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首页> 外文期刊>E3S Web of Conferences >A Fractional Order Control Strategy for LFC via Big Bang Big Crunch & Grey Wolf Optimization Algorithms
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A Fractional Order Control Strategy for LFC via Big Bang Big Crunch & Grey Wolf Optimization Algorithms

机译:LFC通过大爆裂灰丘和灰狼优化算法的一级秩序控制策略

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The Grey Wolf Optimization (GWO) is well known meta-heuristic algorithm and has been previously used for optimization of various conventional PID and FOPID controllers. This paper deals with the application of Grey Wolf Optimizer (GWO) algorithm and internal model control (IMC) for optimization of fractional order PID (FOPID) controller parameters to the load disturbance of system. This is applicable for one (or) single area non reheated electrical system. The simulation results are compared with the non re-heated Big Bang Big Crunch (BBBC) optimization outputs. In this paper, BBBC optimization has the two bounding cases (lower & upper), they are before and after the perturbation cases. Also it is observed that in case of the BBBC output responses, the settling time value of load frequency is more when compared with the GWO. From the simulation results it is concluded that GWO out performs as compared with BBBC as it produces less error and settling time.
机译:灰狼优化(GWO)是众所周知的元启发式算法,以前用于优化各种传统的PID和FoPID控制器。本文涉及灰狼优化器(GWO)算法和内部模型控制(IMC)的应用,以优化分数阶PID(FOPID)控制器参数到系统的负载扰动。这适用于单个区域非重新加热电气系统。将仿真结果与非再加热的大爆炸大重新发生(BBBC)优化输出进行比较。在本文中,BBBC优化具有两个边界案例(下和上部),它们在扰动病例之前和之后。此外,观察到,在BBBC输出响应的情况下,与GWO相比,负载频率的沉降时间值更加。从仿真结果,结论是,与BBBC相比,GWO OUT表现不佳,因为它产生较少的误差和稳定时间。

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