Hybrid robust controller based on interval type 2 fuzzy neural network and higher order sliding mode for robotic manipulators

Authors

  • S. Mohammadrezaei Nodeh Department of Mechanical Engineering, Babol Noshirvani University of Technology, Mazandaran, Iran
  • M. H. Ghasemi Department of Mechanical Engineering, Babol Noshirvani University of Technology, Mazandaran, Iran
  • H.R. Mohammadi Daniali Department of Mechanical Engineering, Babol Noshirvani University of Technology, Mazandaran, Iran

DOI:

https://doi.org/10.5377/nexo.v32i02.9262

Keywords:

Type-2 Fuzzy Logic Neural Network, Higher-order Sliding Mode Control, Robotic Arm

Abstract

Industrial arms should be able to perform their duties in environments where unpredictable conditions and perturbations are present. In this paper, controlling a robotic manipulator is intended under significant external perturbations and parametric uncertainties. Type-2 fuzzy logic is an appropriate choice in the face of uncertain environments, for various reasons, including utilizing fuzzy membership functions. Also, using the neural network (NN) can increase robustness of the controller. Although neural network does not basically need to build its type-2 fuzzy rules, the initial rules based on sliding surface of higher order sliding mode controller (HOSMC) can improve the system's performance. In addition, self-regulation feature of the controller, which is based on the existence of the neural network in the central type-2 fuzzy controller block, increases the robustness of the method even more. Effective performance of the proposed controller (IT2FNN-HOSMC) is shown under various perturbations in numerical simulations.

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Published

2019-12-31

How to Cite

Mohammadrezaei Nodeh, S., Ghasemi, M. H., & Mohammadi Daniali, H. (2019). Hybrid robust controller based on interval type 2 fuzzy neural network and higher order sliding mode for robotic manipulators. Nexo Scientific Journal, 32(02), 106–125. https://doi.org/10.5377/nexo.v32i02.9262

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Section

Articles