Document Type : Research Article


Mechanical Engineering Department, K. N. Toosi University of Technology, Tehran


In the integrated guidance and control approach, the guidance law is developed separately and tested assuming the ideality of the autopilot. The autopilot is also designed independently and is tested assuming the ideality of the guidance law. This article describes the process of designing and simulating the performance of the deep and fuzzy learning adaptive controller, which was created in order to guide the missile in a three-dimensional scenario to minimize the time of collision and the distance of non-collision with the target. In controller design, first a deep learning neural network controller is designed offline and used as a gain table in the adaptive controller. Next, by adding fuzzy control, the capability of this controller increases. The performance of both controllers is evaluated in the presence of disturbance, and according to the simulations, it was shown that the use of these proposed controllers and the application of the integrated guidance and control model, the distance of the final failure of the missile to the target and the collision time compared to the controller PID and LQR are reduced.


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