طراحی و اعتبار سنجی تجربی یک مشاهده‌گر حالت توسعه یافته برای تخمین عدم قطعیت‌ها و ورودی ناشناخته جاده در سیستم تعلیق مک فرسون یک چهارم خودرو

نوع مقاله : مقاله پژوهشی

نویسندگان

مهندسی مکانیک، دانشگاه صنعتی سهند، تبریز، ایران.

چکیده

در این مقاله به طراحی و پیاده‌سازی عملی رویت‌گر حالت توسعه‌یافته بر روی دستگاه آزمایش سیستم تعلیق یک‌چهارم خودرو با مکانیزم مک‌فرسون در مقیاس واقعی و مجهز به حسگرهای متعدد پرداخته می‌شود. هدف این الگوریتم، تخمین عدم‌قطعیت‌های مدل و ورودی‌ نامعلوم جاده است که منجر به تعیین یک مدل دینامیکی دقیق برای سیستم تعلیق می‌گردد. در این روش، جمله‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌هایی که شامل عدم‌قطعیت‌های مدل و ورودی‌های نامعلوم جاده است، به عنوان متغیرهای حالت جدید به سیستم اضافه شده و با استفاده از داده‌های مربوط به جابجایی‌های جرم معلق و غیرمعلق تخمین زده می‌شوند. در ادامه به طراحی یک فیلتر کالمن غیرخطی با ورودی نامعلوم جهت مقایسه با رویت‌گر حالت توسعه‌یافته پرداخته می‌شود. نتایج آزمایشگاهی با داده‌های واقعی که توام با خطاهای اندازه‌گیری است، حاکی از دقت بالاتر رویت‌گر حالت توسعه یافته در ایجاد یک مدل دینامیکی قابل اعتماد برای سیستم می‌باشد. ضمن اینکه ساختار این رویت‌گر در مقایسه با فیلتر کالمن با ورودی نامعلوم ساده‌تر بوده و تنظیم آن راحت‌تر است و از تعداد خروجی‌های کم‌تری استفاده می‌کند. هر یک از رویت‌گرهای طراحی شده در ساختار یک سیستم کنترل تعلیق فعال با کنترل‌کننده بهینه غیرخطی استفاده می‌شود تا اهداف سیستم تعلیق را برآورده نماید. نتایج شبیه‌سازی‌ها به صورت نرم‌افزار در حلقه در محیط متلب/آدامز، عملکرد مناسب‌تر کنترل‌کننده با رویت‌گر حالت توسعه یافته را نشان می‌دهند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Design and Experimental Validation of an Extended State Observer for Estimating of Uncertainties and Unknown Road Input in a Quarter-car McPherson Suspension System

نویسندگان [English]

  • Zahra Ahangari Sisi
  • Mehdi Mirzaei
  • Sadra Rafatnia
Faculty of Mechanical Engineering, Sahand University of Technology, Tabriz, Iran
چکیده [English]

This paper deals with the design and experimental implementation of an extended state observer for a fabricated quarter-car suspension platform with a McPherson mechanism equipped with different sensors. The algorithm aims to estimate uncertainties and road input, leading to an accurate dynamic model for the vehicle suspension system. In the proposed method, the terms including uncertainties and unknown road input are added to the system equations as new state variables and then estimated along with other state variables using data of sprung mass and un-sprung mass displacements. A nonlinear Kalman filter with unknown input is also designed to be compared with the extended state observer. The comparison results using the experimental data under measurement errors indicate the high accuracy of the extended state observer in constructing a precise dynamic model for the system. Meanwhile, the extended state observer uses fewer sensors and its regulation is easier.  Both observers are used within the structure of the active suspension system under an optimal nonlinear controller to provide the objectives of the suspension system. Co-simulation results of Adams/MATLAB show the better performance of the proposed controller using the extended state observer.

کلیدواژه‌ها [English]

  • Vehicle suspension system
  • Unknown road input
  • Extended state observer
  • Unknown input Kalman filter
  • Optimal nonlinear control
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