scholarly journals Automatic Voltage Regulator (AVR) Optimization Based on PID Using the Hybrid Grey Wolf Optimization - Genetic Algorithm (HGWGA) Method

2021 ◽  
Vol 10 (6) ◽  
pp. 136-141
Author(s):  
Anas Setiawan ◽  
Panca Mudjirahardjo ◽  
Wijono .
Keyword(s):  
Genetic Algorithm ◽  
Pid Control ◽  
Control Method ◽  
Hybrid Genetic Algorithm ◽  
Voltage Regulator ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Fitness Score ◽  
Automatic Voltage Regulator ◽  
Avr System

In the generator set (genset), the voltage stability system is affected by the excitation system controlled by control circuit called AVR (Automatic Voltage Regulator). One of the important components in the AVR system is the algorithm of the controller. The application of the PID control method has been widely used in the design of AVR controllers. This study applies the GWO-GA (Grey Wolf Optimization - Genetic Algorithm) hybrid method on PID parameters setting. The best transient automatic voltage regulator (AVR) response results were obtained when using the hybrid genetic algorithm - grey wolf optimization (HGAGW) method with a fitness score of 4.3039, the Grey wolf optimization (GWO) method with a fitness score of 4.5059, and the genetic algorithm (GA) method with a fitness score of 6.0214.

Sine-cosine algorithm-based optimization for automatic voltage regulator system

2018 ◽  
Vol 41 (6) ◽  
pp. 1761-1771 ◽  
Author(s):  
Baran Hekimoğlu
Keyword(s):  
Pid Controller ◽  
Design Method ◽  
Voltage Regulator ◽  
Bee Colony ◽  
Automatic Voltage Regulator ◽  
Avr System ◽  
Sine Cosine Algorithm ◽  
Tuning Methods ◽  
Domain Performance ◽  
Novel Design

A novel design method, sine-cosine algorithm (SCA) is presented in this paper to determine optimum proportional-integral-derivative (PID) controller parameters of an automatic voltage regulator (AVR) system. The proposed approach is a simple yet effective algorithm that has balanced exploration and exploitation capabilities to search the solutions space effectively to find the best result. The simplicity of the algorithm provides fast and high-quality tuning of optimum PID controller parameters. The proposed SCA-PID controller is validated by using a time domain performance index. The proposed method was found efficient and robust in improving the transient response of AVR system compared with the PID controllers based on Ziegler-Nichols (ZN), differential evolution (DE), artificial bee colony (ABC) and bio-geography-based optimization (BBO) tuning methods.

Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm

2022 ◽  
pp. 014233122110667
Author(s):  
Tufan Dogruer ◽  
Mehmet Serhat Can
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Pid Controller ◽  
Robustness Analysis ◽  
Optimal Solution ◽  
Voltage Regulator ◽  
Fuzzy Pid ◽  
Multi Objective ◽  
Fuzzy Pid Controller ◽  
Automatic Voltage Regulator

In this paper, a Fuzzy proportional–integral–derivative (Fuzzy PID) controller design is presented to improve the automatic voltage regulator (AVR) transient characteristics and increase the robustness of the AVR. Fuzzy PID controller parameters are determined by a genetic algorithm (GA)-based optimization method using a novel multi-objective function. The multi-objective function, which is important for tuning the controller parameters, obtains the optimal solution using the Integrated Time multiplied Absolute Error (ITAE) criterion and the peak value of the output response. The proposed method is tested on two AVR models with different parameters and compared with studies in the literature. It is observed that the proposed method improves the AVR transient response properties and is also robust to parameter changes.

PID Parameters Tuning Based on Wavelet Neural Network for Automatic Voltage Regulator Control System

2012 ◽  
Vol 463-464 ◽  
pp. 1663-1667
Author(s):  
Hai Na Hu ◽  
Wu Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Power System ◽  
Synchronous Generator ◽  
Wavelet Neural Network ◽  
System Stability ◽  
Voltage Regulator ◽  
System Control ◽  
Automatic Voltage Regulator ◽  
Avr System

Automatic Voltage Regulator (AVR) was applied to hold terminal voltage magnitude of a synchronous generator at a specified level and its stability seriously affects the security of power system. PID control was applied for AVR system control, but the parameters of PID controller were hard to determine, to overcome this problem, some intelligent techniques should be taken. Wavelet Neural Network (WNN) was constrictive and fluctuant of wavelet transform and has self-study, self adjustment and nonlinear mapping functions of neural networks, so the structure of WNN and PID tuning with WNN was proposed, the tuning algorithm was applied into AVR control system, the simulation was taken with normal BP neural network and WNN, the efficiency and advantages of this control strategy was successfully demonstrated which can applied into AVR system for power system stability.

scholarly journals Salp Swarm Optimization Algorithm-Based Fractional Order PID Controller for Dynamic Response and Stability Enhancement of an Automatic Voltage Regulator System

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1472 ◽  
Author(s):  
Ismail Akbar Khan ◽  
Ali S. Alghamdi ◽  
Touqeer Ahmed Jumani ◽  
Arbab Alamgir ◽  
Ahmed Bilal Awan ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Fractional Order ◽  
Optimization Algorithm ◽  
Pid Controller ◽  
Robustness Analysis ◽  
Operating Conditions ◽  
Voltage Regulator ◽  
Swarm Optimization ◽  
Automatic Voltage Regulator ◽  
Avr System

Owing to the superior transient and steady-state performance of the fractional-order proportional-integral-derivative (FOPID) controller over its conventional counterpart, this paper exploited its application in an automatic voltage regulator (AVR) system. Since the FOPID controller contains two more control parameters (µ and λ ) as compared to the conventional PID controller, its tuning process was comparatively more complex. Thus, the intelligence of one of the most recently developed metaheuristic algorithms, called the salp swarm optimization algorithm (SSA), was utilized to select the optimized parameters of the FOPID controller in order to achieve the optimal dynamic response and enhanced stability of the studied AVR system. To validate the effectiveness of the proposed method, its performance was compared with that of the recently used tuning methods for the same system configuration and operating conditions. Furthermore, a stability analysis was carried out using pole-zero and bode stability criteria. Finally, in order to check the robustness of the developed system against the system parameter variations, a robustness analysis of the developed system was undertaken. The results show that the proposed SSA-based FOPID tuning method for the AVR system outperformed its conventional counterparts in terms of dynamic response and stability measures.

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