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Highly Nonlinear Flexible Manipulator State Estimation Using the Extended and the Unscented Kalman Filters

Mohammed Bakhti(1*), Badr Bououlid Idrissi(2)

(1) Moulay Ismail University, Ecole Nationale Supérieure d’Arts et Métiers, Morocco
(2) Moulay Ismail University, Ecole Nationale Supérieure d’Arts et Métiers, Morocco
(*) Corresponding author



This paper proposes and compares the state estimation scheme and performance of the Extended Kalman Filter and the Unscented Kalman Filter. A highly nonlinear flexible manipulator is targeted by the study to evaluate the effectiveness and robustness of the proposed filters facing an online accurate estimation problem. An Euler-Bernoulli cantilever beam models the manipulator, and the elastic movement is approximated using the assumed modes method. The Hamilton’s principle yields the system nonlinear equations. This article compares, via the included numerical simulation results, the efficiency of the state estimate reflected by the estimation error and the time required by the filters to converge.
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Extended Kalman Filter; Flexible Manipulator; Nonlinear Filtering; Non-additive Noise; Unscented Kalman Filter

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