Titlebook: Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems; Steven X. Ding Book 2014 Springer-Verlag London 2014 Data-driven

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Adaptive Fault Diagnosis SchemesThe key of data-driven fault diagnosis schemes consists in a direct identification of key fault detection statistics like covariance matrices applied in the MVA or SIM based methods.

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Data-Driven Design of Observer-Based Control SystemsIn the previous chapter, we have introduced the fault-tolerant architecture and the associated design parameters. In this chapter, we focus on the data-driven design of the state feedback gain matrix, an H-PRIO parameter of the fault-tolerant architecture, and its application to the observer-based control schemes.

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https://doi.org/10.1007/978-1-4471-6410-4Data-driven Techniques; Fault Detection and Isolation; Fault Diagnosis; Fault-tolerant Systems; Process

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https://doi.org/10.1007/978-3-642-84186-6hemes presented and studied in this book. The first two are real laboratory control systems, which are widely used both in the model-based and data-driven fault diagnosis research. The third one is a benchmark process that is mainly applied for the test and demonstration of data-driven control and m

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https://doi.org/10.1007/978-3-642-84186-6c issues, ideas and solution tools in dealing with fault detection issues. They are useful for our subsequent study. At the end of this chapter, two variations of the essential fault detection problem are then introduced.

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