Speed Control of Induction Motor by Z-N Method and Genetic Algorithm Optimization with PI and PID Controller

Manepalli, Jaya Raju; Raja, Ch.

doi:10.17148/ijireeice.2015.3304

Cited by 6 publications

(1 citation statement)

References 11 publications

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“…Global optimization techniques have caught the attention in the field of controller parameter optimization [8]. Genetic algorithm (GA) is illustrated in [9][10][11][12][13] for speed control of IM despite the fact that this optimization technique requires a very long run time that may be several minutes or even several hours depending on the size of the system under study. Simulated annealing (SA) is introduced in [14] for optimal tuning of speed controllers, but this technique might fail by getting trapped in one of the local optimal.…”

Section: Introductionmentioning

confidence: 99%

ICA-based speed control of induction motor fed by wind turbine

Ali

2015

Neural Comput & Applic

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This paper proposes the speed control of induction motor fed by wind turbine using Imperialist Competitive Algorithm (ICA). The wind turbine plays as a prime mover to a connected DC generator. Pulse-width modulation is used to get three-phase AC voltage from the output of DC generator. The proposed design problem of speed controller is established as an optimization problem. ICA is adopted to search for optimal controller parameters by minimizing the time domain objective function. The behavior of the proposed ICA has been estimated with the behavior of the conventional Ziegler-Nichols and genetic algorithm in order to prove the superiority of the proposed ICA in tuning PI controller. Also, the behavior of the proposed controller has been tested over a wide range of operating conditions. Simulation results confirm on the better behavior of the optimized PI controller based on ICA compared with other algorithms. AbbreviationsIM Induction motor DC Direct current AC Alternating current FLC Fuzzy logic controller ANN Artificial neural network SA Simulated annealing GA Genetic algorithm ABC Artificial bee colony ACO Ant colony algorithm PSO Particle swarm optimization BF Bacteria foraging ICA Imperialist Competitive Algorithm ZN Ziegler-Nichols PWM Pulse-width modulation PI Proportional plus integral IAE The integral of absolute value of the error ITAE The integral of the time-multiplied absolute value of the error ISE The integral of square error ITSE The integral of time-multiplied square errorList of symbols R s ; L ls Stator resistance and leakage inductance R 0 r ; L 0 lr Rotor resistance and leakage inductance L m Magnetizing inductance L S ; L 0 r Total stator and rotor inductances V qs ; i qs q axis stator voltage and current V 0 qr ; I 0 qr q axis rotor voltage and current V ds ; i ds d axis stator voltage and current V 0 dr ; I 0 dr d axis rotor voltage and current u qs ; u ds Stator q and d axis fluxes u 0 qr ; u 0 dr Rotor q and d axis fluxes x m Angular velocity of the rotor h m Rotor angular position P Number of pole pairs x r Electrical angular velocity (x m Á P) h r Electrical rotor angular position (h m Á P) T e Electromagnetic torque T L Shaft mechanical torque J c B Combined rotor and load viscous friction coefficient RThe wind turbine rotor radius V xThe wind speed x tThe mechanical angular rotor speed of the wind turbine P t Wind power (hp) ƿAir density (kg/m 3 )The area of turbine blades (m 2 )The armature generator current and terminal voltage i f , V fThe field generator current and voltage R a ; L aThe armature resistance and inductance R f ; L fThe field resistance and inductance R L ; L L The load resistance and inductance R t R a + R L L t L a + L L

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Section: Introductionmentioning

confidence: 99%