Tuning of PID controller for diesel engines using genetic algorithm

Mohammed, Naeim Farouk; Song, Enzhe

doi:10.1109/icma.2013.6618140

Cited by 7 publications

(10 citation statements)

References 6 publications

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“…Fast Genetic Algorithms (FGA) are stochastic international algorithm depends on the normal evolution to produce good solutions and solve the problems. GA generate initial populace of keys applying the standard of being of the fittest to yield improved keys [10]. FGA technique is used to overcome the problem in classical genetic algorithm by decreases time [11].…”

Section: Proposed Controllermentioning

confidence: 99%

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Response Enhancement of Dc Motor Using Evolutionary Intelligent Fractional-Order Pid Controller

2018

QJES

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An effective intelligent controller is suggested by mixing the Fractional-Order PID (FOPID) and fast genetic algorithms (FGAs) to improve the output response of DC motor. This controller is named as FGA-FOPID controller, the classical FOPID controllers have numerous benefits in practical implementation of many systems such as DC motor control compared with classical PID controllers, where the output response of the DC motor with FOPID or with classical PID is reasonable, but it's not satisfaysthe response enhancements. So FGAs is used to slove the problem and to improve the overall output.The suggested work is confirmed by DC motor control system, and then compared with the classical PID and FOPID controllers. The simulated results establish that, the suggested work is adeptness from previous work.

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Section: Proposed Controllermentioning

confidence: 99%

“…[3] describe The PID of the model experiment consequences show the FOPID has strong strength. [4] determin very simple system to implemnt defferent types of PID systems. [5] explain FOPID system for speed system design.…”

Section: Introductionmentioning

confidence: 99%

Response Enhancement of Dc Motor Using Evolutionary Intelligent Fractional-Order Pid Controller

2018

QJES

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“…Genetic algorithms operate on an initial population of search solutions applying the principle of survival of the fittest to produce better solutions [17]. At each generation a new set of solutions is created which will ideally have greater fitness values than the previous solutions.…”

Section: Controller Designmentioning

confidence: 99%

“…When applied FGA to PID design, the chromosome consist of three genes, each gene represents the controller gain. Usually the error criterion such as integral square error (ISE) is used as a fitness function [17].…”

Section: Controller Designmentioning

confidence: 99%

Transient Response Enhancement of High Order Synchronous Machine based on Evolutionary PID controller

Song¹,

Albakira²,

Mohammed³

2014

IJCA

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“…For this reason, many intelligent optimization techniques have been employed to determine the optimal parameters of PI/PID controller and hence improve the controller performances. Such intelligent optimization techniques include, Differential Evolution (DE) algorithm [2], [3], fuzzy systems [4][5][6], Ant Colony Optimization [7][8], , Particle Swarm Optimization (PSO) [9][10], Genetic Algorithm (GA) [11][12][13][14].Great attention is to find tuning methods that lead to the optimal operation of the PID controllers. A control system is considered an optimum control system when its parameters are adjusted so that its performance index reaches an extreme value.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Intelligent Control System Tuning Methods for an Evaporator based on Genetic Algorithm

Halim¹,

Othman²,

Sakr³

et al. 2017

IJAIS

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This paper employs Genetic Algorithm to obtain the optimum parameters of an evaporator control system by using different tuning methods. Tuning methods consists of two main groups; first group consists of minimizing the performance indices factors separately such as; Integral of Absolute Error (IAE), Integral of Square Error (ISE), Integral of Time Absolute Error (ITAE) and Integral of Time multiplied with Square Error (ITSE).Second group consists of minimizing the performance indices factors separately plus the step response parameters such as; the rise Time (Tr), Settling Time (Ts), The Maximum Overshoot (Mp) and Steady state Error(Ess). Simulation Results prove that the second group of tuning methods give best performance, robust stability and improve the system robustness.

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Tuning of PID controller for diesel engines using genetic algorithm

Cited by 7 publications

References 6 publications

Response Enhancement of Dc Motor Using Evolutionary Intelligent Fractional-Order Pid Controller

Response Enhancement of Dc Motor Using Evolutionary Intelligent Fractional-Order Pid Controller

Transient Response Enhancement of High Order Synchronous Machine based on Evolutionary PID controller

A Comparative Study of Intelligent Control System Tuning Methods for an Evaporator based on Genetic Algorithm

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