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F. Fabiani, S. Grechi, S. Della Tommasina, A. Caiti: "A NLPCA Hybrid Approach for AUV Thrusters Fault Detection and Isolation", SysTol’16 3rd International Conference on Control and Fault–Tolerant Systems, Barcellona (ES), September 2016

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The objective of this paper is to address the problem of Fault Detection and Isolation (FDI) on thrusters of an over-actuated Autonomous Underwater Vehicle (AUV) under on/off abrupt faults. The goal is pursued through Non-Linear Principal Component Analysis (NLPCA), which is the nonlinear extension of the popular Principal Component Analysis (PCA). While the Fault Detection (FD) system directly exploits the model-free nature of NLPCA (data-driven approach), the Fault Isolation (FI) is achieved by properly train off-line Artificial Neural Network (ANN). The consistency and robustness of the proposed method is verified in realistic simulation.