Conventional controllers like the proportional integral differential (PID) would have being very effective not just for speed control alone, if not for some complexities with individually controlling its respective controllers and summing up their individual contributions to effectively yield controlled signal output. Also, for its insensitivity to changes made to model parameters which may be as a result of misrepresentation of some control variables. As a result of this, developing an intelligent based fuzzy logic controller (FLC) became eminent, and on this basis, this book is written. By varying the motor speed with input reference speed, an error signal and a feedback loop is generated. The FLC then operates on the principles of mapping with corrective measure of the error signal generated and it is regulated by sets of IF-THEN rules integrating the Mamdani fuzzy inference approach. The rules projected and formed are used to overcome the drawbacks of conventional controllers. Since induction motors are widely used in many industries today, most especially squirrel caged, an intelligent approach to the control of these motors will save cost, increase reliability and efficiency
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