کنفرانس بین المللی ماشین و محرکه های الکتریکی

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صفحه اصلی / icemd2024

Neural Network and Fractional-Order Control of Permanent Magnet Synchronous Machine (PMSM)

نویسندگان :

Aliyu Sabo¹ Theophilus Ebuka Odoh² Noor Izzri Abdul Wahab³ Hossein Shahinzadeh⁴ Ahmad Hafezimagham⁵ Gevork B Gharehpetian⁶

1- Universiti Putra Malaysia 2- Dangote Refinery and Petrochemicals (DPRP) 3- Universiti Putra Malaysia 4- دانشگاه صنعتی امیرکبیر (پلی‌تکنیک تهران) 5- دانشگاه صنعتی امیرکبیر (پلی‌تکنیک تهران) 6- دانشگاه صنعتی امیرکبیر (پلی‌تکنیک تهران)

کلمات کلیدی :

Permanent Magnetic Synchronous Machine (PMSM)،Fractional Order Proportional Integral Derivate (FOPID)،Artificial Neural Network (ANN)،Proportional Integral (PI) Controller

چکیده :

The Permanent Magnet Synchronous Machine (PMSM) is known for its high efficiency and ability to maintain consistent power across a wide speed range in motor drive systems. However, achieving this performance requires robust and reliable control systems. This paper presents a hybrid control approach combining fractional-order control and neural network techniques as a replacement for traditional Proportional-Integral (PI) controllers in PMSM control systems. Using the Simulink Design Optimization Toolbox, a fractional-order Proportional-Integral-Derivative (FOPID) controller was developed and its parameters optimally tuned. Simultaneously, the neural network controller employs an error correction learning mechanism to minimize the deviation between the system's output and the desired reference. Simulation results in MATLAB/Simulink demonstrate superior performance of the proposed control system compared to the conventional PI controller, achieving enhanced precision and stability in PMSM operations.