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Designing adaptive robust extended Kalman filter based on Lyapunov-based controller for robotics manipulators

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Document pages: 6 pages

Abstract: In this paper, a position and velocity estimation method for roboticmanipulators which are affected by constant bounded disturbances is considered.The tracking control problem is formulated as a disturbance rejection problem,with all the unknown parameters and dynamic uncertainties lumped intodisturbance. Using adaptive robust extended Kalman filter(AREKF) the movementand velocity of each joint is predicted to use in discontinuous Lyapunov-basedcontroller structure. The parameters of the error dynamics have been validatedoff-line by real data. Computer simulation results given for a two degree offreedom manipulator demonstrate the efficacy of the improved Kalman Filter bycomparing the performance of EKF and improved AREKF. Although it is shown thataccurate trajectory tracking can be achieved by using the proposed controller.

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