دانش و فناوری هوافضا

دانش و فناوری هوافضا

هدایت و کنترل مدل دوبعدی یک موشک پدافند هوایی با استفاده از کنترل تطبیقی یادگیری عمیق و فازی

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشجوی دکتری، دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران.
2 دانشیار، دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران
چکیده
روش طراحی معمول هدایت و کنترل، به دلیل در نظر نگرفتن تداخل زیرسیستم‌‌های هدایت و کنترل و نیز به دلیل تأخیر ناشی از اختلاف فرکانس کاری زیرسیستم‌‌ها، سبب ناپایداری یا فاصله عدم برخورد غیرقابل قبول می‌‌شود. از این‌‌رو بهتر است حتی‌الامکان حالت‌‌های مختلف برای زیرسیستم‌‌های هدایت و کنترل به‌‌طور هم‌‌زمان در روند طراحی در نظر گرفته شوند تا دقت و عملکرد کلی سیستم در فاز نهایی افزایش یابد. این امر موجب بهبود کارآیی و صرفه‌جویی در زمان و هزینه می‌‌گردد. در روش طراحی یکپارچه سیستم هدایت و کنترل، تمام قیود زیرسیستم‌‌ها در حین طراحی در نظر گرفته می‌‌شوند و درنتیجه عملکرد سیستم بهبود خواهد یافت. این مقاله به تشریح روند طراحی و شبیه‌‌سازی عملکرد کنترل‌‌کننده‌‌ تطبیقی یادگیری عمیق و فازی می‌‌پردازد، که به منظور هدایت موشک در یک سناریوی دو بعدی جهت کمینه‌‌سازی زمان برخورد و فاصله عدم برخورد به هدف ایجاد شده ‌‌است. در طراحی کنترل‌کننده، ابتدا یک کنترل‌کننده شبکه عصبی یادگیری عمیق بصورت آفلاین طراحی شده و بصورت جدول بهره در کنترل کننده تطبیقی استفاده می‌شود. در ادامه، با اضافه کردن کنترل فازی، توانمندی این کنترل‌کننده افزایش می‌یابد. عملکرد هر دو کنترل‌کننده در حضور اغتشاش مورد ارزیابی قرار میگیرد و با توجه به شبیه‌سازی‌ها نشان داده شد که استفاده از این کنترل‌کننده‌های پیشنهادی و به‌کارگیری مدل هدایت و کنترل یکپارچه، فاصله عدم برخورد نهایی موشک به هدف و زمان برخورد در مقایسه با کنترل‌کننده PID کاهش یافته است.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Guidance and control of a two-dimensional model of an air defense missile using deep learning and fuzzy adaptive control

نویسندگان English

Mohammadmahdi Soori 1
Seyed Hossein Sadati 2
1 PhD student, Mechanical Engineering Department, K. N. Toosi University of Technology, Tehran
2 Associate Professor, Mechanical Engineering Department, K. N. Toosi University of Technology, Tehran.
چکیده English

Conventional method of designing missile guidance and control, due to not taking into account the interference of the guidance and control subsystems and also due to the delay caused by the difference in working frequency of the subsystems, normally leads to instability or unacceptable miss distance. It is advisable to consider the states of the guidance and control subsystems simultaneously in the design process to increase the accuracy and overall performance of the system in the final phase. This can improve efficiency, and it saves time and effort. In the integrated design method of the guidance and control system, limitations of the subsystems are considered in whole during the design, and as a result, the performance of the system will be improved. This article describes the process of designing and simulating the performance of a deep and fuzzy adaptive controller, proposed to guide the missile in a two-dimensional problem of minimizing the collision time and the distance to the target. In the design of the controller, the deep learning neural network controller is first designed offline and used as a gain table in the adaptive controller. Next, this controller is improved by adding fuzzy control. The performance of both controllers is evaluated in the presence of disturbance. Based on simulation results, it is shown that the use of these proposed controllers and the application of the integrated guidance and control model leads to improved miss distance as well as collision time compared to similar results obtained using a PID controller.

کلیدواژه‌ها English

missile
integrated guidance and control
deep learning control
adaptive control
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