Recent developments in theory and tool support for hybrid systems verification with HyPro

This report presents results of a friendly competition for formal verification of continuous and hybrid systems with piecewise constant dynamics. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2018. In this second edition, five tools have been applied to solve five different benchmark problems in the category for piecewise constant dynamics: BACH, Lyse, PHAVer, PHAVer-lite, and VeriSiMPL. Compared to last year, a new tool has participated (PHAVer-lite) and a benchmark has been made more complex (Dutch Railway Network). The result is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results probably provide the most complete assessment of tools for the safety verification of continuous and hybrid systems with piecewise constant dynamics up to this date.

A Tool for Modular Modelling and Verification of Hybrid Systems

Unified Modeling Language is being used for modeling of business processes, real-time systems, embedded systems and hybrid systems. In software engineering, there are different techniques for verification of such systems. Model checking is one of the techniques for the automatic verification of software models. Earlier, these model were verified by sequential model checking tools. For very large complex systems, parallel verification can save verification time. DiVinE is a model checking tool for both CPUs and GPUs clusters to perform parallel linear time logic (LTL) verification of systems. In this paper, we propose a parallel verification methodology for UML models using DiVinE tool. We explain this methodology by the case study example of fuel filling machine.

Verifying properties of hybrid systems can be highly complex. To reduce the effort required to produce a correct proof, the use of mechanical verification techniques is promising. Recently, we extended a mechanical verification system, originally developed to reason about deterministic real-time automata, to verify properties of hybrid systems. To evaluate our approach, we applied our extended proof system to a solution, based on the Lynch-Vaandrager timed automata model, of the Steam Boiler Controller problem, a hybrid systems benchmark. This paper reviews our mechanical verification system, which builds on SRI's Prototype Verification System (PVS), and describes the features we added to handle hybrid systems. It also discusses some errors we detected in applying our system to the benchmark problem. We conclude with a summary of insights we acquired in using our system to specify and verify hybrid systems.

Hybrid system is a dynamic system that involves continuous, discrete behaviors, and the interactions between continuous physical components and discrete controllers. In this paper a hybrid modeling language (called HML) for hybrid systems is extended with templates to achieve code reuse. For the formal analysis of the corresponding hybrid system models in this modeling language, these models are translated into SMT (satisfiability modulo theories) formulas as the input to an SMT solver dReal which retains the capability of bounded reachability analysis for non-linear hybrid systems. Moreover, dReal can produce data for potential traces of hybrid systems, thus it can be employed to simulate on hybrid systems. In this paper the simulation and reachability analysis are integrated in a prototype tool (open source). We present a case study for an inverted pendulum with PID (Proportional-Integral-Derivative) controllers and a rod reactor system for temperature control, both are verified to demonstrate the efficiency of the prototype tool. We conclude that, this modeling language is capable of modeling and verification of hybrid systems based on simulation and bounded reachability analysis.

The hybrid estimation problem involves computation of both the continuous state and the discrete state estimates of a hybrid system from the measurements. In our earlier work, we have developed an algorithm, called the State-Dependent-Transition Hybrid Estimation (STDHE) algorithm which treats the discrete-state transitions to be dependent on the continuous state and governed by guard conditions in the linear form. This paper presents a hybrid estimation algorithm for the hybrid system whose guard conditions are in the quadratic form. The algorithm finds its applications in many areas such as Air Traffic Control (ATC), unmanned aerial vehicles coordination and control, and robot control. Simulation results show that our algorithm gives high estimation accuracy similar to that given by the Monte Carlo integration-based estimation algorithm while it is much more computationally efficient than the sample-based algorithms.

Energy Systems Engineering

This paper reviews recent developments in the area of computer-assisted analysis of mixture distributions (C.A.MAN). Given a biometric situation of interest in which, under homogeneity assumptions, a certain parametric density occurs, such as the Poisson, the binomial, the geometric, the normal, and so forth, then it is argued that this situation can easily be enlarged to allow a variation of the scalar parameter in the population. This situation is called unobserved heterogeneity. This naturally leads to a specific form of nonparametric mixture distribution that can then be assumed to be the standard model in the biometric application of interest (since it also incorporates the homogeneous situations as a special case). Besides developments in theory and algorithms, the work focuses on developments in biometric applications such as meta-analysis, fertility studies, estimation of prevalence under clustering, and estimation of the distribution function of survival time under interval censoring. The approach is nonparametric for the mixing distribution, including leaving the number of components (subpopulations) of the mixing distribution unknown.

