Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems

This paper introduces a methodology for the design, testing and assessment of incipient failure detection techniques for failing components/systems of critical engineered systems/processes masked or hidden by feedback control loops. It is recognized that the optimum operation of critical assets (aircraft, autonomous systems, industrial processes, etc.) may be compromised by feedback control loops, which mask severe fault modes while compensating for typical disturbances. Detrimental consequences of such occurrences include the inability to detect expeditiously and accurately incipient failures, loss of control, and inefficient operation of assets in the form of fuel overconsumption and adverse environmental impact. A novel control-theoretic framework is presented to address the masking problem. Major elements of the proposed approach are employed in simulation to develop, implement and validate how faults are distinguished from disturbances and how faults are detected and identified with performance guarantees, i.e., prescribed confidence level and given false alarm rate.The demonstration and validity of the tools/methods employed necessitates, in addition to the theoretical content, a suitable testbed. We have employed and describe briefly in this paper an autonomous hovercraft as the test prototype. We pursue a systems engineering process to design, construct and test the prototype hovercraft instrumented appropriately for purposes of fault injection, monitoring and the presence of control loops. We emphasize a general control-theoretic framework to the masking problem and utilize a simulation environment to derive results and illustrate the efficacy of the methodology.