Robust Unbalance Compensation of Induction Machines Using Swarm Intelligence Control: Design and Analysis

Abstract

This work presents an innovative approach for solving the problem of unbalance in three-phase induction motors (IM). The presented contribution is based on optimal controller operating with a quantized swarm-intelligence algorithm. The work starts by modeling and investigating the effects of unbalance factors on a three-phase IM operation. The mathematical model of the IM is based on steady state symmetrical component analysis which represents the discrete Fourier transform governing the estimation of control voltages fed into the swarm. The three-phase power input of an IM is controlled by a DSP controller with three-phase current sensors and an output stage that controls the power level of each phase fed into the motor. The controller measures the currents, estimates the current unbalance factor, searches for voltage levels that reduces the unbalance based on a cost functional, therefore, generates control signals on power electronics stage. The swarm-intelligence algorithm searches solutions in a stochastic space for three-phase voltages that minimize and even nullify the unbalance and reacts instantaneously. The algorithm shows very fast convergence to IM input voltages solution in less than 80 ms. The present work is concerned with the design and analysis of applying swarm intelligence control to implement unbalance compensation in three-phase IMs.