Nonlinear Distributed Model Predictive Control for Multiple Missiles Against Maneuvering Target with a Trajectory Predictor

Abstract

This study aims to solve the problem of multi-missile simultaneous attacks on maneuvering target. The challenges include multi-missile cooperative control and target’s trajectory prediction. A controller based on nonlinear distributed model predictive control (NDMPC) is designed for multiple missiles against a maneuvering target, and a trajectory prediction method based on particle swarm optimization (PSO) algorithm is proposed. This study has mainly completed the following three aspects of work. Firstly, the cost function of the controller is constructed to optimize the accuracy and synchronization of the multi-missile system with consideration of collision avoidance. Secondly, the velocity control of the leading missile is designed by using the range-to-go information in real time to ensure the attack efficiency and the control of the terminal velocity difference. Finally, a kinematic model of the target is estimated by using short-term real-time data with the PSO algorithm. The established model is employed to predict the target trajectory in the interval between radar scans. Numerical simulation results of two different scenarios demonstrate the effectiveness of the proposed cooperative guidance approach.