Research on a Force-Sensorless Control Method for an Agricultural Manipulator Based on Fuzzy Sliding Mode Control and a Disturbance Observer

Agricultural manipulators are vulnerable to disturbances induced by compliant and hard contact, variations in object stiffness, and sudden constraint release during branch severing in fruit harvesting and pruning. External force/torque sensors, however, are costly, difficult to install, and poorly suited to agricultural environments. This study proposes a force-sensorless compliant control method integrating fuzzy sliding mode control and a disturbance observer (FSMC-DOB). Experiments are conducted on an RML63 6-DOF manipulator. Fuzzy sliding mode control enhances joint trajectory-tracking robustness, while fuzzy adaptation mitigates the chattering inherent in conventional sliding mode control. A disturbance observer estimates external disturbances at the wrist joints, and bias learning, smooth saturation, and task-specific compliance compensation enable contact disturbance estimation and control adjustment without external force sensing. A dual-timescale disturbance feature-extraction and contact-confidence mapping scheme suppresses false contact triggering caused by short-duration disturbance transients and improves the robustness of contact detection. In addition, a snap/release event detector with short-term impact suppression reduces end-effector rebound and torque shocks after sudden constraint removal during pruning. MATLAB simulations show satisfactory free-motion tracking. Under soft-contact harvesting, the maximum and RMS compression deflections are reduced to 0.090 rad and 0.046 rad, respectively, outperforming PID and conventional sliding mode control. Under hard-contact pruning, the global RMSE and post-snap peak error are 0.1491 rad and 0.3722 rad. ROS–Gazebo simulations and physical experiments further confirm motion continuity, reliable contact identification, and engineering feasibility, demonstrating improved stability, safety, and adaptability in complex agricultural contact operations.

Authors

Institutions

Publication Details

Journal
Agronomy
Published
2026-10-04
DOI
https://doi.org/10.3390/agronomy16191940
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

Research on a Force-Sensorless Control Method for an Agricultural Manipulator Based on Fuzzy Sliding Mode Control and a Disturbance Observer

Wenshuo Gao, Kun Jiang, Bao-guo Yao, Xifeng Liang
Agronomy
Adaptive Control of Nonlinear Systems
article

Research on a Force-Sensorless Control Method for an Agricultural Manipulator Based on Fuzzy Sliding Mode Control and a Disturbance Observer

Wenshuo Gao, Kun Jiang, Bao-guo Yao, Xifeng Liang
article en

Abstract

Agricultural manipulators are vulnerable to disturbances induced by compliant and hard contact, variations in object stiffness, and sudden constraint release during branch severing in fruit harvesting and pruning. External force/torque sensors, however, are costly, difficult to install, and poorly suited to agricultural environments. This study proposes a force-sensorless compliant control method integrating fuzzy sliding mode control and a disturbance observer (FSMC-DOB). Experiments are conducted on an RML63 6-DOF manipulator. Fuzzy sliding mode control enhances joint trajectory-tracking robustness, while fuzzy adaptation mitigates the chattering inherent in conventional sliding mode control. A disturbance observer estimates external disturbances at the wrist joints, and bias learning, smooth saturation, and task-specific compliance compensation enable contact disturbance estimation and control adjustment without external force sensing. A dual-timescale disturbance feature-extraction and contact-confidence mapping scheme suppresses false contact triggering caused by short-duration disturbance transients and improves the robustness of contact detection. In addition, a snap/release event detector with short-term impact suppression reduces end-effector rebound and torque shocks after sudden constraint removal during pruning. MATLAB simulations show satisfactory free-motion tracking. Under soft-contact harvesting, the maximum and RMS compression deflections are reduced to 0.090 rad and 0.046 rad, respectively, outperforming PID and conventional sliding mode control. Under hard-contact pruning, the global RMSE and post-snap peak error are 0.1491 rad and 0.3722 rad. ROS–Gazebo simulations and physical experiments further confirm motion continuity, reliable contact identification, and engineering feasibility, demonstrating improved stability, safety, and adaptability in complex agricultural contact operations.

AgronomyVol. 16(19)
China Jiliang University (CN)
Openalex Percentile: Top 15%
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.