- Title
- Fuzzy logic and gradient descent-based optimal adaptive robust controller with inverted pendulum verification
- Creator
- Hadipour Lakmesari, S.; Mahmoodabadi, M.; Ibrahim, Yousef
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/179777
- Identifier
- vital:15652
- Identifier
-
https://doi.org/10.1016/j.chaos.2021.111257
- Identifier
- ISBN:0960-0779 (ISSN)
- Abstract
- This paper develops an adaptive robust combination of feedback linearization (FL) and sliding mode controller (SMC) based on fuzzy rules and gradient descent laws. The new suggested control algorithm is tested to stabilize a fourth-order under-actuated nonlinear inverted pendulum system. More precisely, the reliable feedback linearization approach and the robust SMC controller are combined to design a stable control effort. In order to enhance the performance of the suggested controller, an adaptation technique as long as fuzzy rules are applied to update the control gains and the boundary layer parameter. Then, a novel evolutionary algorithm termed multi-objective ant lion optimizer (MOALO) is implemented to determine the control coefficients. The analysis and results conducted on the inverted pendulum system demonstrate the desired performance of the proposed control scheme by providing an optimal smooth control input, suitable tracking performance, and proper time responses. © 2021 Elsevier Ltd
- Publisher
- Elsevier Ltd
- Relation
- Chaos, Solitons and Fractals Vol. 151, no. (2021), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Coyright © 2021 Elsevier Ltd
- Subject
- 01 Mathematical Sciences; 08 Information and Computing Sciences; 09 Engineering; Feedback linearization; Fuzzy rules; Gradient descent; Inverted pendulum system; Multi-objective ant lion optimizer; Sliding mode control
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