کنترل میدانگرای بدون سنسور موتور سنکرون آهنربای دائم مبتنی بر مود لغزشی سرعت و کنترلکنندههای PID گام کسری در حلقههای جریان تنظیمشده با الگوریتم حرکت ذرات اصلاحشده
محورهای موضوعی : electrical and computer engineering
سجاد خمیسی نسب
1
,
ناصر عرفانی مجد
2
1 - گروه مهندسی برق، پردیس صنعتی شهدای هویزه ، دانشگاه شهید چمران اهواز، اهواز، ایران
2 - گروه مهندسی برق، پردیس صنعتی شهدای هویزه، دانشگاه شهید چمران اهواز، اهواز، ایران
کلید واژه: کنترل میدانگرای بدون سنسور, موتور سنکرون مغناطیس دایم, کنترلکننده PID گام کسری, الگوریتم حرکت جمعی ذرات اصلاحشده.,
چکیده مقاله :
این مقاله یک استراژی کنترلی نوین برای درایو بدون سنسور موتور سنکرون آهنربای دائم (PMSM) ارائه میدهد که مهمترین نوآوری آن ترکیب سهگانه کنترل مود لغزشی، کنترلکنندههای گام کسری و الگوریتم بهینهسازی اصلاحشده در ساختار کنترل میدانگرا میباشد. در این رویکرد، برای اولین بار از کنترل مود لغزشی در حلقه سرعت و کنترلکنندههای PID گام کسری (FOPID) در حلقههای جریان و تخمینگر سرعت مبتنی بر سیستم تطبیق مدل مرجع (MRAS) به صورت همزمان استفاده شده است. نوآوری دیگر ارائه الگوریتم بهینهسازی حرکت جمعی ذرات (PSO) اصلاحشده با مکانیزم دستهبندی ذرات است که در آن ذرات ضعیف بر اساس فاصله از بهترین ذره آموزش دیده و قوانین بهروزرسانی متمایزی برای هر دسته تعریف میگردد. ارزیابی عملکرد در دو سناریوی تغییر ناگهانی گشتاور بار و سرعت مرجع نشان میدهد که روش پیشنهادی نسبت به کنترلکننده PID کلاسیک، خطای بیشینه تخمین سرعت را تا 65 درصد کاهش داده، زمان نشست پاسخ سرعت را تا 50 درصد بهبود بخشیده و نوسانات گشتاور را به طور چشمگیری کاهش میدهد. این برتری عملکرد ناشی از مقاومت ذاتی کنترل مود لغزشی در برابر اغتشاشات، درجه آزادی اضافی کنترلکنندههای گام کسری و دقت بالای الگوریتم بهینهسازی اصلاحشده در تنظیم ضرائب است.
This paper proposes a novel control strategy for the sensorless drive of a permanent magnet synchronous motor (PMSM), whose main innovation is the triple combination of Sliding Mode Control (SMC), Fractional-Order PID (FOPID) controllers, and a modified Particle Swarm Optimization (PSO) algorithm within a Field-Oriented Control (FOC) structure. In this approach, for the first time, SMC is used in the speed loop and FOPID controllers are simultaneously employed in the current loops and in a Model Reference Adaptive System (MRAS)-based speed estimator. Another innovation is the introduction of a modified PSO algorithm featuring a particle clustering mechanism, where weak particles are updated based on their distance from the trained best particle and distinct update rules are defined for each cluster. Performance evaluation under two scenarios (sudden load torque changes and reference speed changes) demonstrates that the proposed method reduces the maximum speed estimation error by up to 65%, improves the speed response settling time by up to 50%, and significantly reduces torque oscillations compared to classical PID control. This performance superiority stems from the inherent robustness of SMC against disturbances, the extra degree of freedom offered by FOPID controllers and the high accuracy of the modified optimization algorithm in tuning the coefficients.
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