Fuzzy logic system-based force tracking control of robot in highly dynamic environments

Chengguo Liu, Junyang Li, Zeyu Li, Xiutao Chen
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Abstract

Purpose

The study aims to equip robots with the ability to precisely maintain interaction forces, which is crucial for tasks such as polishing in highly dynamic environments with unknown and varying stiffness and geometry, including those found in airplane wings or thin, soft materials. The purpose of this study is to develop a novel adaptive force-tracking admittance control scheme aimed at achieving a faster response rate with higher tracking accuracy for robot force control.

Design/methodology/approach

In the proposed method, the traditional admittance model is improved by introducing a pre-proportional-derivative controller to accelerate parameter convergence. Subsequently, the authors design an adaptive law based on fuzzy logic systems (FLS) to compensate for uncertainties in the unknown environment. Stability conditions are established for the proposed method through Lyapunov analysis, which ensures the force tracking accuracy and the stability of the coupled system consisting of the robot and the interaction environment. Furthermore, the effectiveness and robustness of the proposed control algorithm are demonstrated by simulation and experiment.

Findings

A variety of unstructured simulations and experimental scenarios are designed to validate the effectiveness of the proposed algorithm in force control. The outcomes demonstrate that this control strategy excels in providing fast response, precise tracking accuracy and robust performance.

Practical implications

In real-world applications spanning industrial, service and medical fields where accurate force control by robots is essential, the proposed method stands out as both practical and straightforward, delivering consistently satisfactory performance across various scenarios.

Originality/value

This research introduces a novel adaptive force-tracking admittance controller based on FLS and validated through both simulations and experiments. The proposed controller demonstrates exceptional performance in force control within environments characterized by unknown and varying.

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高动态环境中基于模糊逻辑系统的机器人力跟踪控制
目的本研究旨在使机器人具备精确保持相互作用力的能力,这对于在刚度和几何形状未知且不断变化的高动态环境(包括飞机机翼或薄而软的材料)中执行抛光等任务至关重要。本研究的目的是开发一种新型自适应力跟踪导纳控制方案,旨在为机器人力控制实现更快的响应速度和更高的跟踪精度。在所提出的方法中,通过引入预比例-派生控制器来加速参数收敛,从而改进了传统的导纳模型。随后,作者设计了基于模糊逻辑系统(FLS)的自适应法则,以补偿未知环境中的不确定性。通过 Lyapunov 分析,为所提出的方法建立了稳定性条件,从而确保了力跟踪精度以及由机器人和交互环境组成的耦合系统的稳定性。此外,还通过仿真和实验证明了所提控制算法的有效性和鲁棒性。研究结果设计了多种非结构化仿真和实验场景,以验证所提算法在力控制中的有效性。实际意义在工业、服务和医疗等领域的实际应用中,机器人的精确力控制至关重要,而本文提出的方法既实用又简单,在各种场景下都能提供令人满意的性能。所提出的控制器在以未知和变化为特征的环境中显示出卓越的力控制性能。
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