Genetic algorithms in controller design and tuning

Varšek, Alen; Urbančič, Tanja; Filipič, Bogdan

doi:10.1109/21.260663

Cited by 165 publications

(39 citation statements)

References 9 publications

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“…GA has been recognized as an effective technique for optimization problems [7][8][9]. GA starts with an initial population containing several chromosomes.…”

Section: Genetic Algorithm [Ga]mentioning

confidence: 99%

Speed Control of DC Motor Using PID Controller Based on Changed Intelligence Techniques

Elsrogy¹,

Bahgaat²,

Mi³

et al. 2018

Int J Swarm Intel Evol Comput

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The objective from this paper is to design speed controller for DC motors by choice of a PID factors using Diverse Methods Ziegler and Nichols (ZN), Genetic Algorithm (GA), Modified Adaptive Acceleration Particle Swarm Optimization (MAACPSO) and Adaptive Neuro-Fuzzy Inference System (ANFIS). All of tuning methods for parameters of PID controller will be compared based on improved performance and effectiveness over them.

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“…GA has been recognized as an effective technique for optimization problems [7][8][9]. GA starts with an initial population containing several chromosomes.…”

Section: Genetic Algorithm [Ga]mentioning

confidence: 99%

Speed Control of DC Motor Using PID Controller Based on Changed Intelligence Techniques

Elsrogy¹,

Bahgaat²,

Mi³

et al. 2018

Int J Swarm Intel Evol Comput

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show abstract

“…After the operations of reproduction, crossover, and mutation are performed on the current population, the offspring population of the new generation replaces the old generation. Each individual in the new population of computer programs is measured for fitness, and the process is repeated over many generations [13][14][15][16][17][18][19][20][21]. Fig.…”

Section: Figmentioning

confidence: 99%

Development of a New Personal Magnetic Field Exposure Estimation Method for Use in Epidemiological EMF Surveys among Children under 17 Years of Age

Yang¹,

Ju²,

Myung³

et al. 2012

Journal of Electrical Engineering and Technology

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-A number of scientific researches are currently being conducted on the potential health hazards of power frequency electric and magnetic field (EMF). There exists a non-objective and psychological belief that they are harmful, although no scientific and objective proof of such exists. This possible health risk from ELF magnetic field (MF) exposure, especially for children under 17 years of age, is currently one of Korea's most highly contested social issues. Therefore, to assess the magnetic field exposure levels of those children in their general living environments, the personal MF exposure levels of 436 subjects were measured for about 6 years using government funding. Using the measured database, estimation formulas were developed to predict personal MF exposure levels. These formulas can serve as valuable tools in estimating 24-hour personal MF exposure levels without directly measuring the exposure. Three types of estimation formulas were developed by applying evolutionary computation methods such as genetic algorithm (GA) and genetic programming (GP). After tuning the database, the final three formulas with the smallest estimation error were selected, where the target estimation error was approximately 0.03 μT. The seven parameters of each of these three formulas are gender (G), age (A), house type (H), house size (HS), distance between the subject's residence and a power line (RD), power line voltage class (KV), and the usage conditions of electric appliances (RULE).

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“…For these reasons, it is highly desirable to increase the capabilities of PI controllers by adding new features. Many random search methods, such as Genetic Algorithm (GA) have recently received much interest for achieving high efficiency and searching global optimal solution in problem space (O'Mahony et al, 2000;Varsek et al, 1993) such as the search of optimal PI controller parameters.…”

Section: Introductionmentioning

confidence: 99%

Genetic Based Plus Integral Controller for PMBLDC Motor Control Using Resonant Pole Inverter

T.¹

2012

American Journal of Applied Sciences

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Permanent Magnet Brushless DC (PMBLDC) motor drives are increasingly popular in industrial applications due to rapid progress of technologies in power electronics and the growing demand for energy saving. The increasing demand of energy saving from society is the external force for the development of PMBLDC motor drives. It is however driven by a hard-switching Pulse Width Modulation (PWM) inverter, which has low switching frequency, high switching loss, high Electro-Magnetic Interference (EMI), high acoustic noise and low efficiency, etc. To solve these problems of the hard-switching inverter, many softswitching inverters have been designed in the past. Unfortunately, high device voltage stress, large dc link voltage ripples, complex control scheme and so on are noticed in the soft-switching inverters. This study introduces a novel genetic-proportional Plus Integral (PI) controller based resonant pole inverter using transformer, which can generate dc link voltage notches during chopping which minimize the drawbacks of soft-switching. Hence all switches work in zero-voltage switching condition. The performance of the genetic-based PI controller is compared with conventional PI controller. The experimental results show that the genetic-based PI controller renders a better transient response than the conventional PI controller resulting in negligible overshoot, smaller settling time and rise time. Moreover the proposed controller provides low torque ripples and high starting torque. Both simulation and experimental results are presented to show the superiority of the proposed GA-PI controller based resonant pole inverter.

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Genetic algorithms in controller design and tuning

Cited by 165 publications

References 9 publications

Speed Control of DC Motor Using PID Controller Based on Changed Intelligence Techniques

Speed Control of DC Motor Using PID Controller Based on Changed Intelligence Techniques

Development of a New Personal Magnetic Field Exposure Estimation Method for Use in Epidemiological EMF Surveys among Children under 17 Years of Age

Genetic Based Plus Integral Controller for PMBLDC Motor Control Using Resonant Pole Inverter

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