Nonlinear Optimal Control Using Sequential Niching Differential Evolution and Parallel Workers

Yves Matanga, Yanxia Sun, Zenghui Wang

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)257-263
Number of pages7
JournalJournal of Advances in Information Technology
Issue number2
Publication statusPublished - 2023


  • differential evolution
  • nonlinear optimal control
  • sequential niching

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence


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