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Tunable Nonlinear-Function-Based Estimators for Mismatched Disturbances and Performance Analysis | IEEE Journals & Magazine | IEEE Xplore

Tunable Nonlinear-Function-Based Estimators for Mismatched Disturbances and Performance Analysis


Abstract:

In this article, based on the concept of an equivalent-input-disturbance (EID), a tunable nonlinear-function-based estimator is developed for fast and efficient control o...Show More

Abstract:

In this article, based on the concept of an equivalent-input-disturbance (EID), a tunable nonlinear-function-based estimator is developed for fast and efficient control of unknown and mismatched disturbances of a tracking control system, and the control performances are analyzed. A great superiority over the conventional EID estimators is that the gain is varying and tunable with respect to an intermediate disturbance-rejection performance indicator. First, the control task is divided into the control of reference-tracking and disturbance-rejection, and the corresponding control mechanisms are clarified. For the disturbance-rejection control, explanation of the intermediate performance indicator is provided and a tunable nonlinear-function-based EID estimator is constructed. Then, the tunability condition for the varying gain of the developed EID estimator is given. A relation between control performances and control parameters is clarified a theoretical analysis. An input-to-state stability condition is derived for the closed-loop control system. Finally, comparisons with other methods through simulations and experiments demonstrate fast disturbance-rejection response, weak noise impact, and strong robustness of the developed method.
Published in: IEEE Transactions on Industrial Electronics ( Volume: 71, Issue: 9, September 2024)
Page(s): 11453 - 11464
Date of Publication: 06 December 2023

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