Fault detection and isolation based on novel unknown input observer design

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Conference Proceeding

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Proceedings of the American Control Conference



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With an emphasis on fault isolation and by treating fault detection as a byproduct of fault isolation, both actuator and sensor fault detection and isolation (FDI) problems for a class of uncertain Lipschitz nonlinear systems are studied using an unknown input observer (UIO) design technique. To solve the actuator fault detection and isolation problem, we develop a particular system structure by regrouping the system inputs, which is suitable for UIO design. By filtering the regrouped outputs properly, the same system structure can be developed for sensor fault detection and isolation problem, which allows us to treat the sensor fault detection and isolation problem as an actuator fault detection and isolation problem. To accomplish FDI efficiently, a novel full order nonlinear UIO is designed with a special property suitable for fault isolation purposes, and a necessary and sufficient conditions for its existence are presented. The LMI based sufficient condition enables the designers to use Matlab LMI toolbox and makes the computationally difficult UIO design much easier. For UIO based FDI, the following three problems are investigated: 1) Under what conditions is it possible to isolate single and/or multiple faults? 2) What is the maximum number of faults that can be isolated simultaneously? 3) How to design fault isolation schemes to achieve multiple fault isolation (that is, to make decisions on how many faults have occurred and the location of each fault)? Conditions for problem 1) are derived and the maximum number of faults that can be isolated is determined for problem 2). To solve problem 3), an FDI scheme is designed using a bank of nonlinear UIOs and its design procedure is presented in a step by step fashion. An example is given to show how to use the proposed FDI scheme and simulations results illustrate that the proposed technique works well for FDI in uncertain Lipschitz nonlinear systems. © 2006 IEEE.





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