模糊机械臂系统的最优鲁棒约束跟随控制设计与实验验证。

IF 6.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions Pub Date : 2025-03-01 DOI:10.1016/j.isatra.2024.12.041

Hao Sun , Xin Wang , Luchuan Tu , MianHao Wang , Ke Shao

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引用次数: 0

摘要

机器人机械手作为典型的复杂机械系统，具有结构复杂、参数不确定、易受外界干扰等特点。本文从二阶伺服约束的角度出发，提出了一种鲁棒约束跟随控制算法，该算法能满足模糊集理论描述的系统不确定性下机器人机械手系统的控制要求。同时，该算法还保证了均匀约束性（UB）和均匀极限约束性（UUB）的确定性能。建立了基于模糊信息的系统性能指标函数，并通过最小化系统性能指标函数，解决了控制器增益参数的优化设计问题。数值模拟和实验结果验证了鲁棒控制器和控制参数优化方法的有效性。

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Optimal robust constraint following control design and experimental validation for fuzzy robotic manipulator system

As a typically complex mechanical system, robotic manipulator has the characteristics of complex structure, parameter uncertainty and vulnerability to external interference. From the perspective of second-order servo constraints, this paper proposes a robust constraint following control algorithm, which can meet the control requirements of robotic manipulator system under system uncertainty, which is described by fuzzy set theory. It also guarantees the deterministic performance of uniform boundedness (UB) and uniform ultimate boundedness (UUB). The system performance index function based on fuzzy information is established, and by minimizing the system performance index function, the optimization design problem of the controller gain parameter is solved. Numerical simulations and experimental results verify the efficacy of the robust controller and control parameter optimization method.

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来源期刊

ISA transactions 工程技术-工程：综合

CiteScore

11.70

自引率

12.30%

发文量

824

审稿时长

4.4 months

期刊介绍： ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.