DESIGN OF OPTIMAL PID CONTROLLER FOR THREE PHASE INDUCTION MOTOR BASED ON ANT COLONY OPTIMIZATION

Speed control of an induction motor is an important part of the operation of an induction motor. One method of regulating motor speed is the addition of a PID controller. PID parameters must be tuned properly to get the optimal speed. In this study, the PID controller tuning method uses an artificial intelligence method based on Ant Colony Optimization (ACO). ACO algorithm in an intelligent algorithm that is inspired by the behavior of ants looking for food sources in groups with traces of feromone left behind. In this study, food sources are represented as optimal parameters of PID. From the computational results obtained optimal parameters respectively, P (Proportional) 0.5359, I (Integral) 0.1173, D (Derivative) 0.0427. ACO computing found the optimal parameters in the 21st iteration with a minimum fitness function of 11.8914. Case studies are used with two variations of the speed of the induction motor input. With optimal tuning, the performance of the induction motor is increasing, marked by a minimum overshoot of 1.08 pu and a speed variation of both overshoots of 1,201 pu, whereas without control 1.49 pu and 1.28 pu, as well as with PID trial control of 1.22 pu and 1.23 pu respectively. The benefits of this research can be used as a reference for the operation of induction motors, by tuning the Ant Colony intelligent method for the PID controller in real-time with the addition of microcontroller components

Induction Motor Control Using Two Intelligent Algorithms Analysis

Part 6: RoboticsInternational audienceThe main drawbacks of classical direct torque control (C-DTC) are: the high torque and flux ripples and variable switching frequency. To overcome these problems, two intelligent control theories, namely fuzzy logic control (FLC) and neuro-fuzzy control (NFC) are introduced to replace the hysteresis comparators and lookup table of the C-DTC for induction motor drive. The effectiveness and feasibility of the proposed approaches have been demonstrated through computer simulations. A comparison study between the C-DTC, FL-DTC and NF-DTC has been made in order to confirm the validity of the proposed schemes. The superiority of the NF-DTC has been proved through comparative simulation results