Reduced Adaptive Fuzzy Decoupling Control for Lower Limb Exoskeleton

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.

MeSH terms

  • Algorithms
  • Biomechanical Phenomena / physiology
  • Equipment Design
  • Exoskeleton Device*
  • Fuzzy Logic*
  • Gait / physiology
  • Humans
  • Lower Extremity / physiology*
  • Machine Learning
  • Nonlinear Dynamics
  • Signal Processing, Computer-Assisted*
  • Walking / physiology