基于规定性能函数的滑模控制及其在基于sea的下肢外骨骼中的应用。

IF 2.9 Q2 ROBOTICS
Frontiers in Robotics and AI Pub Date : 2025-03-04 eCollection Date: 2025-01-01 DOI:10.3389/frobt.2025.1534040
Feilong Zhang, Tian Wang, Liang Zhang, Enming Shi, Chengchao Wang, Ning Li, Yu Lu, Bi Zhang
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引用次数: 0

摘要

针对离散单输入单输出系统,提出了一种基于规定性能函数的滑模控制方法。控制器设计的目的是将跟踪误差保持在由性能函数描述的预定义收敛区域内。但由于控制器结构固定,限制了该方法的适用性和通用性。为了解决这一问题,我们将控制器分为两部分,并分析了规定性能控制(PPC)方法的原理。然后我们可以用基于模型的控制方法代替控制器的线性部分,以适应被控系统的具体特性。与现有的方法相比,在系统模型不准确的情况下,在跟踪误差在规定范围内的情况下,通过引入惩罚常数来改变系统的暂态特性,可以提高系统的平滑度或响应速度。最后,通过数值仿真和下肢外骨骼实验验证了所建立的结果和所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sliding-mode control based on prescribed performance function and its application to a SEA-Based lower limb exoskeleton.

A sliding-mode control based on a prescribed performance function is proposed for discrete-time single-input single-output systems. The controller design aims to maintain the tracking error in a predefined convergence zone described by a performance function. However, due to the fixed structure of the controller, the applicability and universality of this method are limited. To address this issue, we separate the controller into two parts and analyze the principle of the prescribed performance control (PPC) method. Then we can replace the linear part of the controller with model-based control methods to adapt to the specific characteristics of the controlled system. Compared with current works, when the established system model is inaccurate, we can enhance the smoothness or response speed of the system by introducing a penalty constant to alter the system's transient characteristics while the tracking error is within the prescribed domain. Finally, numerical comparison simulations and a lower limb exoskeleton experiment illustrate the established results and the effectiveness of the proposed method.

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来源期刊
CiteScore
6.50
自引率
5.90%
发文量
355
审稿时长
14 weeks
期刊介绍: Frontiers in Robotics and AI publishes rigorously peer-reviewed research covering all theory and applications of robotics, technology, and artificial intelligence, from biomedical to space robotics.
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