Design of an adaptive missile autopilot considering the boost phase using the SDRE method and neural networks

Abstract

An adaptive autopilot to control a skid-to-turn missile during its boost phase is designed using the state-dependent Riccati equation (SDRE) method and neural networks (NN). To address the rapid changes in parameters during the boost phase, the translational and rotational motions of the missile are modeled with time-varying velocity and inertial parameters. The autopilot with a two-loop structure is designed to perform integrated roll-pitch-yaw control of the missile with cross-coupled dynamics; each loop has a baseline controller and an adaptive controller. The baseline controller is designed using the SDRE method for reference command tracking in a nominal environment, and the adaptive controller is designed based on NN to manage uncertainty during the boost phase. Stability analysis of the closed-loop system is performed, and the performance of the proposed autopilot is demonstrated by numerical simulation.