Improved fixed-time sliding mode control for trajectory tracking of robot manipulators using adaptive disturbance observer

Precise and fast motion trajectory tracking response for rigid robot manipulator systems (RRMSs) pose a significant challenge due to the system uncertainties and unknown disturbances during operation. Despite extensive research, the varied and fluctuating factors in these harsh conditions consistently degrade the trajectory tracking performance of RRMSs. To address this issue, a fixed-time sliding mode control (FSMC) with an adaptive fixed-time disturbance observer (AFDO) offers an effective solution. Firstly, an improved FSMC method using a new sliding mode manifold is proposed, which can eliminate the dependence of the settling time on initial values of system and avoid singularity. Subsequently, a AFDO based on the equivalent input is presented to estimate the lump disturbances in real time, which introduce adaptive gain to further mitigate the effects of disturbances. Finally, the sufficient conditions for establishing the fixed-time stability of RRMSs are derived via Lyapunov theory. The results of numerical simulations and control experiments show that the proposed method can enhance the global fixed-time stability and reduce the high-frequency chattering. Compared with existing methods, it exhibits superior trajectory tracking control accuracy for RRMSs.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Published
2026-04-21
DOI
https://doi.org/10.1177/09544062261434273
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Improved fixed-time sliding mode control for trajectory tracking of robot manipulators using adaptive disturbance observer

Xuhui Xia, Lei Wang, Zelin Zhang, Qing Liu et al.
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Adaptive Control of Nonlinear Systems
article

Improved fixed-time sliding mode control for trajectory tracking of robot manipulators using adaptive disturbance observer

Xuhui Xia, Lei Wang, Zelin Zhang, Qing Liu, Ailong Wu
article en

Abstract

Precise and fast motion trajectory tracking response for rigid robot manipulator systems (RRMSs) pose a significant challenge due to the system uncertainties and unknown disturbances during operation. Despite extensive research, the varied and fluctuating factors in these harsh conditions consistently degrade the trajectory tracking performance of RRMSs. To address this issue, a fixed-time sliding mode control (FSMC) with an adaptive fixed-time disturbance observer (AFDO) offers an effective solution. Firstly, an improved FSMC method using a new sliding mode manifold is proposed, which can eliminate the dependence of the settling time on initial values of system and avoid singularity. Subsequently, a AFDO based on the equivalent input is presented to estimate the lump disturbances in real time, which introduce adaptive gain to further mitigate the effects of disturbances. Finally, the sufficient conditions for establishing the fixed-time stability of RRMSs are derived via Lyapunov theory. The results of numerical simulations and control experiments show that the proposed method can enhance the global fixed-time stability and reduce the high-frequency chattering. Compared with existing methods, it exhibits superior trajectory tracking control accuracy for RRMSs.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Hubei Normal University (CN), Wuhan University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Adaptive Control of Nonlinear Systems
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.