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Double Iterative Compensation Learning Control for Active Training of Upper Limb Rehabilitation Robot

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  • Robot and Applications
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Abstract

In this paper, the problem of non parametric uncertainty in the active training stage of stroke patients is discussed. On the basis of the nonlinear iterative learning theory, a double iterative compensation learning control is proposed. This method adopts the strategy of double loop iteration which can adjust controller parameters in real time to satisfy the patients’ condition. First, a class of saturated nonlinear functions is introduced to satisfy the requirement of position constraints. Then, reference trajectory self-modified strategy is designed for the initial positioning error. Meanwhile, the iterative compensation controller is designed according to the active torque of the patient, which can provide appropriate power compensation to the affected limb and update the parameters of the iterative learning controller continuously. At last, the convergence condition and its proof are given. The simulation results show the effectiveness and practicability of the proposed double iterative compensation optimal control strategy.

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Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Xuefeng Zhu & Jianhui Wang

Authors
  1. Xuefeng Zhu
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  2. Jianhui Wang
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Corresponding author

Correspondence to Xuefeng Zhu.

Additional information

Recommended by Associate Juhoon Back under the direction of Editor Jessie (Ju H.) Park. This work was supported by “Fundamental Research Funds for the Central Universities” (N150804001), 2015 Liaoning province Doctoral Fund (201501142) and National Natural Science Foundation of China (61503070).

Xuefeng Zhu received the Ph.D. degree in Northeastern University in 2017. Her research interests include modeling, simulating, control and operation optimization of complex process system.

Jianhui Wang is a doctoral supervisor at Northeastern University. Her research interests include modeling, simulating, control and operation optimization of complex process system.

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Zhu, X., Wang, J. Double Iterative Compensation Learning Control for Active Training of Upper Limb Rehabilitation Robot. Int. J. Control Autom. Syst. 16, 1312–1322 (2018). https://doi.org/10.1007/s12555-017-0163-6

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  • DOI: https://doi.org/10.1007/s12555-017-0163-6

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