Tuning of PID controller of synchronous generators using genetic algorithm

Mohammed, Naeim Farouk; Song, Enzhe; Hayat, Qaisar

doi:10.1109/icma.2014.6885929

Cited by 12 publications

(7 citation statements)

References 2 publications

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“…Among different heuristic algorithms, Genetic Algorithm (GA) [10] and Particle Swarm Optimization (PSO) [11] are widely used for tuning the parameters of PID controller. However, they have high computational burden [12], especially when there is a correlation between optimization parameters [13].…”

Section: Experimental Evaluation Of Optimal Tuning For Pidmentioning

confidence: 99%

Experimental Evaluation of Optimal Tuning for PID Parameters in an AVR System

Foroutan

Tootoonchian

2021

Scientia Iranica

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Automatic Voltage Regulator (AVR) is employed to stabilize the output voltage of the generators in the electric power plants. However, reliable performance of AVR depends on professional tuning of its PID controller's parameters. Therefore, different optimization algorithms are used to determine those parameters. The objective of the optimization is defined as minimizing the characteristics of transient step response such as settling time, rise time, overshoot, and steady state error. Then, to verify the optimization results, a simulator is built experimentally for AVR and PID system that can also be used for other studies on AVR systems. The experimental results are compared with those of MATLAB and Pspice Software. Close agreement between the simulation and experimental results confirms the success of the optimization.

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Section: Experimental Evaluation Of Optimal Tuning For Pidmentioning

confidence: 99%

Experimental Evaluation of Optimal Tuning for PID Parameters in an AVR System

Foroutan

Tootoonchian

2021

Scientia Iranica

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“…Literatürde kullanılan hibrit denetleyici yapılarından genetik algoritma (GA) tabanlı olanlar, oransal, integral ve türev kazanç katsayılarının ayarlandığı genetik algoritma tabanlı hibrit sistemlerdir [2], [13], [14]. Genetik algoritmalar, rastgele arama yöntemlerine kıyasla daha etkili ve verimli bir teknik olarak kabul edilir [15].…”

Section: Gi̇ri̇ş (Introduction)unclassified

Design of Hybrid Controller for Automatic Voltage Regulator

et al. 2023

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Senkron generatörler elektrik enerjisinin üretiminde temel makina olma görevini sürdürmektedir. Senkron generatörlerin çıkış gerilimi ve frekansı uyartım akımı ve devir sayısı değiştirilerek kolayca ayarlanabilmektedir. Genellikle senkron generatörler şebekeye bağlı olarak çalıştıkları için çıkış gerilimi ve frekansının sabit olması gerekmektedir. Gerilimin ayarlanması için kullanılan Otomatik Gerilim Regülatörlerinde çeşitli denetleyici sistemler kullanılmaktadır. Bu çalışmada MATLAB/Simulink programında bulanık mantık tabanlı anahtarlamalı bir hibrit denetleyici yapısı önerilmiştir. Önerilen hibrit denetleyici, Yapay Arı Kolonisi Algoritması kullanılarak optimize edilen PID denetleyiciyle ve Ziegler-Nichols yöntemine dayalı farklı denetleyicilerden elde edilen sonuçlarla karşılaştırılmıştır. Karşılaştırma kriterleri maksimum aşım miktarı, yükselme zamanı ve oturma zamanı olarak belirlenmiştir. Karşılaştırmanın sonuçları da çok kriterli karar verme tekniklerinden biri olan TOPSIS metodu ile analiz edilerek değerlendirilmiş ve sunulmuştur.

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“…For this reason, many intelligent optimization techniques have been employed to determine the optimal parameters of PI/PID controller and hence improve the controller performances. Such intelligent optimization techniques include, Differential Evolution (DE) algorithm [2], [3], fuzzy systems [4][5][6], Ant Colony Optimization [7][8], , Particle Swarm Optimization (PSO) [9][10], Genetic Algorithm (GA) [11][12][13][14].Great attention is to find tuning methods that lead to the optimal operation of the PID controllers. A control system is considered an optimum control system when its parameters are adjusted so that its performance index reaches an extreme value.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Intelligent Control System Tuning Methods for an Evaporator based on Genetic Algorithm

Halim¹,

Othman²,

Sakr³

et al. 2017

IJAIS

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This paper employs Genetic Algorithm to obtain the optimum parameters of an evaporator control system by using different tuning methods. Tuning methods consists of two main groups; first group consists of minimizing the performance indices factors separately such as; Integral of Absolute Error (IAE), Integral of Square Error (ISE), Integral of Time Absolute Error (ITAE) and Integral of Time multiplied with Square Error (ITSE).Second group consists of minimizing the performance indices factors separately plus the step response parameters such as; the rise Time (Tr), Settling Time (Ts), The Maximum Overshoot (Mp) and Steady state Error(Ess). Simulation Results prove that the second group of tuning methods give best performance, robust stability and improve the system robustness.

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Tuning of PID controller of synchronous generators using genetic algorithm

Cited by 12 publications

References 2 publications

Experimental Evaluation of Optimal Tuning for PID Parameters in an AVR System

Experimental Evaluation of Optimal Tuning for PID Parameters in an AVR System

Design of Hybrid Controller for Automatic Voltage Regulator

A Comparative Study of Intelligent Control System Tuning Methods for an Evaporator based on Genetic Algorithm

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