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General Type-2 Fuzzy Gain Scheduling PID Controller with Application to Power-Line Inspection Robots

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Abstract

In this paper, a general type-2 fuzzy gain scheduling PID (GT2FGS-PID) controller is presented to achieve self-balance adjustment of the power-line inspection (PLI) robot system. As the PLI robot system is an under-actuated nonlinear system, obtaining the full information of the four-state variables is necessary to balance the PLI robot. However, as the number of input variables increases, the number of control rules increases exponentially, making the design of the fuzzy controller extremely complex. Therefore, the proposed controller prevents the problem of rule explosion using information fusion and then simplifies the control design. Moreover, the particle swarm optimization algorithm is used to select improved controller parameters and make the controller achievable. In this paper, the control performance and anti-interference ability of the traditional PID control, type-1 fuzzy control, interval type-2 fuzzy control, and general type-2 fuzzy control methods are compared. By means of numerical simulation, we can conclude that the GT2FGS-PID controller exhibits superior stability and robustness over other controllers for the PLI robot system.

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Funding

This work is supported by the National Key R&D Program of China (2018YFB1307401) and the National Natural Science Foundation of China (61703291).

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Authors and Affiliations

  1. College of Electrical Engineering, Sichuan University, Chengdu, 610065, China

    Tao Zhao, Yao Chen & Songyi Dian

  2. State Grid Shandong Electric Power Company, Jinan, 250001, China

    Rui Guo

  3. Electric Power Research Institute of State Grid Liaoning Electric Power Co., Ltd., Shenyang, 110006, China

    Shengchuan Li

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  1. Tao Zhao
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  2. Yao Chen
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  3. Songyi Dian
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Correspondence to Songyi Dian.

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Zhao, T., Chen, Y., Dian, S. et al. General Type-2 Fuzzy Gain Scheduling PID Controller with Application to Power-Line Inspection Robots. Int. J. Fuzzy Syst. 22, 181–200 (2020). https://doi.org/10.1007/s40815-019-00780-1

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