Optimization Design of BP-PID Neural Networks for Falcon Rocket Attitude Control System

This paper takes the SpaceX Falcon 9 launch vehicle as the research object and optimizes the design of its attitude control system based on the MATLAB platform. First, it introduces the structure and parameters of the Falcon 9 launch vehicle in detail, including its two-stage propulsion system, engine configuration, and thrust characteristics. Second, it establishes the kinematics and dynamics equations of the rocket launching process and analyzes the forces and velocity increments of the rocket at different stages (e.g., takeoff, first-stage operation, separation, and ignition). On this basis, the paper designs an attitude control system based on a PID controller and implements numerical simulation of the system through MATLAB/Simulink. To address the external disturbances (e.g., wind disturbances, aerodynamic changes) and internal disturbances (e.g., fuel consumption, thrust asymmetry) that the rocket may encounter during flight, the study proposes an improved PID control strategy, incorporating an integral anti-saturation mechanism and parameter optimization methods to enhance the system's robustness and anti-interference capability. The simulation results demonstrate that the optimized attitude control system effectively suppresses random disturbances, enabling the rocket's attitude angle and angular velocity to converge to the target values quickly. This significantly improves the system's stability and control accuracy. The research in this paper provides a theoretical basis and practical method for the design and optimization of rocket attitude control systems.