Johanna Nellen

A CEGAR Tool for the Reachability Analysis of PLC-Controlled Plants Using Hybrid Automata

In this paper we address the safety analysis of chemical plants controlled by programmable logic controllers (PLCs). We consider sequential function charts (SFCs) for the programming of the PLCs, extended with the specification of the dynamic plant behavior. The resulting hybrid SFC models can be transformed to hybrid automata, opening the way to the application of advanced techniques for their reachability analysis. However, the hybrid automata models are often too large to be analyzed. To keep the size of the models moderate, we propose a counterexample-guided abstraction refinement (CEGAR) approach, which starts with the purely discrete SFC model of the controller and extends it with those parts of the dynamic behavior, which are relevant for proving or disproving safety. Our algorithm can deal with urgent locations and transitions, and non-convex invariants. We integrated the CEGAR approach in the analysis tool spaceex and present an example.

Two CEGAR-based approaches for the safety verification of PLC-controlled plants

In this paper we address the safety analysis of chemical plants controlled by programmable logic controllers (PLCs). We consider a specification of the control program of the PLCs, extended with the specification of the dynamic plant behavior. The resulting hybrid models can be transformed to hybrid automata, for which advanced techniques for reachability analysis exist. However, the hybrid automata models are often too large to be analyzed. We propose two counterexample-guided abstraction refinement (CEGAR) approaches to keep the size of the hybrid models moderate.

Divide and Conquer: Variable Set Separation in Hybrid Systems Reachability Analysis

In this paper we propose an improvement for flowpipe-construction-based reachability analysis techniques for hybrid systems. Such methods apply iterative successor computations to pave the reachable region of the state space by state sets in an over-approximative manner. As the computational costs steeply increase with the dimension, in this work we analyse the possibilities for improving scalability by dividing the search space in sub-spaces and execute reachability computations in the sub-spaces instead of the global space. We formalise such an algorithm and provide experimental evaluations to compare the efficiency as well as the precision of our sub-space search to the original search in the global space.

A CEGAR approach for the reachability analysis of PLC-controlled chemical plants

In this paper we address the safety analysis of chemical plants controlled by programmable logic controllers (PLCs). We consider sequential function charts (SFCs)for the programming of the PLCs, extended with the specification of the dynamic plant behavior. The resulting hybrid SFC models can be transformed to hybrid automata, opening the way to the application of advanced techniques for their reachability analysis. However, the hybrid automata models are often too large to be analyzed. To keep the size of the models moderate, we propose a counterexample-guided abstraction refinement (CEGAR) approach, which starts with the purely discrete SFC model of the controller and extends it with those parts of the dynamic behavior, which are relevant for proving or disproving safety.

Learning-based control strategies for hybrid electric vehicles

Hybrid electric vehicles use control strategies to distribute the torque requested by the driver between the internal combustion engine and the electrical motor. Many different types of control strategies have been proposed, but in general it is impossible to determine which control strategy performs best if the future driving conditions are unknown. In this paper, we introduce two learning-based control strategies which use an arbitrary set of basic control strategies in order to minimize the fuel consumption of the hybrid electric vehicle. Our simulation results show that the fuel consumption of the learning-based control strategies are comparable to the fuel consumption of the best basic control strategy in the set even without a priori knowledge of the driving conditions.

Counterexample Generation for Hybrid Automata

The last decade brought us a whole range of over-approximative algorithms for the reachability analysis of hybrid automata, a widely used modeling language for systems with combined discrete-continuous behavior. Besides theoretical results, there are also some tools available for proving safety in the continuous time domain. However, if a given set of critical states is found to be reachable, these tools do not provide counterexamples for models beyond timed automata.

Formal Verification of Automotive Simulink Controller Models: Empirical Technical Challenge, Evaluation and Recommendations

The automotive industry makes increasing usage of Simulink-based software development. Typically, automotive Simulink designs are analyzed using non-formal test methods, which do not guarantee the absence of errors. In contrast, formal verification techniques aim at providing formal guarantees or counterexamples that the analyzed designs fulfill their requirements for all possible inputs and parameters. Therefore, the automotive safety standard ISO 26262 recommends the usage of formal methods in safety-critical software development.

On collaboratively conveying computer science to pupils

Though there is an increasing need for computer scientists in our society, gifted young people with strong mathematical background, who would be well-suited for a study of computer science, often do not consider this choice because they have a wrong picture of computer science in mind. In this paper we present a new concept of collaborative learning to introduce high-school students to the field of theoretical computer science. In particular, we choose the demanding field of real-time systems in order to illustrate the applicability of theoretical methods on real-world systems. Statistical results show that with our concept we are able to point out the manifoldness, beauty and challenge of this scientific area and can convince high-school students to consider computer science as a choice of study.