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下肢外骨骼的简化自适应模糊解耦控制

Reduced Adaptive Fuzzy Decoupling Control for Lower Limb Exoskeleton.

作者信息

Sun Wei, Lin Jhih-Wei, Su Shun-Feng, Wang Ning, Er Meng Joo

出版信息

IEEE Trans Cybern. 2021 Mar;51(3):1099-1109. doi: 10.1109/TCYB.2020.2972582. Epub 2021 Feb 17.

Abstract

This article reports our study on a reduced adaptive fuzzy decoupling control for our lower limb exoskeleton system which typically is a multi-input-multi-output (MIMO) uncertain nonlinear system. To show the applicability and generality of the proposed control methods, a more general MIMO uncertain nonlinear system model is considered. By decoupling control, the entire MIMO system is separated into several MISO subsystems. In our experiments, such a system may have problems (even unstable) if a traditional fuzzy approximator is used to estimate the complicated coupling terms. In this article, to overcome this problem, a reduced adaptive fuzzy system together with a compensation term is proposed. Compared to traditional approaches, the proposed fuzzy control approach can reduce possible chattering phenomena and achieve better control performance. By employing the proposed control scheme to an actual 2-DOF lower limb exoskeleton rehabilitation robot system, it can be seen from the experimental results that, as expected, it has good performance to track the model trajectory of a human walking gait. Therefore, it can be concluded that the developed approach is effective for the control of a lower limb exoskeleton system.

摘要

本文报道了我们对下肢外骨骼系统的一种简化自适应模糊解耦控制的研究,该系统通常是一个多输入多输出(MIMO)不确定非线性系统。为了展示所提出控制方法的适用性和通用性,考虑了一个更一般的MIMO不确定非线性系统模型。通过解耦控制,整个MIMO系统被分解为几个单输入多输出(MISO)子系统。在我们的实验中,如果使用传统模糊逼近器来估计复杂的耦合项,这样的系统可能会出现问题(甚至不稳定)。在本文中,为了克服这个问题,提出了一种简化自适应模糊系统以及一个补偿项。与传统方法相比,所提出的模糊控制方法可以减少可能的抖振现象并实现更好的控制性能。通过将所提出的控制方案应用于实际的两自由度下肢外骨骼康复机器人系统,从实验结果可以看出,正如预期的那样,它在跟踪人类步行步态的模型轨迹方面具有良好的性能。因此,可以得出结论,所开发的方法对于下肢外骨骼系统的控制是有效的。

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