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Article type: Research Article
Authors: Eslami, Mohammada | Shayesteh, Mohammad Rezaa; * | Pourahmadi, Majida | Ayatollahitafti, Vahidb
Affiliations: [a] Department of Electrical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran | [b] Department of Computer Engineering, Taft Branch, Islamic Azad University, Taft, Iran
Correspondence: [*] Corresponding author. Mohammad Reza Shayesteh, Department of Electrical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran. Tel.: +983531872758; E-mail: [email protected].
Abstract: Generally, increase in energy demand and consequently unwanted events in a current system will lead to instability. To increase the power system reliability, the current system can be expanded, resulting in a high financial burden. Therefore, one of the most effective options is appropriate controllers usage for stability. In order to overcome the defects of classical controllers such as non-linear, complex uncertain systems, an appropriate mathematical model needs to be designed in limited working conditions. In this paper, a new fractional-order fuzzy proportional-integral-deferential (FOPID) controller is proposed. The proposed controller in its structure is an integral, derivative gain with a fractional order. This controller is structurally adjustable with two fractional orders, performing the stability process in a short time. On the other hand, in the proposed controller, the optimal adjustment of the controller gain and membership functions has turned into an optimization problem, which is done by a hybrid algorithm based on the virus colony search (VCS) and artificial bee colony (ABC). Local and final search powers in the proposed hybrid algorithm reduce the possibility of local presence dramatically. Simulation results have shown that the proposed controller achieves the higher robustness, the lower fall time, and the lower frequency oscillations compared to the existing controllers.
Keywords: Fractional-order fuzzy controller, intelligent hybrid algorithm, virus serach colony, bee colony, optimization, low frequency oscillation
DOI: 10.3233/JIFS-182918
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7865-7882, 2019
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