The measurement of quality in auditorium acoustics by subjective scaling methods—A review of developments in theory and practice

In this paper a review of the recent developments in the theory of a slowly oscillating low aspect ratio, pointed wing at sonic speed is presented, using the concepts of the parabolic method, the equivalence rule and a iteration method to approximately incorporate the thickness effect in the analysis.

Hybrid systems are characterized by combining discrete and continuous behaviors. Verification of hybrid systems is, in general, a diffcult task due to the potential complexity of the continuous dynamics. Currently, there are different formalisms and tools which are able to analyze specific types of hybrid systems, model checking being one of the most used approaches. In this paper, we describe an extension of Java PathFinder in order to analyze hybrid systems. We apply a general methodology which has been successfully used to extend Spin. This methodology is non-intrusive, and uses external libraries, such as the Parma Polyhedra Library, to abstract the continuous behavior of the hybrid system.

The interplay of random phenomena with discrete-continuous dynamics deserves increased attention in many systems of growing importance. Their verification needs to consider both stochastic behaviour and hybrid dynamics. In the verification of classical hybrid systems, one is often interested in deciding whether unsafe system states can be reached. In the stochastic setting, we ask instead whether the probability of reaching particular states is bounded by a given threshold. In this thesis, we consider stochastic hybrid systems and develop a general abstraction framework for deciding such problems. This gives rise to the first mechanisable technique that can, in practice, formally verify safety properties of systems which feature all the relevant aspects of nondeterminism, general continuous-time dynamics, and probabilistic behaviour. Being based on tools for classical hybrid systems, future improvements in the effectiveness of such tools directly carry over to improvements in the effectiveness of our technique. We extend the method in several directions. Firstly, we discuss how we can handle continuous probability distributions. We then consider systems which we are in partial control of. Next, we consider systems in which probabilities are parametric, to analyse entire system families at once. Afterwards, we consider systems equipped with rewards, modelling costs or bonuses. Finally, we consider all orthogonal combinations of the extensions to the core model.

We present a scalable reachability algorithm for hybrid systems with piecewise affine, non-deterministic dynamics. It combines polyhedra and support function representations of continuous sets to compute an over-approximation of the reachable states. The algorithm improves over previous work by using variable time steps to guarantee a given local error bound. In addition, we propose an improved approximation model, which drastically improves the accuracy of the algorithm. The algorithm is implemented as part of SpaceEx, a new verification platform for hybrid systems, available at spaceex.imag.fr. Experimental results of full fixed-point computations with hybrid systems with more than 100 variables illustrate the scalability of the approach.KeywordsHybrid SystemSupport FunctionReachable StateHybrid AutomatonReachability AnalysisThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This paper proposes a new design scheme for hybrid dynamic worm detection system. In the proposed scheme, the features of matching detection method based on protocol analysis, Bayesian detection method based on probability, and honeypot-based detection method are integrated for a relative complemented function to develop the advantages and avoid the disadvantages of each detection method. The designed hybrid dynamic worm detection system can be used for effective detection of abnormal data behavior of the hosts attacked by worms, and it also serves for dynamic real-time update of the rule base. Then a preliminary functional verification is performed on this system.

In this article, H ∞ structured model reduction is addressed for linear discrete systems. Two important classes of systems are considered for structured model reduction, i.e. Markov jump systems and uncertain systems. The problem we deal with is the development of algorithms with the flexibility to allow any structure in the reduced-order system design, such as the structure of an original system, decentralisation of a networked system, pole assignment of the reduced system, etc. The algorithms are derived such that an associated model reduction error guarantees to satisfy a prescribed H ∞ norm-bound constraint. A new condition for the existence of desired reduced-order models preserving a certain structure is presented in a set of linear matrix inequalities (LMI) and non-convex equality constraints. Effective computational algorithms involving LMI are suggested to solve the matrix inequalities characterising a solution of the structured model reduction problem. Numerical examples demonstrate the advantages of the proposed model reduction method.