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Kalman filters in non-uniformly sampled multirate systems: for FDI and beyond. (English) Zbl 1138.93056

Summary: The first part of the paper is the development of a data-driven Kalman filter for a Non-Uniformly Sampled Multirate (NUSM) system. Algorithms for both one-step predictor and filtering are developed and analysis of stability and convergence is conducted in the NUSM framework. The second part of the paper investigates a Kalman filter-based methodology for unified detection and isolation of sensor, actuator, and process faults in the NUSM system with analysis on fault detectability and isolability. Case studies using data respectively collected from a pilot experimental plant and a simulated system are conducted to justify the practicality of the proposed theory.

MSC:

93E11 Filtering in stochastic control theory
93C57 Sampled-data control/observation systems
93C55 Discrete-time control/observation systems
93C10 Nonlinear systems in control theory
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