Verifying Properties of an Electro-Mechanical Braking System

Strathmann, Thomas; Oehlerking, Jens

doi:10.29007/x87p

Cited by 12 publications

(32 citation statements)

References 6 publications

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“…These ranges are identified by model designers [9]. In general, the ranges for model inputs and configuration parameters should be identified by engineers who design and implement the models.…”

Section: Resultsmentioning

confidence: 99%

“…In the first experiment, we fix the BR(t) signal to the one used in [9] and vary the values of R and L within the ranges [0.4, 0.6] and [0.00025, 0.00175], respectively. These ranges are identified by model designers [9].…”

Section: Resultsmentioning

confidence: 99%

“…Our approach, however, is applicable not just to generic properties but also to controllers function-specific requirements. For example, the following requirement is specified for EMB [9]:…”

Section: Specificationmentioning

confidence: 99%

“…The above requirement (denoted by ϕ 1 ) can be formalized in terms of a temporal logic formula as follows [9]:…”

Section: Specificationmentioning

confidence: 99%

“…It is an experimental Electro-Mechanical Braking (EMB) system consisting of a physical (plant) model together with the software controller consisting of a discrete state machine (open-loop) and a continuous PID (closed-loop) controller. EMB is published by Bosch research lab as a representative benchmark model for cyber physical systems from the automotive domain [9] and is available at [8]. It is implemented in Matlab/Simulink [10].…”

Section: Motivating Examplementioning

confidence: 99%

See 4 more Smart Citations

Automated testing of hybrid Simulink/Stateflow controllers: industrial case studies

Matinnejad

Nejati

Briand

2017

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

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We present the results of applying our approach for testing Simulink controllers to one public and one proprietary model, both industrial. Our approach combines explorative and exploitative search algorithms to visualize the controller behavior over its input space and to identify test scenarios in the controller input space that violate or are likely to violate the controller requirements. The engineers' feedback shows that our approach is easy to use in practice and gives them confidence about the behavior of their models. CCS CONCEPTS• Software and its engineering → Software verification and validation;

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Specificationmentioning

confidence: 99%

“…The above requirement (denoted by ϕ 1 ) can be formalized in terms of a temporal logic formula as follows [9]:…”

Section: Specificationmentioning

confidence: 99%

Section: Motivating Examplementioning

confidence: 99%

See 3 more Smart Citations

Automated testing of hybrid Simulink/Stateflow controllers: industrial case studies

Matinnejad

Nejati

Briand

2017

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

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Local Descent for Temporal Logic Falsification of Cyber-Physical Systems

Yaghoubi

Fainekos

2019

Cyber Physical Systems. Design, Modeling, and Evaluation

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One way to analyze Cyber-Physical Systems is by modeling them as hybrid automata. Since reachability analysis for hybrid nonlinear automata is a very challenging and computationally expensive problem, in practice, engineers try to solve the requirements falsification problem. In one method, the falsification problem is solved by minimizing a robustness metric induced by the requirements. This optimization problem is usually a non-convex non-smooth problem that requires heuristic and analytical guidance to be solved. In this paper, functional gradient descent for hybrid systems is utilized for locally decreasing the robustness metric. The local descent method is combined with Simulated Annealing as a global optimization method to search for unsafe behaviors.

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