Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping

Direct-drive servo systems are extensively applied in biomimetic robotics and other bionic applications, but their performance is susceptible to uncertainties and disturbances. This paper proposes an adaptive disturbance rejection Zeta-backstepping control scheme with adjustable damping ratios to en...

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Main Authors: Zhongjin Zhang, Zhitai Liu, Weiyang Lin, Wei Cheng
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Biomimetics
Subjects:
Online Access:https://www.mdpi.com/2313-7673/9/12/780
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author Zhongjin Zhang
Zhitai Liu
Weiyang Lin
Wei Cheng
author_facet Zhongjin Zhang
Zhitai Liu
Weiyang Lin
Wei Cheng
author_sort Zhongjin Zhang
collection DOAJ
description Direct-drive servo systems are extensively applied in biomimetic robotics and other bionic applications, but their performance is susceptible to uncertainties and disturbances. This paper proposes an adaptive disturbance rejection Zeta-backstepping control scheme with adjustable damping ratios to enhance system robustness and precision. An iron-core permanent magnet linear synchronous motor (PMLSM) was employed as the experimental platform for the development of a dynamic model that incorporates compensation for friction and cogging forces. To address model parameter uncertainties, an indirect parameter adaptation strategy based on a recursive least squares algorithm was introduced. It updates parameters based on the system state instead of output error, ensuring robust parameter convergence. An integral sliding mode observer (ISMO) was constructed to estimate and compensate for residual uncertainties, achieving finite-time state estimation. The proposed Zeta-backstepping controller enables adjustable damping ratios through parameterized control laws, offering flexibility in achieving desired dynamic performance. System stability and bounded tracking performance were validated via a second-order Lyapunov function analysis. Experimental results on a real PMLSM platform demonstrated that, while achieving adjustable damping ratio dynamic characteristics, there is a significant improvement in tracking accuracy and disturbance suppression. This underscores the scheme’s potential for advancing precision control in biomimetic robotics and other direct-drive system applications.
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institution Kabale University
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spelling doaj-art-ebda7074b08b423db71442ef8b51c33b2024-12-27T14:13:32ZengMDPI AGBiomimetics2313-76732024-12-0191278010.3390/biomimetics9120780Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-BacksteppingZhongjin Zhang0Zhitai Liu1Weiyang Lin2Wei Cheng3Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, ChinaResearch Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, ChinaResearch Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, ChinaDevol Advanced Automation, Inc., Shenzhen 518101, ChinaDirect-drive servo systems are extensively applied in biomimetic robotics and other bionic applications, but their performance is susceptible to uncertainties and disturbances. This paper proposes an adaptive disturbance rejection Zeta-backstepping control scheme with adjustable damping ratios to enhance system robustness and precision. An iron-core permanent magnet linear synchronous motor (PMLSM) was employed as the experimental platform for the development of a dynamic model that incorporates compensation for friction and cogging forces. To address model parameter uncertainties, an indirect parameter adaptation strategy based on a recursive least squares algorithm was introduced. It updates parameters based on the system state instead of output error, ensuring robust parameter convergence. An integral sliding mode observer (ISMO) was constructed to estimate and compensate for residual uncertainties, achieving finite-time state estimation. The proposed Zeta-backstepping controller enables adjustable damping ratios through parameterized control laws, offering flexibility in achieving desired dynamic performance. System stability and bounded tracking performance were validated via a second-order Lyapunov function analysis. Experimental results on a real PMLSM platform demonstrated that, while achieving adjustable damping ratio dynamic characteristics, there is a significant improvement in tracking accuracy and disturbance suppression. This underscores the scheme’s potential for advancing precision control in biomimetic robotics and other direct-drive system applications.https://www.mdpi.com/2313-7673/9/12/780direct-drive systemparameter adaptiveintegral sliding mode observerdamping ratiosbackstepping methodcogging force
spellingShingle Zhongjin Zhang
Zhitai Liu
Weiyang Lin
Wei Cheng
Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping
Biomimetics
direct-drive system
parameter adaptive
integral sliding mode observer
damping ratios
backstepping method
cogging force
title Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping
title_full Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping
title_fullStr Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping
title_full_unstemmed Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping
title_short Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping
title_sort adaptive disturbance rejection motion control of direct drive systems with adjustable damping ratio based on zeta backstepping
topic direct-drive system
parameter adaptive
integral sliding mode observer
damping ratios
backstepping method
cogging force
url https://www.mdpi.com/2313-7673/9/12/780
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