Design and Development of an Intelligent Control by Using Bee Colony Optimization Technique

Problem statement: In the modern industrial manufacturing system, the efficiency of machine control is essential to reduce waste and increase the output. Most of the manufacturing machines employ an induction motor in their driving system. A number of induction motors must be controlled during machine operation. The more accurately these motors are controlled the higher is the quality of the finished product. Approach: This study focuses on using the Bee Colony Optimization (BCO) to find optimal fuzzy rules and membership functions of a fuzzy speed controller for an indirect field-orientated Induction Motor (IM). The BCO optimizes those quantities so that the controller can control the motor to a desired speed with the minimum rise time and speed error. The fitness function of BCO is defined as rise time and Integral Time Absolute Error (ITAE). An indirect field-orientation method for an IM drive and a description of the BCO are introduced briefly. Results: The speed tracking capability of the Proportional-Integral (PI), fuzzy and BCO optimized fuzzy controllers are compared under no-load and various load conditions with different reference speeds. Conclusion: The designed controller could track to the set point with a relatively minimum rise time and low overshoot compared to the other conventional controllers.