High-Precision and Efficient Multi-Physics Modeling for Missile Servo Systems

The missile servo system is an important system that controls the missile's flight trajectory, and its performance directly affects the missile's guidance accuracy and maneuverability. Therefore, establishing a high-precision missile servo system model is of great significance for conducting missile performance analysis. However, the missile servo system is a complex system that includes multiple disciplines such as mechanics, electromagnetics, and controls. Traditional servo system modeling methods focus on a single discipline, resulting in many problems such as low simulation accuracy and long product design cycles, which cannot meet the current rapid, agile, and high-precision design requirements. Although multi-physics-based modeling methods can provide high-precision integrated simulation models, the large data scale required and low computational efficiency have limited their large-scale promotion and application. Therefore, a method that can guarantee higher simulation accuracy while greatly improving computational efficiency is needed to solve the contradiction between high precision and high computational efficiency in missile servo system multi-physics-based modeling.

This paper takes the air-to-air missile servo system as the research object, and models and optimizes the servo system's motor, transmission mechanism, and control algorithm by analyzing the composition and principle of the missile servo system. The model reduction technology and its application in the motor finite element system are deeply studied to complete the construction of the reduced-order model. The integrated simulation technology is used to achieve high-precision and high-efficiency multi-physics-based modeling and analysis of the servo system. The main research contents are as follows:

(1) Analyze the basic composition and working principle of the missile servo system, conduct in-depth research on each subsystem of the electric servo system, and complete the modeling and analysis of the main subsystems such as the motor, transmission mechanism, and control. Use Maxwell software to complete the motor design and verify the rationality of the motor model through magnetic circuit calculation and finite element analysis results. Establish a multi-rigid body dynamics model of the transmission mechanism, import the flexible body model into the finite element software to establish a rigid-flexible coupling model, and complete comparative verification. In the control subsystem, a fuzzy PID control algorithm is established, and the system response of traditional PID control is compared and analyzed.

(2) In order to improve the computational efficiency of the finite element model, the model reduction method based on the Kriging model is used to optimize the finite element model. By building a motor finite element model and conducting motor simulation, the simulation results are used to construct a training dataset. After collecting sample points that meet the requirements, the Kriging method is used to construct a response surface model, and the performance of the reduced-order model is judged by predicting the response of unknown points through the built motor finite element model. Then, the trained reduced-order model is used to replace the motor model for simulation, and the reduced-order model is compared with the motor simulation results based on other methods to verify the effectiveness of the model reduction method.

(3) Using integrated simulation technology in the Simplorer platform, the main subsystem models of the missile servo system are integrated to establish a multi-physics-based model. Through the working principle between the main subsystem models, integrated simulation is achieved. Comparing the simulation results with the physical test results not only verifies the reliability of the multi-physics-based model but also reduces the system iteration times and optimizes the system design process.

This paper establishes the models of the main subsystems of the servo system and conducts analysis, uses integrated simulation to build a multi-physics-based model, and improves the model's computational efficiency through model reduction methods. Through the analysis of the integrated simulation results, the simulation and verification of the missile servo system multi-physics-based model are finally achieved.