Title
A New Type-II Fuzzy System for Flexible-Joint Robot Arm Control
Document Type
Conference Proceeding
Publication Date
10-1-2019
Publication Title
Proceedings - 2019 6th International Conference on Control, Instrumentation and Automation, ICCIA 2019
Keywords
Adaptive Neuro-Fuzzy Inference System (ANFIS), Flexible-Joint Robot Arm, Gaussian Type-I Fuzzy Sets, Interval Gaussian Type-II Fuzzy Sets
Abstract
© 2019 IEEE. In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) based on the Interval Gaussian Type-II Fuzzy sets in the antecedent part and Gaussian Type-I Fuzzy sets as coefficients of a linear combination of the input variables in the consequent part is presented. The capability of the proposed control method to function approximation and dynamical system identification is investigated. An adaptive learning rate based on the Backpropagation method with guaranteed convergence is employed for parameter learning. Finally, the proposed method is applied to control a flexible-joint robot arm. The simulation results show the robustness and effectiveness of the proposed control method. The proposed control method is also compared with the conventional ANFIS method.
DOI
10.1109/ICCIA49288.2019.9030872
Recommended Citation
Tavoosi, Jafar and Mohammadi, Fazel. (2019). A New Type-II Fuzzy System for Flexible-Joint Robot Arm Control. Proceedings - 2019 6th International Conference on Control, Instrumentation and Automation, ICCIA 2019.
https://scholar.uwindsor.ca/electricalengpub/24