Dependability-oriented design and analysis of control systems at the model level under random hardware faults

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Model-based design is a common methodology in the development of embedded complex control systems. Control system engineers typically prefer to use MATLAB Simulink and suitable automatic code generators for the development and deployment of software. Embedded systems are subject to random hardware faults. This thesis proposes an analytical method for the evaluation of the reliability properties of control systems that are designed with Simulink models. The method is based on a transformation of the assembly code, which is generated from the Simulink model, into a formal stochastic error propagation model as well as its quantification through underlying Markov chain models and state-of-the-art probabilistic model-checking techniques. In the case of model-based development, redundancy mechanisms are preferable for direct application at the model level (Simulink model level). This thesis introduces a systematic classification of fault-tolerant design patterns. Such patterns can be applied to the Simulink model to tolerate random hardware faults, and taken into account during the control system design. This thesis proposes a model-level reliability evaluation of Simulink models. The efficiency of the proposed model-level evaluation is verified by a comparison of the reliability properties that are assessed at the assembly and model levels.