الگوریتم جدید فرا ابتکاری تطبیقی در تخمین وضعیت و مدل فضاپیما

نویسندگان

1 دانشگاه شهید بهشتی - دانشکده مهندسی فناوری های نوین

2 دانشگاه شهید بهشتی

چکیده

افزایش دقت و پایداری‌ در تخمین آنلاین مدل یک فضاپیما، به دلیل هم‌زمانی وجود نامعینی در دینامیک سیستم و نویز در خروجی حس‌گرهای وضعیت، یکی از چالش‌های کنترل وضعیت است. یکی از روش‌های مؤثر تخمین این نوع از مدل‌های دینامیکی، روش کمترین مربعات خطا در ترکیب با فیلتر کالمن است. برای افزایش عملکرد روش تخمین ذکر شده، الگوریتم آنلاین فرا ابتکاری جدیدی بر اساس توسعه روش کمترین باقیمانده تعمیم‌یافته ارائه می‌گردد. این الگوریتم یک روش مبتنی بر تکرار است که با استفاده از اطلاعات مرحله قبل و بر اساس تجربه کاربر، و یا یک روش فرا ابتکاری آنلاین نوین، تعداد گام‌های حل دستگاه در زیر فضای کریلف را تعیین کرده و همگرایی کلی به پاسخ را بهبود می‌بخشد. برای بررسی دقت تخمین این روش، روش‌های کمترین باقیمانده تعمیم‌یافته ساده، گرادیان دو مزدوجی، گرادیان مزدوج مربعی و گرادیان دو مزدوجی پایدار مقایسه شده است، که روش فرا ابتکاری کمترین باقیمانده تعمیم‌یافته تطبیقی بیشترین دقت و پایداری در پاسخ را نشان می‌دهد.

کلیدواژه‌ها


عنوان مقاله [English]

A New Online Meta-Heuristic Adaptive GMRES Method to Estimate the Attitude and the Model of a Satellite

نویسندگان [English]

  • M. Navabi 1
  • ُshahram Hosseini 2
1 هوافضا شهید بهشتی
2 shahid Beheshti university
چکیده [English]

 Increasing precision and stability in the online estimation of a spacecraft's model, due to the uncertainty and noise is one of the challenges in the attitude control of the space systems. The least squares error method in combination with the Kalman filter is one of the effective methods for estimating these types of dynamic models. Based on the development of the GMRES (generalized minimal residual) methods, in order to increase the performance of the estimation method, a newonline meta-heuristic algorithm is proposed. The algorithm is an iterative-based method that uses previous step information based on user experience, or a new online meta-heuristic method which determines the number of steps to solve the matrix equations system in the Krylov subspace and improves overall convergence to the response. In order to evaluate the accuracy of this estimation method, the GMRES, Bi-CG (Bi Conjugate Gradient), CGS (Conjugate Gradients Squared), BI-CGSTAB (Bi Conjugate Gradient Stabilized) methods are compared that the online meta-heuristic GMRES method shows the highest accuracy and stability in the estimation.

کلیدواژه‌ها [English]

  • Adaptive GMRES
  • Model Estimation
  • attitude estimation
  • Meta-heuristic
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