Robust Finite-Time Control of Multi-Link Manipulators: A Data-Driven Model-Free Approach

In recognising both the emerging industrial applications of multi-link robotic manipulators and the inherent challenges of modelling and controlling their highly complex nonlinear dynamics, this work proposes a completely model-free terminal sliding mode control (MFTSMC) design approach to reduce the sensitivity and complexity often associated with model-based routines. Consequently, the proposed design achieves strong robustness, simplicity, and good operation tuning by eliminating the need for system modelling and enabling direct operator–machine interaction. Simulink simulations on a 3-link case subjected to different disturbance conditions (free, low-frequency, high-frequency, and mixed) show rapid dynamic convergence, good tracking precision, and strong disturbance rejection. The system reaches the sliding surface within 0.07 s, maintains steady-state errors around 10−2, and achieves a smooth torque response with low energy costs. The benchmark results confirm the finite-time convergence and demonstrate that the proposed framework is practical and scalable for multi-DOF systems and has potential for underactuated manipulators. It should be noted that a generalised dynamic model for a planar n-link manipulator is presented in the study for (1) the ground truth of the manipulator in simulation (not for the MFTSMC design), (2) the model-based controller designs in comparison to the MFTSMC, and (3) understanding the dynamic characteristics.

Authors

Institutions

Publication Details

Journal
Machines
Published
2026-01-26
DOI
https://doi.org/10.3390/machines14020146
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robust Finite-Time Control of Multi-Link Manipulators: A Data-Driven Model-Free Approach

Quanmin Zhu, Xiaoang Zhang
Machines
Adaptive Control of Nonlinear Systems
article

Robust Finite-Time Control of Multi-Link Manipulators: A Data-Driven Model-Free Approach

Quanmin Zhu, Xiaoang Zhang
article en

Abstract

In recognising both the emerging industrial applications of multi-link robotic manipulators and the inherent challenges of modelling and controlling their highly complex nonlinear dynamics, this work proposes a completely model-free terminal sliding mode control (MFTSMC) design approach to reduce the sensitivity and complexity often associated with model-based routines. Consequently, the proposed design achieves strong robustness, simplicity, and good operation tuning by eliminating the need for system modelling and enabling direct operator–machine interaction. Simulink simulations on a 3-link case subjected to different disturbance conditions (free, low-frequency, high-frequency, and mixed) show rapid dynamic convergence, good tracking precision, and strong disturbance rejection. The system reaches the sliding surface within 0.07 s, maintains steady-state errors around 10−2, and achieves a smooth torque response with low energy costs. The benchmark results confirm the finite-time convergence and demonstrate that the proposed framework is practical and scalable for multi-DOF systems and has potential for underactuated manipulators. It should be noted that a generalised dynamic model for a planar n-link manipulator is presented in the study for (1) the ground truth of the manipulator in simulation (not for the MFTSMC design), (2) the model-based controller designs in comparison to the MFTSMC, and (3) understanding the dynamic characteristics.

MachinesVol. 14(2)
University of the West of England (GB), University of Bristol (GB)
Openalex Percentile: Top 77%
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.