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Disturbance Suppression and System Design Based on Parallel-Equivalent-Input-Disturbance Approach

Xiang Yin, Jinhua She, Zhentao Liu, Yonghua Xiong

2023IEEE Transactions on Systems Man and Cybernetics Systems24 citationsDOI

Abstract

The conventional equivalent-input-disturbance (EID) approach exhibits two estimation errors that degrade the disturbance-suppression performance. This article aims to suppress the effects of estimation errors and improve disturbance-suppression performance. Taking the errors to be an artificial disturbance, several other EID compensators are connected to suppress the disturbance. Simplifying the connected EID compensators yields the design of a parameter, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> , in the conventional EID estimator. Based on such an idea, this article presents a parallel-EID (PEID) approach, which has many merits. The disturbance-suppression performance of this approach is better than that of previous related studies, while its configuration is simple and universal. The physical meaning of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> is clear and explains the reason why the disturbance-suppression performance improves. Furthermore, this article designs a novel virtual filter for transforming the PEID-based control system into an equivalent configuration that is easy to derive stability conditions. Finally, the PEID approach is applied in controlling the speed of a permanent magnet synchronous motor. Additionally, comparisons between the conventional EID, improved EID, PEID, and modified EID approaches show the validity and superiority of the PEID approach.

Topics & Concepts

Disturbance (geology)EstimatorControl theory (sociology)Stability (learning theory)Computer scienceNotationFilter (signal processing)AlgorithmMathematicsControl (management)Artificial intelligenceArithmeticStatisticsMachine learningComputer visionPaleontologyBiologySensorless Control of Electric MotorsAdaptive Control of Nonlinear SystemsMultilevel Inverters and Converters
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