Order Reduction of Continuous Time Linear Interval Systems Using Whale Optimization Algorithm
- DOI
- 10.2991/978-94-6463-074-9_17How to use a DOI?
- Keywords
- Whale Optimization Algorithm; Reduced Order Interval Model; Integral Square Error; Impulse Response Energy
- Abstract
The Whale Optimization Algorithm (WOA) is a nature-inspired meta-heuristic optimization algorithm that replicates humpback whale social behaviour. The method of bubble-net hunting inspired the algorithm. In this paper, the decreasing Order Interval System was acquired using WOA from a higher order linear continuous time interval model. The lower order system denominator and numerator polynomials are obtained in this suggested technique by applying WOA to minimise the cost function of Integral Squared Error (ISE). The WOA algorithm outperforms both state-of-the-art meta-heuristic algorithms and traditional approaches in terms of optimization results. The WOA method has been determined to be straightforward, easy to use, and to deliver the best answer. A numerical example from the literature is used to demonstrate the feasibility and usefulness of this WOA.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - G. Ramesh AU - M. Siva Kumar AU - B. Dasu AU - R. Srinivasa Rao PY - 2022 DA - 2022/12/05 TI - Order Reduction of Continuous Time Linear Interval Systems Using Whale Optimization Algorithm BT - Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022) PB - Atlantis Press SP - 192 EP - 203 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-074-9_17 DO - 10.2991/978-94-6463-074-9_17 ID - Ramesh2022 ER -