Fuzzy Logic-Based Vector Control Method for Induction Motors
Subject Areas : Fuzzy logic, fuzzy set theory, and many-valued logic
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Keywords: Fuzzy logic, Speed control, Torque control, Induction motors, Motor performance optimization,
Abstract :
Vector control methods in induction motors based on proportional-integral (PI) and proportional-integral-derivative (PID) controllers with fixed gains are not effective against changes in system parameters, load changes, temperature changes, magnetic saturation, and other disturbances due to their strong dependence on machine parameters.
In vector control systems, motor flux and torque control are performed by determining the currents and spatial angles of the vectors, which are not very accurate due to instantaneous oscillations in the load and changes in rotor resistance. In many industrial applications, the stable and precise performance of these controllers is challenged. To deal with these problems, there is a need for an adaptive control system that can dynamically adjust the controller gains.
The use of fuzzy logic controllers (FLC) due to their high flexibility, adaptability to different operating conditions, and improved dynamic response, without the need for a precise mathematical model of the system, can adjust control strategies based on linguistic rules and fuzzy sets.
In this paper, an induction motor indirect vector control method is replaced with the fuzzy logic controller. The results of simulation and evaluation of the method in different conditions show that the use of fuzzy control leads to improved stability, reduced speed, and torque oscillations, reduced system response delay, and increased control accuracy and can be a suitable alternative to classical controllers in industrial applications in systems requiring precise and stable performance.
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