Disturbance Estimation for High-Degree-of-Freedom Euler-Lagrangian Systems Using Sliding Mode Observer without Matching Conditions
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This paper proposes a novel observer-based disturbance estimation method for high degree-of-freedom Euler-Lagrangian systems using an unknown input-output (UIO) sliding mode observer (SMO). Different from the previous SMO methods, this approach does not assume the matching condition of the disturbances. Besides, compared to the conventional disturbance estimation methods, the proposed method does not require the calculation of the inverse inertia matrices and accurate measurement of system velocities. This advantage resolves the concerns of heavy computational load and amplified noise for practical problems like external torque estimation of high degree-of-freedom manipulators in safe human-robot collaboration. We achieve this by defining a novel linearized model for the Euler-Lagrangian system and designing a sliding-mode-based disturbance observer. The estimation precision of the observer is ensured by the Lyapunov-based stability proof and the equivalent control theory of sliding mode. At the end of this paper, the method is implemented on a seven-degree-of-freedom robot manipulator, and the experimental results confirm its decent performance and potential to be applied in practice.
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