Embedded Estimation Of Fault Parameters In An Unmanned Aerial Vehicle
PROCEEDINGS OF THE 2006 IEEE INTERNATIONAL CONFERENCE ON CONTROL APPLICATIONS, VOLS 1-4(2006)
摘要
In this paper, we present a model-based approach for estimating fault conditions in an aircraft. We formulate fault estimation as a convex optimization problem, where estimates are obtained by solving a constrained quadratic program (QP). A moving horizon framework is used to enable recursive implementation of the constrained QP of fixed size. The estimation scheme takes into account a priori known monotonicity constraints on the faults. Monotonicity implies that the fault conditions can only deteriorate with time. We validate the proposed estimation scheme on a detailed nonlinear simulation model of the Aerosonde unmanned aerial vehicle (UAV) in the presence of winds and turbulence. An excellent performance of the developed approach is demonstrated.
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关键词
i. i ntroduction,atmospheric modeling,computational modeling,convex programming,acceleration,estimation,remotely operated vehicles,simulation model,quadratic programming,mobile robots,parameter estimation,quadratic program,convex optimization,predictive models,information systems
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