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基于非洲水牛优化算法的自动电压调节器PID控制器参数整定

Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization.

作者信息

Odili Julius Beneoluchi, Mohmad Kahar Mohd Nizam, Noraziah A

机构信息

Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Kuantan, Malaysia.

IBM Centre of Excellence, Universiti Malaysia Pahang, Kuantan, Malaysia.

出版信息

PLoS One. 2017 Apr 25;12(4):e0175901. doi: 10.1371/journal.pone.0175901. eCollection 2017.

Abstract

In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system's gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics.

摘要

本文尝试应用非洲水牛优化算法(ABO)来调整用于有效自动电压调节器(AVR)的PID控制器参数。现有的元启发式调谐方法已被证明相当成功,但仍存在一些明显需要改进的地方,特别是在系统增益超调量和稳态误差方面。使用ABO算法,其中牛群中每头水牛的位置都是比例积分微分参数的候选解,这对于解决这两个令人关注的领域非常有帮助。与遗传算法PID(GA-PID)、粒子群优化PID(PSO-PID)、蚁群优化PID(ACO-PID)、PID、细菌觅食优化PID(BFO-PID)等的性能相比,使用ABO对PID控制器参数进行调谐的仿真得到的令人鼓舞的结果,使得ABO-PID成为使用元启发式方法解决PID控制器调谐问题的一个很好的补充。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9ee/5404770/c0011a252cfe/pone.0175901.g001.jpg

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