Spatial adaptive repetitive learning control for rotating motor systems with non-parametric uncertainties
CHEN Qiang
SU Yang
SHI Hui-hui
HE Xiong-xiong
Abstract：A spatial adaptive fully-saturated repetitive learning control method is proposed for rotating motor systems that perform spatial repetitive tasks.The spatial differential operator is introduced to transform the controlled system from the time domain to the spatial domain.By utilizing the spatial periodic repetitive operation characteristics of rotating motor systems,a spatial adaptive fully-saturated repetitive learning controller is designed to achieve high-precision tracking of desired trajectory for the angular velocity of rotating motor.The fully-saturated repetitive learning law is constructed to estimate and compensate for system non-parametric uncertainties with spatial periodic characteristics,and the estimated value can be limited within the specified bounds.Finally,the error convergence is analyzed through the Lyapunov stability theory,and simulation results are provided to verify the effectiveness of the proposed method.
Keywords：spatial repetitive learning controladaptive controlfully-saturated learning lawnon-parametric uncertain-ties
Publication Date：2026-01-30
Online Publishing Date：2026-02-05(First online date of this platform, not the publication date of the document)
Pages：7( 169-175 )