Deterministic Adaptive Robust Control With a Novel Optimal Gain Design Approach for a Fuzzy 2-DOF Lower Limb Exoskeleton Robot System

To enhance the lower limbs' rehabilitation training of stroke patients, in this article, a deterministic adaptive robust control with control gain parameters optimized by a novel cooperative game theory is proposed for the two-degree-of-freedom (DOF) lower limb exoskeleton robot system (LLERs)...

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Bibliographic Details
Published inIEEE transactions on fuzzy systems Vol. 29; no. 8; pp. 2373 - 2387
Main Authors Han, Jiang, Yang, Siyang, Xia, Lian, Chen, Ye-Hwa
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive control
Adaptive robust control
cooperative game theory
Cost function
Degrees of freedom
Disturbances
exoskeleton robot
Exoskeletons
Fuzzy set theory
Fuzzy sets
Gait
Game theory
Limbs
Parameter estimation
Rehabilitation
Robots
Robust control
Training
Uncertainty
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Summary:To enhance the lower limbs' rehabilitation training of stroke patients, in this article, a deterministic adaptive robust control with control gain parameters optimized by a novel cooperative game theory is proposed for the two-degree-of-freedom (DOF) lower limb exoskeleton robot system (LLERs) with uncertainties and external disturbances. On the one hand, the deterministic adaptive robust control put forward will guarantee the uniform boundedness and uniform ultimate boundedness of gait constraint deviation and parameter estimation error. On the other hand, for uncertainties and external disturbance (possibly fast time-varying), which will arise in the two-DOF LLERs inevitably, we suppose that these uncertainties and disturbances are bounded, and their bounds are lying within the fuzzy sets, which can be characterized by membership functions; with such descriptions and control performance analysis, a novel cooperative game with two players participated will be formulated to seek the Pareto optimal solutions for the control gains of deterministic adaptive robust control proposed, and furthermore, the existence of optimal solutions is also shown by invoking a numerical technique. Eventually, the simulation results presented have verified the effectiveness of our proposed methodology on improving rehabilitation training of lower limbs.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2020.2999739