2023
doi: 10.12720/jait.14.2.257-263
Nonlinear Optimal Control Using Sequential Niching Differential Evolution and Parallel Workers
Yves Matanga1,*
, ,
- 1Department of Electrical and Electronic Engineering, Science University of Johannesburg, Johannesburg, South Africa
- 2Department of Electrical Engineering, University of South Africa, Pretoria, South Africa
- Manuscript receivedJuly 27, 2022
- revisedAugust 26, 2022
- acceptedOctober 31, 2022
- publishedMarch 21, 2023
Abstract
Optimal control is a high-quality and challenging control approach that requires very explorative metaheuristic optimisation techniques to find the most efficient control profile for the performance index function, especially in the case of highly nonlinear dynamic processes. Considering the success of differential evolution in nonlinear optimal control problems, the current research proposes the use of sequential niching differential evolution to boost further the solution accuracy of the solver owing to its globally convergent feature. Also, because sequential niching bans previously discovered solutions, it can propose several competing optimal control profiles relevant for control practitioners. Simulation experiments of the proposed algorithm have been first conducted on IEEE CEC2017/2019 datasets and n-dimensional classical test sets, yielding improved solution accuracy and robust performances on optimal control case studies.
Keywords
- sequential niching
- differential evolution
- nonlinear optimal control
How to Cite
Yves Matanga, Yanxia Sun, and Zenghui Wang, "Nonlinear Optimal Control Using Sequential Niching Differential Evolution and Parallel Workers," Journal of Advances in Information Technology, vol. 14, no. 2, pp. 257-263, 2023. https://doi.org/10.12720/jait.14.2.257-263
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
