A prognostic health management based framework for fault-tolerant control
Brown, Douglas W.
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The emergence of complex and autonomous systems, such as modern aircraft, unmanned aerial vehicles (UAVs) and automated industrial processes is driving the development and implementation of new control technologies aimed at accommodating incipient failures to maintain system operation during an emergency. The motivation for this research began in the area of avionics and flight control systems for the purpose to improve aircraft safety. A prognostics health management (PHM) based fault-tolerant control architecture can increase safety and reliability by detecting and accommodating impending failures thereby minimizing the occurrence of unexpected, costly and possibly life-threatening mission failures; reduce unnecessary maintenance actions; and extend system availability / reliability. Recent developments in failure prognosis and fault tolerant control (FTC) provide a basis for a prognosis based reconfigurable control framework. Key work in this area considers: (1) long-term lifetime predictions as a design constraint using optimal control; (2) the use of model predictive control to retrofit existing controllers with real-time fault detection and diagnosis routines; (3) hybrid hierarchical approaches to FTC taking advantage of control reconfiguration at multiple levels, or layers, enabling the possibility of set-point reconfiguration, system restructuring and path / mission re-planning. Combining these control elements in a hierarchical structure allows for the development of a comprehensive framework for prognosis based FTC. First, the PHM-based reconfigurable controls framework presented in this thesis is given as one approach to a much larger hierarchical control scheme. This begins with a brief overview of a much broader three-tier hierarchical control architecture defined as having three layers: supervisory, intermediate, and low-level. The supervisory layer manages high-level objectives. The intermediate layer redistributes component loads among multiple sub-systems. The low-level layer reconfigures the set-points used by the local production controller thereby trading-off system performance for an increase in remaining useful life (RUL). Next, a low-level reconfigurable controller is defined as a time-varying multi-objective criterion function and appropriate constraints to determine optimal set-point reconfiguration. A set of necessary conditions are established to ensure the stability and boundedness of the composite system. In addition, the error bounds corresponding to long-term state-space prediction are examined. From these error bounds, the point estimate and corresponding uncertainty boundaries for the RUL estimate can be obtained. Also, the computational efficiency of the controller is examined by using the number of average floating point operations per iteration as a standard metric of comparison. Finally, results are obtained for an avionics grade triplex-redundant electro-mechanical actuator with a specific fault mode; insulation breakdown between winding turns in a brushless DC motor is used as a test case for the fault-mode. A prognostic model is developed relating motor operating conditions to RUL. Standard metrics for determining the feasibility of RUL reconfiguration are defined and used to study the performance of the reconfigured system; more specifically, the effects of the prediction horizon, model uncertainty, operating conditions and load disturbance on the RUL during reconfiguration are simulated using MATLAB and Simulink. Contributions of this work include defining a control architecture, proving stability and boundedness, deriving the control algorithm and demonstrating feasibility with an example.