Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System

被引:123
|
作者
Ekinci, Serdar [1 ]
Hekimoglu, Baran [2 ]
机构
[1] Batman Univ, Comp Engn Dept, TR-72100 Batman, Turkey
[2] Batman Univ, Elect & Elect Engn Dept, TR-72100 Batman, Turkey
关键词
Automatic voltage regulator; improved kidney-inspired algorithm; PID tuning; robustness analysis; transient response; AUTOMATIC VOLTAGE REGULATOR; SEARCH ALGORITHM; PERFORMANCE ANALYSIS; DERIVATIVE CONTROLLER; OPTIMUM DESIGN; OPTIMIZATION; STABILIZERS;
D O I
10.1109/ACCESS.2019.2906980
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a novel tuning design of proportional integral derivative (PID) controller via an improved kidney-inspired algorithm (IKA) with a new objective function. The main objective of the proposed approach is to optimize the transient response of the AVR system by minimizing the maximum overshoot, settling time, rise time and peak time values of the terminal voltage, and eliminating the steady state error. After obtaining the optimal values of the three gains of the PID controller (K-P, K-I, and K-D) with the proposed approach, the transient response analysis was performed and compared with some of the current heuristic algorithms-based approaches in literature to show the superiority of the optimized PID controller. In order to evaluate the stability of the automatic voltage regulator (AVR) system tuned by IKA method, the pole/zero map analysis and Bode analysis are performed. Finally, the robustness analysis of the proposed approach has been carried out with variations in the parameters of the AVR system. The numerical simulation results demonstrated that the proposed IKA tuned PID controller has better control performances compared to the other existing approaches. The essence of the presented study points out that the proposed approach may successfully be applied for the AVR system.
引用
收藏
页码:39935 / 39947
页数:13
相关论文
共 50 条
  • [31] A particle swarm optimization approach for optimum design of PID controller in AVR system
    Gaing, ZL
    IEEE TRANSACTIONS ON ENERGY CONVERSION, 2004, 19 (02) : 384 - 391
  • [32] Dual Kidney-Inspired Algorithm for Water Quality Prediction and Cancer Detection
    Abdullah, Salwani
    Jaddi, Najmeh Sadat
    IEEE ACCESS, 2020, 8 : 109807 - 109820
  • [33] Application of an improved augmented Lagrangian algorithm to the tuning of robust PID controller for hydraulic turbine governing system
    He, Xuesong
    Liu, Changyu
    Dong, Hongkui
    Yan, Qiurong
    INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2015, 23 (02) : 181 - 191
  • [34] Parameter optimization of PID controller based on an enhanced whale optimization algorithm for AVR system
    Zhang, Jinzhong
    Zhang, Tan
    Zhang, Gang
    Kong, Min
    OPERATIONAL RESEARCH, 2023, 23 (03)
  • [35] Optimal Control of AVR System With Tree Seed Algorithm-Based PID Controller
    Kose, Ercan
    IEEE ACCESS, 2020, 8 : 89457 - 89467
  • [36] Parameter optimization of PID controller based on an enhanced whale optimization algorithm for AVR system
    Jinzhong Zhang
    Tan Zhang
    Gang Zhang
    Min Kong
    Operational Research, 2023, 23
  • [37] Optimal tuning of multi-PID controller using improved CMOCSO algorithm
    Hu, Ying
    Liu, Xiongyan
    Chen, Hao
    PEERJ COMPUTER SCIENCE, 2024, 10
  • [38] Optimal tuning of multi-PID controller using improved CMOCSO algorithm
    Hu, Ying
    Liu, Xiongyan
    Chen, Hao
    PeerJ Computer Science, 2024, 10
  • [39] PID Controller Parameter Tuning Based on Improved Particle Swarm Optimization Algorithm
    Miao, Yanzi
    Liu, Yang
    Chen, Ying
    Jin, Huijie
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS AND MECHATRONICS, 2016, 34 : 104 - 107
  • [40] OPTIMAL PID CONTROLLER DESIGN FOR AVR SYSTEM USING PARTICLE SWARM OPTIMIZATION ALGORITHM
    Rahimian, MohammadSadegh
    Raahemifar, Kaamran
    2011 24TH CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE), 2011, : 337 - 340