Design and Implementation of Intelligent Hybrid Neuro Controller for Automatic Voltage Regulator

2020 ◽  
Vol 17 (5) ◽  
pp. 2197-2202
Author(s):  
Golla Suri Babu ◽  
Tirumalasetty Chiranjeevi
Keyword(s):  
Feedforward Neural Network ◽  
Voltage Regulator ◽  
Backpropagation Algorithm ◽  
Design And Implementation ◽  
Hybrid Controller ◽  
System A ◽  
Automatic Voltage Regulator ◽  
Avr System ◽  
Multilayer Feedforward Neural Network ◽  
Neuro Controller

In this paper, we presented a hybrid controller by combining the advantages of both PID and Neuro controllers for automatic voltage regulator (AVR) system. A Neuro controller is designed using multilayer feedforward neural network and Levenberg-Marquardt backpropagation algorithm is used for training the network. Also, hybrid controller is achieved by blending the characteristics of classical PID and proposed Neuro controller using a switching mechanism based on the error. The proposed PID, Neuro and Hybrid controllers are simulated in MATLAB environment and their transient response parameters are compared. The simulation results clearly indicated the improvement in the transient output of the automatic voltage regulator system with proposed hybrid controller even in the presence of uncertainties in the system.

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.

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.

scholarly journals Focused Time Delay Neural Network For Tuning Automatic Voltage Regulator

2019 ◽  
Vol 7 (1) ◽  
pp. 34-43 ◽  
Author(s):  
Widi Aribowo
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Dynamic Networks ◽  
Voltage Regulator ◽  
Robust Performance ◽  
Matlab Simulink ◽  
Automatic Voltage Regulator ◽  
Avr System ◽  
Load Angle

This paper proposes a novel controller for automatic voltage regulator (AVR) system. The controller is used Focused Time Delay Neural Network (FTDNN). It does not require dynamic backpropagation to compute the network gradient. FTDNN AVR can train network faster than other dynamic networks. Simulation was performed to compare load angle (load angle) and Speed. The performance of the system with FTDNN-AVR has compared with a Conventional AVR (C-AVR) and RNN AVR. Simulations in Matlab/Simulink show the effectiveness of FTDNN-AVR design, and superior robust performance with different cases.

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.

Design of PID controller for automatic voltage regulator system using Ant Lion Optimizer

2018 ◽  
Vol 15 (3) ◽  
pp. 373-387 ◽  
Author(s):  
Rosy Pradhan ◽  
Santosh Kumar Majhi ◽  
Bibhuti Bhusan Pati
Keyword(s):  
Pid Controller ◽  
Parametric Uncertainty ◽  
Frequency Domain Analysis ◽  
Voltage Regulator ◽  
Content Type ◽  
Ant Lion Optimizer ◽  
Automatic Voltage Regulator ◽  
Avr System ◽  
Nature Inspired Algorithm ◽  
Ant Lion

Purpose Now days, various techniques are used for controlling the plants. New ideas are evolving day by day to get better-quality control for various industrial processes to produce high-quality products. Currently, the focus of this research is being emphasized on application of nature-inspired algorithms in control systems. The purpose of this paper is to apply a nature-inspired algorithm called Ant Lion Optimizer (ALO) for the design of proportional-integrator-derivative (PID) controller for an automatic voltage regulator (AVR) system. Design/methodology/approach For the design of the PID controller, the ALO algorithm is considered as a designing tool for obtaining the optimal values of the controller parameter. All the simulations are carried out in Simulink/MATLAB environment. A comparative study is carried out with some modern nature-inspired algorithm to describe the advantages of this tuning method. Findings The proposed method has superiority value in transient and frequency domain analysis than the other published heuristic optimization algorithms. The presented approach has almost no variation in transient response when varying time constants of the system parameter, such as exciter, generator, amplifier and sensor from −50 per cent to +50 per cent. In addition, the close loop system is robust against any disturbances such as input–output disturbances and parametric uncertainty, as the sensitivity values are nearly equal to one. Originality/value The proposed method presents the design and performance analysis of proportional integral derivate (PID) controller for an AVR system using the recently proposed ALO.

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