Multiloop FOPID Controller Design for TITO Process Using Evolutionary Algorithm

Pub Date : 2019-07-01 DOI:10.4018/IJEOE.2019070107
S. Lakshmanaprabu, D. N. Jamal, U. Banu
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引用次数: 2

Abstract

In this article, the tuning of multiloop Fractional Order PID (FOPID) controller is designed for Two Input Two Output (TITO) processes using an evolutionary algorithm such as the Genetic algorithm (GA), the Cuckoo Search algorithm (CS) and the Bat Algorithm (BA). The control parameters of FOPID are obtained using GA, CS, and BA for minimizing the integral error criteria. The main objective of this article is to compare the performance of the GA, CS, and BA for the multiloop FOPID controller problem. The integer order internal model control based PID (IMC-PID) controller is designed using the GA and the performance of the IMC-PID controller is compared with the FOPID controller scheme. The simulation results confirm that BA offers optimal controller parameter with a minimum value of IAE, ISE, ITAE with faster settling time.
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基于进化算法的TITO过程多回路FOPID控制器设计
本文采用遗传算法(GA)、布谷鸟搜索算法(CS)和蝙蝠算法(BA)等进化算法,针对双输入双输出(TITO)过程设计了多环分数阶PID (FOPID)控制器的整定。利用遗传算法(GA)、遗传算法(CS)和遗传算法(BA)得到FOPID的控制参数,以最小化积分误差准则。本文的主要目的是比较GA、CS和BA在多环路FOPID控制器问题上的性能。利用遗传算法设计了基于整阶内模控制的PID (IMC-PID)控制器,并将其性能与FOPID控制器方案进行了比较。仿真结果表明,BA提供了最优的控制器参数,使IAE、ISE、ITAE值最小,且沉降时间更快。
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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