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Adaptive Control of a Two-Link Flexible Manipulator Using a Type-2 Neural Fuzzy System

  • Research Article-Electrical Engineering
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Abstract

This paper presents a simple novel intelligent control scheme. The devised control scheme is a Takagi Sugeno Kang (TSK)- based type-2 neural fuzzy system (NFS) with a self-tuning mechanism optimized via a conjugate gradient (CG) method. Defuzzification phase of the NFS comprises T-norms rather than the conventional product–sum combination. The proposed control scheme is incorporated with a two-link flexible manipulator (TLFM), which belongs to the class of multi-body discrete/distributed, nonlinear, infinite-dimensional and highly coupled systems. The finite-dimensional model is acquired by using an assumed mode method (AMM). The truncated model has uncertainties, which makes it a difficult control problem. The control objective is to accomplish angular maneuvering of the TLFM links while regulating their intrinsic fluctuations. For an extensive analysis, the proposed control scheme is compared with a TSK model-based type-1 NFS and an adaptive proportional integral derivative (APID) control scheme. The simulation results demonstrate that the proposed control scheme exhibits better position tracking and vibration regulation capabilities compared to the other intelligent control schemes.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Faculty of Engineering, Gaziantep University, Gaziantep, Turkey

    Muhammad Umair Khan & Tolgay Kara

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  1. Muhammad Umair Khan
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  2. Tolgay Kara
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Correspondence to Muhammad Umair Khan.

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Khan, M.U., Kara, T. Adaptive Control of a Two-Link Flexible Manipulator Using a Type-2 Neural Fuzzy System. Arab J Sci Eng 45, 1949–1960 (2020). https://doi.org/10.1007/s13369-020-04341-9

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