Adaptive Parameter Identification Based Tracking Control of Servo Systems with Unknown Actuator Backlash Compensation

This paper presents a robust tracking control strategy for servo systems with unknown backlash, employing adaptive parameter identification to address performance degradation caused by backlash nonlinearities. In high-precision positioning and rapid-response applications, backlash significantly compromises system performance. To address this challenge, a servo system model incorporating backlash nonlinearities is developed, and a novel adaptive inverse function is introduced for backlash compensation. The estimation error of unidentified parameters is indirectly obtained through the design of a state observer. Minimizing the estimation error facilitates the accurate identification of model parameters, encompassing those associated with backlash. Additionally, an adaptive law is designed to estimate the unknown upper bounds of disturbance dynamics. Then, a robust tracking controller is proposed, which dynamically adjusts control inputs in real time based on identified backlash parameters to counteract backlash-induced adverse effects. Theoretical analysis and simulation results demonstrate that the proposed strategy significantly improves tracking performance in servo systems with unknown backlash.

Authors

Institutions

Publication Details

Journal
Actuators
Published
2025-06-11
DOI
https://doi.org/10.3390/act14060288
Citations
1
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
1.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Adaptive Parameter Identification Based Tracking Control of Servo Systems with Unknown Actuator Backlash Compensation

Xiongfeng Deng, Binzi Xu, Liang Tao, Hailan Du
1 citations
Actuators
Iterative Learning Control Systems
1.21
article

Adaptive Parameter Identification Based Tracking Control of Servo Systems with Unknown Actuator Backlash Compensation

Xiongfeng Deng, Binzi Xu, Liang Tao, Hailan Du
article en
1 citations

Abstract

This paper presents a robust tracking control strategy for servo systems with unknown backlash, employing adaptive parameter identification to address performance degradation caused by backlash nonlinearities. In high-precision positioning and rapid-response applications, backlash significantly compromises system performance. To address this challenge, a servo system model incorporating backlash nonlinearities is developed, and a novel adaptive inverse function is introduced for backlash compensation. The estimation error of unidentified parameters is indirectly obtained through the design of a state observer. Minimizing the estimation error facilitates the accurate identification of model parameters, encompassing those associated with backlash. Additionally, an adaptive law is designed to estimate the unknown upper bounds of disturbance dynamics. Then, a robust tracking controller is proposed, which dynamically adjusts control inputs in real time based on identified backlash parameters to counteract backlash-induced adverse effects. Theoretical analysis and simulation results demonstrate that the proposed strategy significantly improves tracking performance in servo systems with unknown backlash.

ActuatorsVol. 14(6)
Anhui Polytechnic University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 20%
Iterative Learning Control Systems
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.