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A multi-agent based symbiotic organisms search algorithm for tuning fractional order PID controller

机译:一种基于多蛋白酶的共生生物搜索分数PID控制器的搜索算法

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摘要

This work proposes a Multi Agent based Symbiotic Organisms Search (MASOS) by incorporating multi agent system (MAS) into the Symbiotic Organisms Search (SOS) algorithm. Each organism in MASOS acts as an agent participating in local interactions, to search for the optimum solution. In doing so, the conventional operations, namely, mutualism, commensalism and parasitism become localized and thus, decentralized. The decentralization of the SOS algorithm helps in exhaustive exploration of the search space, eliminating the chances of getting trapped into local optima. The algorithm is tested over ten benchmark functions, and the results compared with well known evolutionary and swarm intelligence based algorithms. Further, the proposed algorithm is applied to the tuning of 1-Degree of Freedom (DOF) and 2-DOF Integer Order and Fractional Order Proportional-Integral-Derivative (PID) controllers for magnetic levitation plant. The obtained results validate the accuracy, stability and strong performance of the proposed algorithm over other algorithms. (C) 2020 Elsevier Ltd. All rights reserved.
机译:该工作通过将多种子体系统(MAS)掺入共生生物搜索(SOS)算法来提出基于组织的共生生物搜索(MASO)。 Masos中的每个生物都充当参与当地互动的代理商,以寻找最佳解决方案。在这样做时,传统的行动,即相互主义,共识和寄生派对本地化,因此分散。 SOS算法的分散化有助于彻底探索搜索空间,从而消除了被困到本地最佳最佳的机会。该算法在十个基准函数上进行了测试,结果与众所周知的进化和基于智能的算法相比。此外,所提出的算法应用于用于磁悬浮厂的1度自由度(DOF)和2-DOF整数和分数比例 - 积分 - 积分衍生(PID)控制器的调谐。所获得的结果验证了所提出的算法在其他算法上的准确性,稳定性和强度性能。 (c)2020 elestvier有限公司保留所有权利。

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