Fuzzy Logic-Based Vector Control Method for Induction Motors
محورهای موضوعی : منطق فازی، نظریه مجموعه های فازی، و منطق چند ارزشی
1 - Energy and Environment Research Center, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
کلید واژه: Fuzzy logic, Speed control, Torque control, Induction motors, Motor performance optimization,
چکیده مقاله :
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.
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.
[1] R. Kumar, S. Das, P. Syam, and A. K. Chattopadhyay, “Review on model reference adaptive system for sensorless vector control of induction motor drives,” IET Electr Power Appl, vol. 9, no. 7, pp. 496–511, Aug. 2015, doi: 10.1049/iet-epa.2014.0220.
[2] S. Di Gennaro, J. Rivera Dominguez, and M. A. Meza, “Sensorless High Order Sliding Mode Control of Induction Motors With Core Loss,” IEEE Transactions on Industrial Electronics, vol. 61, no. 6, pp. 2678–2689, Jun. 2014, doi: 10.1109/TIE.2013.2276311.
[3] V. V. Alekseev, A. P. Emel’yanov, and A. E. Kozyaruk, “Analysis of the dynamic performance of a variable-frequency induction motor drive using various control structures and algorithms,” Russian Electrical Engineering, vol. 87, no. 4, pp. 181–188, Apr. 2016, doi: 10.3103/S1068371216040027.
[4] S. Yaacob and F. A. Mohamed, “Real time self tuning controller for induction motor based on PI method,” in SICE ’99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456), Soc. Instrum. & Control Eng, pp. 909–914. doi: 10.1109/SICE.1999.788670.
[5] F. N. Sarapulov, V. E. Frizen, E. L. Shvydkiy, and I. A. Smol’yanov, “Mathematical Modeling of a Linear-Induction Motor Based on Detailed Equivalent Circuits,” Russian Electrical Engineering, vol. 89, no. 4, pp. 270–274, Apr. 2018, doi: 10.3103/S1068371218040119.
[6] M. Konuhova, “Induction Motor Dynamics Regimes: A Comprehensive Study of Mathematical Models and Validation,” Applied Sciences, vol. 15, no. 3, p. 1527, Feb. 2025, doi: 10.3390/app15031527.
[7] C. W. de Silva, Intelligent Control. CRC Press, 2018. doi: 10.1201/9780203750513.
[8] Y. A. Almatheel and A. Abdelrahman, “Speed control of DC motor using Fuzzy Logic Controller,” in 2017 International Conference on Communication, Control, Computing and Electronics Engineering (ICCCCEE), IEEE, Jan. 2017, pp. 1–8. doi: 10.1109/ICCCCEE.2017.7867673.
[9] L. A. Zadeh, “Fuzzy Logic,” 2009, pp. 19–49. doi: 10.1007/978-1-0716-2628-3_234.
[10] M. Masoumi, S. Hossani, F. Dehghani, and A. Masoumi, THE CHALLENGES AND ADVANTAGES OF FUZZY SYSTEMS APPLICATIONS A PREPRINT. 2020. doi: 10.13140/RG.2.2.22310.96328.
[11] A. G. M. A. Aziz, A. Y. Abdelaziz, Z. M. Ali, and A. A. Z. Diab, “A Comprehensive Examination of Vector-Controlled Induction Motor Drive Techniques,” Energies (Basel), vol. 16, no. 6, p. 2854, Mar. 2023, doi: 10.3390/en16062854.
[12] A. Mishra and P. Choudhary, “Speed control of an induction motor by using indirect vector control method,” International Journal of Emerging Technology and Advanced Engineering, vol. 2, no. 12, pp. 144–150, 2012.
[13] G. Satyanarayana, M. Karthikeyan, R. Mahalakshmi, and T. Vandarkuzhali, “Vector Control of an Induction Motor for Speed Regulation,” in 2023 7th International Conference on Computing Methodologies and Communication (ICCMC), IEEE, Feb. 2023, pp. 1621–1625. doi: 10.1109/ICCMC56507.2023.10084248.
