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Recent trends in bio-inspired meta-heuristic optimization techniques in control applications for electrical systems: a review


This article represents a brief study on popular bio-inspired meta-heuristic optimization methods and their applications. These methods, which imitate biological phenomena or natural occurrences, have the potential to solve real-world problems. This article looked at several popular optimization methods and briefly discussed them. Although these methods have been used in a variety of domains of science and engineering, this article has focused on control engineering and electrical power systems in particular. This article aimed to provide a clearer picture of the recent trends and practices in the use of optimization in various control studies and research studies related to electrical system optimization.

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Fig. 1



Ant colony optimization


Artificial bee colony


Automatic voltage regulator


Cuckoo search


Dragonfly algorithm


Genetic algorithm


Grey wolf optimization


Grasshopper optimization algorithm


Integral linear quadratic Gaussian


Integral of time multiplied absolute error


Integral of time weighted squared error


Linear quadratic regulator


Linear quadratic Gaussian


Least average error


Mayfly algorithm


Model predictive control


Maximum power point tracking




Particle swarm optimization


Proportional integral derivative




Salp swarm algorithm


Whale optimization


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1. Md. Hassanul Karim Roni: Research, writing, drafting. 2. M. S. Rana: Supervision, Proof Reading, drafting. 3. H. R. Pota: Supervision, Proof Reading. 4. Md. Mahmudul Hasan: Research. 5. Md. Shajid Hussain: Research.

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Roni, M.H.K., Rana, M.S., Pota, H.R. et al. Recent trends in bio-inspired meta-heuristic optimization techniques in control applications for electrical systems: a review. Int. J. Dynam. Control 10, 999–1011 (2022).

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