Particle Swarm and Fuzzy Logic Based Optimal Energy Control of Induction Motor for a Mine Hoist Load Diagram.

This paper investigates the importance of controllers on energy saving opportunity of partial loaded three-phase induction motor in mine hoist applications. The input power of a vector controlled 1 HP induction motor is investigated with three topologies namely constant flux operation, loss model based flux controller using Particle Swarm Optimization (PSO) and search controller in steady-state conditions. In this study, the flux level in a machine has been considered to adjust to give minimum input power for a given load of the motor. Even though flux controllers improve the performance of the motor in terms of minimum input power, they offer ripples in torque and speed of the motor (lower stability). To increase the stability of the motor drive during variable speed and load operation, Fuzzy Pre-compensated Proportional Integral (FPPI) Controller is used and compared its results with conventional Proportional Integral (PI) controller. According to the test results DE along with fuzzy logic outperforms the conventional controllers and saves 100 W power in the test motor. Four benchmark problems are used to validate PSO algorithm. C++ code is used for PSO implementation. [ABSTRACT FROM AUTHOR]