Robustness Study of Fractional Order PID Controller Optimized by Particle Swarm Optimization in AVR System

Raju, N. Ramesh; Reddy, P. Linga

doi:10.11591/ijece.v6i5.pp2033-2040

Cited by 3 publications

(5 citation statements)

References 12 publications

(13 reference statements)

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“…The algorithm is very effective, easy and understandable to apply on the search of optimization process in large solution space. These specialties of it have made possible to apply in the various engineering area and especially control engineering [19], [21], [35].…”

Section: Pso Methods Is a Population Based Stochastic Optimization Tecmentioning

confidence: 99%

“…Automatic voltage regulators (AVR) are practically used to maintain terminal voltage at the nominal level for synchronous alternator [21], [34], [35]. For this reason, it is important to keep voltage level at the desired value for power plants.…”

Section: Automatic Voltage Regulator (Avr) Systemmentioning

confidence: 99%

“…Luo have put forward new design techniques which are systematic ways for FOPID controllers [14]- [16]. In addition to this, heuristic optimization techniques have also been considered for obtaining fractional controller coefficients [17]- [21]. Additionally, Gaing have used PSO technique to obtain optimal solution for AVR control system [17].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Design of a Variable Coefficient Fractional Order PID Controller by using Heuristic Optimization Algorithms

Aydoğdu¹,

Korkmaz²

2019

ijacsa

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This paper deals with an optimal design of a new type Variable coefficient Fractional Order PID (V-FOPID) controller by using heuristic optimization algorithms. Although many studies have mainly paid attention to correct the performance of the system's transient and steady state responses together, few studies are interested in both transient and steady state performances separately. It is obvious that handling these two cases independently will bring out a better control response. However, there are no studies using different controller parameters for the transient and steady state responses of the system in fractional order control systems. The major contribution of the paper is to fill this gap by presenting a novel approach. To justify the claimed efficiency of the proposed V-FOPID controller, variable coefficient controllers and classical ones are tested through a set of simulations which is about controlling of an Automatic Voltage Regulator (AVR) system. According to the obtained results, first of all it was observed that proposed V-FOPID controller has superiority to the classical PID, Variable coefficient PID (V-PID) and classical Fractional Order PID (FOPID) controllers. Secondly, Particle Swarm Optimization (PSO) algorithm has shown its advantage compared to the Artificial Immune System (AIS) algorithm for the controller design.

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Section: Pso Methods Is a Population Based Stochastic Optimization Tecmentioning

confidence: 99%

Section: Automatic Voltage Regulator (Avr) Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Design of a Variable Coefficient Fractional Order PID Controller by using Heuristic Optimization Algorithms

Aydoğdu¹,

Korkmaz²

2019

ijacsa

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“…The development of fractional calculus in the control field lead to design of non-integer PID controller [5][6][7][8][9] and non-integer models [10,11]. Tuning of fractional controllers for FOPDT systems using analytical methods [12], non-linear systems [13], time delay systems [14,15], optimization techniques [16][17][18] are reported in literatures. The Flexibility of FOPID controller is increased by the additional parameters such as fractional order derivative and integrator, but it also increases the complexity of the controller tuning.…”

Section: Introductionmentioning

confidence: 99%

Internal model controller based PID with fractional filter design for a nonlinear process

Hemavathy¹,

Y²,

Lakshmanaprabu³

2020

IJECE

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In this paper, an Internal model Controller (IMC) based PID with fractional filter for a first order plus time delay process is proposed. The structure of the controller has two parts, one is integer PID controller part cascaded with fractional filter. The proposed controller has two tuning factors λ, filter time constant and a, fractional order of the filter. In this work, the two factors are decided in order to obtain low Integral Time Absolute Error (ITAE). The effectiveness of the proposed controller is studied by considering a non linear (hopper tank) process. The experimental set up is fabricated in the laboratory and then data driven model is developed from the experimental data. The non linear process model is linearised using piecewise linearization and two linear regions are obtained. At each operating point, linear first order plus dead time model is obtained and the controller is designed for the same. To show the practical applicability, the proposed controller is implemented for the proposed experimental laboratory prototype.

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“…The oscillation of LFC and AVR are studied with PID controller in [6,7] to improve the performance of two control loops. To more efficient results the artificial intelligence techniques was used for tuning the gains of PID controller for LFC with AVR loops, the applications of artificial intelligence technique based on optimization of PID controller for LFC are presented in [8][9][10][11][12], whereas the optimal design of PID controller by using artificial intelligence technique for AVR system are presented in [13][14][15][16][17]. The LFC and AVR control loops with tuning PID parameters by optimization technique are studied individually in [18,19], while the interaction effect among the LFC with AVR control loops with optimized the PID controller gains are presented in [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Application of artificial intelligence techniques for LFC and AVR systems using PID controller

Salman

Jafar

Ismael

2019

IJPEDS

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Development of electrical power systems led to search for a new mathematical methods to find the values of PID (Proportional-Integral-Derivative) controller. The goal of the paper is to improve the performance of the overall system, through improved the frequency deviation and the voltage deviation characteristics using PID controller, so in this paper are proposed three methods of artificial intelligence techniques for designing the optimal values of PID controller of Load-Frequency-Control (LFC) and Automatic-Voltage-Regulator (AVR), the first is the Firefly Algorithm (FA), the second is the Genetic Algorithm (GA) and the third is the Particle Swarm Optimization (PSO), in addition to these three methods use the conventional (Ziegler–Nichols, Z-N). The FA, GA and PSO are used to obtain the optimal parameters of PID controller based on minimized different various indices as a fitness function, these fitness functions namely Integral-Time-Absolute-Error (ITAE) and Integral-Time-Square-Error (ITSE). Comparison between the results obtained show that FA has better performance to control of frequency deviation and terminal voltage than GA and PSO, so the results observed the FA is more effectual and reliable to determine the optimal values of PID controller.

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Robustness Study of Fractional Order PID Controller Optimized by Particle Swarm Optimization in AVR System

Cited by 3 publications

References 12 publications

Optimal Design of a Variable Coefficient Fractional Order PID Controller by using Heuristic Optimization Algorithms

Optimal Design of a Variable Coefficient Fractional Order PID Controller by using Heuristic Optimization Algorithms

Internal model controller based PID with fractional filter design for a nonlinear process

Application of artificial intelligence techniques for LFC and AVR systems using PID controller

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