Evolutionary algorithms based tuning of PID controller  for an AVR system

Govindan, Petchinathan

doi:10.11591/ijece.v10i3.pp3047-3056

Cited by 17 publications

(16 citation statements)

References 26 publications

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“…A cuckoo Search based Optimization finding is a new metaheuristic technique and has been presented by Yang and Deb in 2009 [19]. CSO algorithm is executed dependent on powerful offspring freeloading activities of cuckoo variety in blend through Levy Flight performance of certain cuckoo birds [22]. These sorts of cuckoos used to lay their own eggs in other host bird nests via raising the shot at hatching through picking recently brought forth settles and disposing of setting up eggs.…”

Section: Pi Controller Tuning With Cuckoo Search Optimization Techniquementioning

confidence: 99%

Soft Computing Based Tuning of PI Controller With Cuckoo Search Optimization For Level Control of Hopper Tank System

Vinothkumar

Esakkiappan²

2021

Preprint

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The paper work focuses on soft computing and Conventional tuning approach to design of PI controller, which provides a better sustainable performance for a nonlinear hopper tank system which is used in Wastewater treatment applications. The system processes the combination of a conical and cylindrical tank for providing Multi-region based mathematical modelling to obtain the first order with delay time (FOPDT) process transfer function model. The Ziegler Nichols, Cohen-coon, Tyreus Luben, CHR (Chien, Hrones, and Reswick), IMC (Internal Model Control), Direct Synthesis, FOPI( Fractional Order PI) Conventional tuning formulae and Cuckoo Search Optimization (CSO) algorithm are used to optimize the servo regulatory responses of PI controller. The integral and proportional gain of the PI controller is said to produce the fastest settling time and reduces the error using performance indices and achieves Liquid Level control in hopper tank. Comparison is made for the various conventional controller tuning methods with Cuckoo Search Optimization tuning responses and identified to CSO-PI method offers enhanced Optimized Performance while comparing to Conventional tuning methods for a region based system.

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Section: Pi Controller Tuning With Cuckoo Search Optimization Techniquementioning

confidence: 99%

Soft Computing Based Tuning of PI Controller With Cuckoo Search Optimization For Level Control of Hopper Tank System

Vinothkumar

Esakkiappan²

2021

Preprint

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“…Gong [10] suggested an approach to obtain the optimum values of a PID controller using the Jaya algorithm. Govindan [11] verified the effectiveness of an optimization algorithm based on an evolutionary algorithm to design a PID controller. Kose [12] implemented an optimal Tree-Seed algorithm (TSA) to optimize PID controller gain values.…”

Section: Introductionmentioning

confidence: 98%

Control of the Automatic Voltage Regulator System with a Novel Stability-based Artificial Intelligence Method

Tabakh

Tiryaki

2021

ELEKTRON ELEKTROTECH

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This paper proposes a novel Stability-Based Artificial Intelligence Method for predicting the optimum parameters of the proportional-integral-derivative controller in an automatic voltage regulator system. To implement the stability-based artificial intelligence method, first, parameters which are of great importance for the control of the system are applied to the system randomly, data are collected, and then artificial intelligence studies are carried out. The suggested approach has been applied to the system and compared with other control methods in the literature, namely the improved Kidney Inspired algorithm, Jaya algorithm, Tree Seed algorithm, Water Wave Optimization, and Biography-Based Optimization to test the robustness of the new method. The numerical results indicate that the proposed method significantly outperforms all other methods.

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“…In this context, many different methods have been suggested to determine the parameters of PID controller. The most well-known method used in this target is the Ziegler-Nichols approach [9,10]. Nevertheless, this method is complex and time consuming for systems with non-linearities such as synchronous generator [11].…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, this method is complex and time consuming for systems with non-linearities such as synchronous generator [11]. Generally, it delivers a huge overshoot in the response of AVR system and is not suitable to achieve a fast dynamic response [10], [12].…”

Section: Introductionmentioning

confidence: 99%

“…In order to remedy these problems, different optimization methods have been adopted for tuning the optimal parameters of PID controller of an AVR system. Such algorithms included genetic algorithm (GA) [13], particle swarm optimization (PSO) [4], invasive weed optimization (IWO) algorithm [14], Artificial Bee Colony algorithm (ABC) [6], cuckoo search (CS) [10], and others.…”

Section: Introductionmentioning

confidence: 99%

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Output voltage regulation of synchronous generator using PSO algorithm-based PI controller

Habbi¹,

Gabour²,

Boudissa³

et al. 2021

IJPEDS

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In this paper a regulation of the terminal voltage of synchronous generator (SG) has been developed. Here, the nonlinear model of the SG is used directly without requirement for a linearized mathematical model of the generator. A proportional integral PI-controller is used to adjust the duty cycle of the DC chopper of step-down type for controlling the field voltage and consequently the output voltage of the generator. Furthermore, Particle swarm optimization (PSO) algorithm is employed as an optimization technique for tuning the optimal parameters of the PI controller (Kp and Ki). This is achieved by the minimization of the quadratic output error between the reference voltage and the output voltage calculated from the adopted model at the same time. In order to test the performance of the PSO-PI controller, results are compared with the genetic algorithm (GA). Moreover, to reduce the overshoot resulting in the response of the terminal voltage, a varied reference voltage is adopted. Results obtained show the superiority of the varied reference voltage to decrease the overshoot versus the fixed reference voltage.

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Evolutionary algorithms based tuning of PID controller for an AVR system

Cited by 17 publications

References 26 publications

Soft Computing Based Tuning of PI Controller With Cuckoo Search Optimization For Level Control of Hopper Tank System

Soft Computing Based Tuning of PI Controller With Cuckoo Search Optimization For Level Control of Hopper Tank System

Control of the Automatic Voltage Regulator System with a Novel Stability-based Artificial Intelligence Method

Output voltage regulation of synchronous generator using PSO algorithm-based PI controller

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