Integrated Design of Autonomous Orbit Determination and Orbit Control for GEO Satellite Based on Neural Network

Youtao Gao,Zhicheng You,Bo Xu

doi:10.1155/2020/3801625

Abstract

In order to improve the autonomy of a maneuvered GEO satellite which is a member of a navigation satellite system, an integrated design method of autonomous orbit determination and autonomous control was proposed. A neural network state observer was designed to estimate the state of the GEO satellite, with only the intersatellite ranging information as observations. The controller is determined autonomously by another neural network based on the estimated state and the preset correction trajectory. A gradient descent learning method with a forgetting factor was used to derive the weight updating strategy which can satisfy the system’s stability and real-time performance. A Lyapunov method was used to prove the stability of both the observer and the controller. The neural network observer can reduce the influence of control on autonomous orbit determination. The neural network controller can improve the robustness of the maneuvered GEO satellite. The simulation results show the effectiveness of this method.

Highlights

Autonomous orbit determination (AOD) of a navigation satellite system can effectively enhance the operational safety of the navigation system, which has attracted the attention of many scholars
We proposed an integrated design method of autonomous orbit determination and autonomous control during the GEO satellite maneuver
The joint navigation satellite system (JNSS) constructed by a near-Earth constellation and a Lagrangian navigation constellation has been studied in detail in Reference [1], and it points that joint autonomous navigation can suppress the rotational drift of the near-Earth constellation

Summary

Introduction

Autonomous orbit determination (AOD) of a navigation satellite system can effectively enhance the operational safety of the navigation system, which has attracted the attention of many scholars. The pulse control makes the system state discontinuous Those bring great challenges for precise orbit determination of a maneuvered GEO. The neural network has an excellent ability of self-learning and self-adaption [6] It can be used in the AOD of a maneuvered GEO. The low thrusters have been successfully applied in reality such as pulsed plasma thrusters (PPT) Their working characteristics are as follows: The thrust force is small; control (digital and autonomous control) is convenient and flexible. The observation residual will be applied to the weight update law of the neural network, and the observer can be well fitted to the perturbation term which is difficult to model (naturally, it includes the execution error of the controller).

Program Overview of GEO Satellite Autonomous Operation

System Equations for a Maneuvered Satellite

Design of Observer and Controller Based on Neural Networks

System Stability Proof Based on Lyapunov Method

Simulation and Analysis

Conclusions