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A data-driven sensor fault-tolerant control scheme based on subspace identification
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DOI：10.1002/rnc.5666.png)
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Abstract
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We study the sensor fault estimation and accommodation problems in a data-driven Script capital H-infinity setting, leading to a data-driven sensor fault-tolerant control scheme. First, we formulate the fault estimation problem as a finite-horizon minimax Script capital H-infinity-optimization problem in a data-driven setup, whose solution yields the fault estimate. The estimated fault is then used for output compensation. This compensated output and the experimental input are used to achieve certain control objectives in a data-driven Script capital H-infinity setting. Next, the data-driven Script capital H-infinity fault estimation and control problems are solved using a subspace predictor-based approach. Finally, the proposed algorithm is applied to the steering subsystem of the remotely operated underwater vehicle.
Keywords:
H-infinity control
data-driven control
fault-tolerant control
fault estimation
subspace predictor
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