Hybrid bacteria foraging-particle swarm optimization algorithm in DTC performance improving for induction motor drive

Abstract

<p dir="ltr"><span>This paper presents a hybrid algorithm that combines the particle swarm optimization method with the bacteria foraging technique, named: BF-PSO. The aim is to achieve more efficient and precise parameters determination of the regulators that leads to performance improvement in the speed-loop control of an induction motor (IM) implemented in a direct torque control (DTC). The approach consists of tuning the proportional-integral (PI) parameters that meet high dynamics and tracking behavior using the hybrid BF-PSO algorithm. </span>Investigations have been completed with Matlab/Simulink and several performance tests are conducted. The comparison results are exposed with the most used indices in the controllers' tuning with optimization techniques. It will be shown that the presented technique presents better quality results compared to the conventional method of calculated PI.</p><div><span><br /></span></div>

Comparative study of nature-inspired maximum power point tracking algorithms for partially shaded photovoltaic systems

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