Abstract
In this paper we present an application to an electrical induction motor of a recently proposed gain-scheduling Fault Detection and Isolation (FDI) filter design method for LPV systems. Starting from a detailed nonlinear mathematical representation of the motor it is shown how, based on a judicious convex interpolation of a family of linearized models, a quasi-LPV approximation can be achieved and used for synthesizing the LPV-FDI filter. The latter is then synthesized by ensuring guaranteed levels of disturbance rejection and fault detection and isolation sensitivity. The resulting diagnostic filter is gain-scheduled and uses a set of motor variables, assumed measurable on-line, as a scheduling vector. The effectiveness of the LPV-FDI framework is illustrated by a numerical example.
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