NEURAL NETWORKS AUTOPILOT DESIGN FOR BALLISTIC MISSILE

Ali Mohamed  Elmelhi

doi:10.66411/jer.v18i.256

Authors

Ali Mohamed Elmelhi Electrical and Electronic Engineering Department, Faculty of Engineering University of Tripoli, Libya Author

DOI:

https://doi.org/10.66411/jer.v18i.256

Keywords:

Flight Dynamics and Control, Missile Trajectory, Autopilot Design, Neural Network, Nonlinear Control Design

Abstract

Guidance and control system of the ballistic missiles normally refers to a system that automatically controls the flight trajectory. The whole flight trajectory is a combination of the powered flight stage and free flight stage. In this paper, the command angle of attack model is presented and modeled in different phases so that the burnout parameters such as path angle and missile velocity can be evaluated at the end time of the powered flight phase. In addition, the relation between the ballistic range and burnout parameters values is studied, and investigated. Furthermore, the feed forward neural network is used here to stabilize the missile in longitudinal motion. Where, it can be used as an Autopilot dynamics to generate a control signal for elevator actuator deflections which in turns cause the missile to be maneuvered, so that an accurate tracking to a command angle of attack can be satisfied. To demonstrate the objectives of this study, simulation results for a typical ballistic missile are shown at the end of this paper.

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