Active Disturbance Rejection Control(ADRC)possesses robust disturbance rejection capabilities,making it well-suited for longitudinal velocity control.However,the conventional Extended State Observer(ESO)in ADRC fails ...Active Disturbance Rejection Control(ADRC)possesses robust disturbance rejection capabilities,making it well-suited for longitudinal velocity control.However,the conventional Extended State Observer(ESO)in ADRC fails to fully exploit feedback from first-order and higher-order estimation errors and tracking error simultaneously,thereby diminishing the control performance of ADRC.To address this limitation,an enhanced car-following algorithm utilising ADRC is proposed,which integrates the improved ESO with a feedback controller.In comparison to the conventional ESO,the enhanced version effectively utilises multi-order estimation and tracking errors.Specifically,it enhances convergence rates by incorporating feedback from higher-order estimation errors and ensures the estimated value converges to the reference value by utilising tracking error feedback.The improved ESO significantly enhances the disturbance rejection performance of ADRC.Finally,the effectiveness of the proposed algorithm is validated through the Lyapunov approach and experiments.展开更多
基金State Key Laboratory of Intelligent Green Vehicle and Mobility,Grant/Award Number:KFY2417Science and Technology Innovation 2030-“New Generation Artificial Intelligence”Major Project,Grant/Award Number:2022ZD0116305+7 种基金State Key Laboratory of Intelligent Vehicle Safety Technology,Grant/Award Number:IVSTSKL-202402Anhui Province Natural Science Funds for Distinguished Young Scholar,Grant/Award Number:2308085J02National Natural Science Foundation of China,Grant/Award Numbers:U2013601,U20A20225Wuhu Major Scientific and Technological Achievements Engineering Project,Grant/Award Number:2021zc04CAAI-Huawei Mind Spore Open Fund,Grant/Award Number:CAAIXSJLJJ-2022-011ANatural Science Foundation of Hefei,China,Grant/Award Number:202321State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body,Grant/Award Number:32215010Wuhu Municipal Science and Technology Program,Grant/Award Number:2021hg17。
文摘Active Disturbance Rejection Control(ADRC)possesses robust disturbance rejection capabilities,making it well-suited for longitudinal velocity control.However,the conventional Extended State Observer(ESO)in ADRC fails to fully exploit feedback from first-order and higher-order estimation errors and tracking error simultaneously,thereby diminishing the control performance of ADRC.To address this limitation,an enhanced car-following algorithm utilising ADRC is proposed,which integrates the improved ESO with a feedback controller.In comparison to the conventional ESO,the enhanced version effectively utilises multi-order estimation and tracking errors.Specifically,it enhances convergence rates by incorporating feedback from higher-order estimation errors and ensures the estimated value converges to the reference value by utilising tracking error feedback.The improved ESO significantly enhances the disturbance rejection performance of ADRC.Finally,the effectiveness of the proposed algorithm is validated through the Lyapunov approach and experiments.
