Hybrid robust controller based on interval type 2 fuzzy neural network and higher order sliding mode for robotic manipulators
DOI:
https://doi.org/10.5377/nexo.v32i02.9262Keywords:
Type-2 Fuzzy Logic Neural Network, Higher-order Sliding Mode Control, Robotic ArmAbstract
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.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 Array
This work is licensed under a Creative Commons Attribution 4.0 International License.
The authors who publish in Nexo Scientific Journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of the first publication under the license Creative Commons Attribution License https://creativecommons.org/licenses/by/3.0/, which allows others to share the work with a recognition of the authorship of the work and the initial publication in Nexo Scientific Journal.
- Authors may separately establish additional agreements for the non-exclusive distribution of the version of the work published in the journal (for example, in an institutional repository or a book), with the recognition of the initial publication in Nexo Scientific Journal.
- Authors are allowed and encouraged to disseminate their works electronically (for example, in institutional repositories or in their own website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published works.