A new robust fuzzy-PID controller design using gravitational search algorithm

N. Kouba, M. Menaa, M. Hasni, M. Boudour
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Abstract

This paper proposes the design of a novel robust load frequency control (LFC) strategy-based optimised fuzzy-PID controller employing gravitational search algorithm (GSA). The suggested GSA algorithm was applied to optimise the input scaling factors of the fuzzy logic and the PID controller gains. To show the potential of the proposed control methodology, a multi-sources two-area interconnected power system was investigated for the simulation. The considered test system comprises various power generating units from hydro, thermal and nuclear sources in area-1, and power generation from hydro, nuclear and diesel sources in area-2. Initially, the simulation was carried considering a centralised controller for both areas to cope with load changes, and then was extended with decentralised controller. Further, sensitivity analysis was performed to demonstrate the ability of the proposed approach in face of wide changes in system parameters and position of load changes. The frequency deviations and the tie-line power flow change were presented, and the superiority of the proposed control strategy was demonstrated by comparing the results with individual gravitational search algorithm (GSA), fuzzy logic controller (FLC) and with some reported techniques in the literature such as Ziegler-Nichols, genetics algorithm (GA), bacterial foraging optimisation algorithm (BFOA) and particle swarm optimisation (PSO).
采用引力搜索算法设计了一种新的鲁棒模糊pid控制器
提出了一种基于引力搜索算法(GSA)的鲁棒负载频率控制(LFC)策略的优化模糊pid控制器。提出的GSA算法用于优化模糊逻辑的输入比例因子和PID控制器增益。为了证明所提出的控制方法的潜力,对一个多源两区互联电力系统进行了仿真研究。所考虑的测试系统包括1区的水力、热能和核能发电机组,以及2区的水力、核能和柴油发电机组。最初,仿真考虑了两个区域的集中控制器来应对负载变化,然后扩展了分散控制器。此外,进行了灵敏度分析,以证明所提出的方法在面对系统参数和负载变化位置的大变化时的能力。通过与个体引力搜索算法(GSA)、模糊逻辑控制器(FLC)以及文献报道的Ziegler-Nichols算法、遗传算法(GA)、细菌觅食优化算法(BFOA)和粒子群优化算法(PSO)进行比较,验证了所提控制策略的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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