Comparative Performance Analysis of AVR Controllers Using Modern Optimization Techniques

Mosaad, Ahmed; Attia, Mahmoud A.; Abdelaziz, Almoataz Y.

doi:10.1080/15325008.2018.1532471

Cited by 59 publications

(56 citation statements)

References 19 publications

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“…Since fluctuations in the terminal voltage adversely affect the system, the terminal voltage must be kept constant at a specific level. The PID controllers are usually used for this [18][19][20][21][22][23][24][25][26][27][28][29][30][31]. But when the PI controller is selected, one less zero is added to the system than the PID controller.…”

Section: Modelling Avr Systems With a Pi Controllermentioning

confidence: 99%

“…The first PSO based heuristic method proposing to determine the AV R system controller gains was introduced by Gaing [12]. After this study, many heuristic methods have been used in this subject [15,[18][19][20][21][22][23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

“…The main purpose of all control systems is to keep the system stable, to provide the desired transient state performance, and to remove the steady state error or to keep in a limited band. In these AV R system studies, the performances of controller gains were verified by different methods such as root locus, bode plots, closed-loop poles, damping ratio [12,[18][19][20][21][22]. Among these studies it has been seen that one of the researchers used only closed-loop values [25], some researchers used only bode values [23,24], some only considered transient state performances, and some did not carry out any verification studies for the performance [26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel optimum PI controller design based on stability boundary locus supported particle swarm optimization in AVR system

Özdemir¹

2021

Turk J Elec Eng & Comp Sci

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This study proposes a new approach that combines stability and optimization in the design of PI controller of automatic voltage regulators (AV R) of synchronous generators with variable system parameters. Thanks to this approach, a PI controller, providing the desired performance and the stability of the AV R system, has been designed. The approach follows a method investigating for the PI gain values to achieve the desired goals. In the first step of the study, a new stability boundary locus is calculated for the case in which AV R system's parameters have changed. The Stability Boundary Locus (SBL) Method is a graphic-based technique, and is used for the calculation of a new stability boundary locus curve. In this technique, the stable region is obtained by using the roots of the characteristic equation of the AV R system, so depends on the parameters of the AV R system. In the second step, the controller gains are searched by the particle swarm optimization (PSO) algorithm modified with respect to the proposed approach. In the last step, in order to validate the efficiency of the proposed approach, the system has been optimized by the classical PSO and proposed SBL PSO. The comparative results of both optimizations have been presented. The results show that the proposed approach shortens optimization time by 20%. Thanks to this approach, the AV R system always runs at the desired performance and is always stable. It also substantially contributes to the implementation of optimization of closed loop control systems.

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Section: Modelling Avr Systems With a Pi Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A novel optimum PI controller design based on stability boundary locus supported particle swarm optimization in AVR system

Özdemir¹

2021

Turk J Elec Eng & Comp Sci

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“…In the previous table, KA, KE, KG, and KS stand for gains of an amplifier, exciter, generator, and sensor, respectively, while TA, TE, TG, and TS are time constants of the amplifier, exciter, generator, and sensor. Values that are considered in this paper are KA = 10, KE = 1, KG = 1, KS = 1, TA = 0.1, TE = 0.4, TG = 1, and TS = 0.01 [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. It is important to mention that the gain of the generator KG depends on the load of the generator.…”

Section: Component Transfer Functionmentioning

confidence: 99%

“…Also, it can be found that the authors used Chaotic Ant Swarm (CAS) [7], Multi-Objective Extremal Optimization (MOEO) [9], Cuckoo Search (CS) [10], and Salp Swarm Optimization (SSO) algorithm [12] to determine unknown parameters of the FOPID. Besides the FOPID, many existing studies deal with the optimization of the parameters of the classical PID controller for the AVR systems [13][14][15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Fractional Order PID Controller Design for an AVR System Using Chaotic Yellow Saddle Goatfish Algorithm

2020

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This paper presents a novel method for optimal tunning of a Fractional Order Proportional-Integral-Derivative (FOPID) controller for an Automatic Voltage Regulator (AVR) system. The presented method is based on the Yellow Saddle Goatfish Algorithm (YSGA), which is improved with Chaotic Logistic Maps. Additionally, a novel objective function for the optimization of the FOPID parameters is proposed. The performance of the obtained FOPID controller is verified by comparison with various FOPID controllers tuned by other metaheuristic algorithms. A comparative analysis is performed in terms of step response, frequency response, root locus, robustness test, and disturbance rejection ability. Results of the simulations undoubtedly show that the FOPID controller tuned with the proposed Chaotic Yellow Saddle Goatfish Algorithm (C-YSGA) outperforms FOPID controllers tuned by other algorithms, in all of the previously mentioned performance tests.

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Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

Paliwal

Srivastava

Pandit

2021

Int Trans Electr Energ Syst

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Summary This paper presents a novel fractional‐order PID plus derivative with filter coefficient (FOPID‐DN) controller for automatic voltage regulator (AVR) system using the MATLAB/Simulink environment. An AVR system is employed in the power system to maintain the terminal voltage at the desired level. Parameters of the proposed FOPID‐DN controller are optimally tuned by the recently developed Equilibrium Optimizer (EO) algorithm. Performance of the designed FOPID‐DN controller for an AVR system is compared with various controllers which are optimally tuned by different optimization algorithms. Comparative transient response analysis of the proposed technique has been carried out by considering vital transient response indicators like maximum overshoot, rise time, and settling time. Performance analysis of the proposed technique for an AVR system has been done by considering several input conditions. Robustness analysis of the EO algorithm tuned FOPID‐DN controller has been performed by varying the time constants of different components in an AVR system. The capability of the FOPID‐DN controller to handle nonlinearities of an AVR system has been investigated. The stability of the FOPID‐DN controlled AVR system has been analyzed. In addition, the disturbance rejection capability of the FOPID‐DN controlled AVR system has also been investigated. From the various simulation results obtained using the MATLAB/Simulink environment, it has been observed that the proposed FOPID‐DN‐based AVR system provided better performance as compared to different existing controllers.

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Comparative Performance Analysis of AVR Controllers Using Modern Optimization Techniques

Cited by 59 publications

References 19 publications

A novel optimum PI controller design based on stability boundary locus supported particle swarm optimization in AVR system

A novel optimum PI controller design based on stability boundary locus supported particle swarm optimization in AVR system

Fractional Order PID Controller Design for an AVR System Using Chaotic Yellow Saddle Goatfish Algorithm

Equilibrium optimizer tuned novel FOPID‐DN controller for automatic voltage regulator system

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