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

Abstract

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.INDEX TERMS Automatic voltage regulator, improved kidney-inspired algorithm, PID tuning, robustness analysis, transient response. I. INTRODUCTION A. RESEARCH BACKGROUNDAutomatic voltage regulator (AVR) is essential equipment that is used in power system utilities. As its name implies, the main objective of AVR is to control the terminal voltage of synchronous generator by adjusting its exciter voltage. Due to the high inductance of the generator field windings and load variations, stable and fast response of the regulator is difficult to achieve [1]. Therefore, it is important to improve the AVR performance and ensure stable and efficient response to transient changes in terminal voltage. So far, different control techniques have been proposed by researchers to analyze the AVR system with an aim to gain better dynamic response. However, among these controllers the classical proportional plus integral plus derivative (PID) is the most preferable controller because of its simple design structure and robustness to variations of the system parameters [2]. B. LITERATURE SURVEYThe optimal tuning of the gain parameters (K P , K I and K D ) of the PID controller is a very difficult problem.The associate editor coordinating the review of this manuscript and approving it for publication was Fangfei Li.

Enhanced Chaotic Grasshopper Optimization Algorithm Based PID Controller for Automatic Voltage Regulator System

“…The value of gain and time constant of each model of AVR system reviewed in many research papers [9][10][11][12][13][14][15][16][17][18] and the preferred values are given in Table -I. The Eqn.1provides transfer function of AVR system and Eqn.2confer transfer function of the system after placing the value in Eqn.1.…”

“…The best value acquired from AI for controller but however it require more time to train the model and affects speedy response of convergence time in real application. At present, several intelligent optimization algorithms based on evolutionary technique have been recommended to adjust the controller parameters in the AVR system like Artificial Bee Colony Algorithm(ABC) [9], Biogeography-based optimization (BBO) [10], Cuckoo Search Algorithm(CS) [8], Grasshopper Optimization Algorithm (GOA) [11], Bacterial Foraging Optimization Algorithm(BFOA) [12], Improved Kidney-Inspired Algorithm (IKA) [13], Monarch Butterfly Optimization [14], particle swarm optimization [15] [16], sine-cosine algorithm (SCA) [17], Chaotic Differential Evolution Algorithm (CDE) [3],Flower Pollination Algorithm (FPA) [18]and many more such as Ant Lion Optimizer [19], Many Optimizing Liaisons (MOL) [20], Jaya [21] [22] and etc. In 2005, Karaboga reported ABC Algorithm.…”

“…The GOA is gifted to for electrical engineering applications includes renewable microgrid [24], economic load dispatch issue [25], voltageregulator [11]. Hekimoglu et al employed GOA for AVR system and gained better performance than ZN, DE and ABC in terms of transient performance [11].Serdar Ekinci et al [13] incorporated the IKA for AVR system and had a good stability and not pretentious by the fluctuations than ABC BBO, DE, GOA PSO and many more heuristic optimization .Anbarasi et al [12] incorporated theBFOA and confirmed the better responses, stability and robustness of AVR system as relating to ABC, DE algorithms, PSO and MOL.Sambariya [14] et al presented the MBO for the system and improved transient response debated. In 2108, Baran Hekimoglu [17] presented SCA for AVR system and debated that robustness, fast and effective search to give thefinest parameters of controller as compared with ZN, ABC, BBO, DE in transient analysis Vivekanandan et al [3] presented Chaotic DE for AVR system and discussed better performance for AVR system as compared with ZN, TL, DE.The scholar of Cambridge university X.S.Yang proposed the FPA in 2012.…”

Speed Control of DC Motors: Optimal Closed PID-Loop Model Predictive Control

“…Most recent works on PID tuning in the literature such as [31][32][33][34][35] are devoted to employing metaheuristic optimization algorithms as new PID tuning methods. This way, different objective functions and performance constraints such as stability, bandwidth, and robustness are considered for tuning the PID.…”

Dynamic response enhancement of grid‐tied ac microgrid using salp swarm optimization algorithm

“…In old MG control architectures like in previous studies, these gains were selected by using two of the well‐known methods called “trial‐and‐error” and Ziegler‐Nichols (ZN). The former is a very lengthy process and generally unable to yield the optimal results while the latter one involves lengthy mathematical calculations to reach the final results. Furthermore, they do not guarantee the optimal PI parameters and thus generate unwanted lengthy oscillations and overshoots in the system.…”