms of topology, material applications and control strategies. Finally, the development trends and opportunities of the three motors in EVs are predicted.

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Challenges Faced by Electric Vehicle Motors and Their Solutions

Compositional abstraction-based synthesis for networks of stochastic switched systems

In the context of electricity shortage and an attempt to save the environment, introduction of energy efficient motors in different fields of application has become a necessity. This paves the way for fusing the conventional machine design procedures with optimization techniques. Unfortunately, the mathematics of electrical machine design involves calculations with highly nonlinear equation sets, and hence the conventional analytical optimization techniques do not fit well. In this study, design of an efficiency-optimized squirrel cage induction motor is considered, where genetic algorithm is chosen as the tool for optimization. The various constraints considered are selected on the basis of material, mechanical, and performance considerations as approved by standards and practices. The influence of change of materials and change of upper limit of customer's budget on different key motor design performance indicators are studied with and without cost constraints. Also, a systematic and statistics-based approach is proposed to achieve an optimized motor design, even at very low cost, provided relaxation of some constraints is allowed by the specific application. The optimized results are validated through tests on laboratory prototypes.

Efficiency and Cost Optimized Design of an Induction Motor Using Genetic Algorithm

We present multi-layered abstraction-based controller synthesis, which extends standard abstraction-based controller synthesis (ABCS) algorithms for continuous-time control systems by simultaneously maintaining several "layers" of abstract systems with decreasing precision. The resulting abstract multi-layered controller uses the coarsest abstraction whenever this is feasible, and dynamically adjusts the precision---by moving to a more precise abstraction and back to a coarser abstraction---based on the structure of the given control problem. Abstract multi-layered controllers can be refined to controllers with non-uniform resolution using feedback refinement relations established between each abstract layer and the concrete system, resulting in a sound ABCS method. We provide multi-layered controller synthesis algorithms for reachability, safety, and generalized Buchi specifications; our approach can be generalized to any ω-regular objective. Our algorithms are complete relative to single-layered synthesis on the finest layer. We empirically demonstrate that multi-layered synthesis can outperform standard (single-layer) ABCS algorithms on a number of examples, despite the additional cost of constructing multiple abstract systems.

Multi-Layered Abstraction-Based Controller Synthesis for Continuous-Time Systems

Controller-synthesis techniques for continuous systems with respect to temporal logic specifications typically use a finite-state symbolic abstraction of the system model. Constructing this abstraction for the entire system is computationally expensive, and does not exploit natural decompositions of many systems into interacting components. We describe a methodology for compositional symbolic abstraction to help scale controller synthesis for temporal logic to larger systems. We introduce disturbance bisimulation , which strengthens the standard approximate alternating bisimulation relation used in control. It extends naturally to systems that are composed of weakly interconnected subcomponents, possibly connected in feedback, and models the coupling signals as disturbances. We show how networks of incrementally input-to-state stable, nonlinear, continuous-time control systems can be abstracted compositionally, so that all local abstractions are simultaneously disturbance bisimilar to their continuous counterparts. Furthermore, our construction ensures that the final composed abstraction is disturbance bisimilar to the original system. Finally, we discuss how we get a compositional abstraction-based controller-synthesis methodology for networks of such systems against local temporal specifications as a byproduct of our construction.

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Compositional Synthesis of Finite-State Abstractions

We consider the policy synthesis problem for continuous-state controlled Markov processes evolving in discrete time, when the specification is given as a Buchi condition (visit a set of states infinitely often). We decompose computation of the maximal probability of satisfying the Buchi condition into two steps. The first step is to compute the maximal qualitative winning set, from where the Buchi condition can be enforced with probability one. The second step is to find the maximal probability of reaching the already computed qualitative winning set. In contrast with finite-state models, we show that such a computation only gives a lower bound on the maximal probability where the gap can be non-zero. In this paper we focus on approximating the qualitative winning set, while pointing out that the existing approaches for unbounded reachability computation can solve the second step. We provide an abstraction-based technique to approximate the qualitative winning set by simultaneously using an over- and under-approximation of the probabilistic transition relation. Since we are interested in qualitative properties, the abstraction is non-probabilistic; instead, the probabilistic transitions are assumed to be under the control of a (fair) adversary. Thus, we reduce the original policy synthesis problem to a Buchi game under a fairness assumption and characterize upper and lower bounds on winning sets as nested fixed point expressions in the μ-calculus. This characterization immediately provides a symbolic algorithm scheme. Further, a winning strategy computed on the abstract game can be refined to a policy on the controlled Markov process. We describe a concrete abstraction procedure and demonstrate our algorithm on two case studies. We show that our techniques are able to provide tight approximations to the qualitative winning set for the Van der Pol oscillator and a 3-d Dubins' vehicle.

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Symbolic controller synthesis for Büchi specifications on stochastic systems

Distributed reactive synthesis is the problem of algorithmically constructing controllers of distributed, communicating systems so that each closed-loop system satisfies a given temporal specification. We present an algorithm, called negotiation , for sound (but necessarily incomplete) distributed reactive synthesis based on assume–guarantee decompositions. The negotiation algorithm iteratively constructs assumptions and guarantees for each system. In each iteration, each system attempts to fulfill its specification and its guarantee (from the previous round), under the current assumption on the other systems, by solving a reactive synthesis problem. If the specification is not realizable, the algorithm computes a sufficient assumption on the other systems that ensures it can realize the specification and guarantee. This additional assumption further constrains the behavior of other systems and they might require an additional assumption, leading to the next round in the negotiation. The process terminates when a compatible assumption–guarantee pair is found for each system, which is sufficient to also satisfy the specification of each system. We have built a tool called Agnes that implements this algorithm. Using Agnes, we empirically demonstrate the effectiveness of our proposed algorithm on two case studies.

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Kaushik Mallik

Papers

Efficiency and Cost Optimized Design of an Induction Motor Using Genetic Algorithm

Multi-Layered Abstraction-Based Controller Synthesis for Continuous-Time Systems

Compositional Synthesis of Finite-State Abstractions

Symbolic controller synthesis for Büchi specifications on stochastic systems

Assume–Guarantee Distributed Synthesis