هدایت و کنترل یکپارچه کانال فراز موشک آشیانه یاب زمین به هوا با استفاده از کنترل عصبی بهینه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری / دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران

2 عضو هیات علمی / دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران

چکیده

به شکل مرسوم سیستم هدایت و کنترل موشک از سه زیرسیستم ناوبری، هدایت و کنترل تشکیل می‌شود. وظیفه این زیر سیستم‌ها به ترتیب محاسبه مقدار انحراف وسیله هدایت‌شونده از مسیر مطلوب، تعیین حرکت یا شتاب مناسب برای جبران انحراف است. در روش‌های معمول طراحی سیستم هدایت و کنترل، هر یک از زیرسیستم‌های هدایت و کنترل به‌طور جداگانه و با فرض ایده‌آل بودن زیرسیستم دیگر طراحی می‌شود. در رویکرد هدایت وکنترل یکپارچه، قانون هدایت به‌طور جداگانه توسعه یافته و با فرض ایده‌آل بودن خودخلبان آزموده می‌شود. خودخلبان نیز به‌طور مستقل طراحی شده و با فرض ایده‌آل بودن قانون هدایت آزموده می‌شود. این مقاله به تشریح روند طراحی و شبیه‌سازی عملکرد کنترل‌کننده عصبی بهینه می‌پردازد، که به منظور هدایت موشک در یک مساله دو بعدی کمینه‌سازی زمان برخورد و فاصله تا هدف ایجاد شده است. در طراحی کنترل‌کننده عصبی بهینه، ابتدا نوع کلاسیک و معمول یک کنترل‌کننده عصبی بهینه شامل دو شبکه عصبی کم‌عمق شناساگر و کنترل‌کننده، طراحی شده و از طریق انجام شبیه‌سازی نشان داده شده است که عملکرد این کنترل‌کننده برای مسئله مورد بررسی مطلوب نیست. بنابراین با جایگزینی شبکه‌های کم‌عمق شناساگر و کنترل‌کننده، با نوع عمیق و بهره‌گیری از مفاهیم یادگیری تقویتی، نتایج شبیه‌سازی‌های انجام شده بهبود عملکرد این نوع کنترلر را نشان می‌دهد. دراین تحقیق مدل یکپارچه موشک با تلفیقی از شبکه عصبی یادگیری عمیق با الگوریتم‌های بهینه‌سازی انجام شده و‌ استفاده از کنترل شبکه عصبی و الگوریتم‌های بهینه‌سازی باعث افزایش دقت برخورد وکاهش زمان پرواز شد.

کلیدواژه‌ها

عنوان مقاله [English]

Integrated guidance and control of the surface-to-air homing missile Pitch channel using optimal neural network

نویسندگان [English]

  • Mohammad Mahdi 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]

, the missile guidance and control system consists of three subsystems: navigation, guidance, and control. The task of these sub-systems is to calculate the deviation of the guided vehicle from the desired path so as to determine the appropriate movement or acceleration to compensate for the deviation. In the traditional methods , each of the guidance and control subsystems is designed separately, a. In the integrated guidance and control approach, the guidance law is developed separately and tested under the assumption of ideal autopilot. The autopilot is also designed independently and is tested under the assumption of an ideal guidance law. This paper describes the process of designing and simulating the performance of the optimal neural controller, which was created in order to guide the missile in a two-dimensional problem of minimizing the collision time and the distance from the target. In the design of the optimal neural controller, first the classical optimal neural controller (MLP) neural networks, the identifier, and the controller was designed and through simulation it was shown that the performance of this controller is not satisfactory. Therefore, by replacing the estimator MLP networks and controller with the deep type network, along with the use of the concepts of reinforcement learning, a quite improved performance was demonstrated through simulation. In this research, the integrated rocket model was made by integrating deep learning neural network with optimization algorithms, and the use of neural network control and optimization algorithms increased collision accuracy and reduced flight time.

کلیدواژه‌ها [English]

  • missile
  • integrated guidance and control
  • optimal control
  • neural network control
  • deep neural network

مراجع

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