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

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.

Real geo‐time‐based secured access computation model for e‐Health systems

“…To address the issues of scalability and performance, especially priorities, dynamic location, and the time‐based situation (i.e., a situation like COVID‐19) in the AC model, we put forward the idea of integration of the LBAC model with ARBAC 27‐37 model along with the priority attribute. The real challenge is to understand the mapping between every component and incorporate priority, location, and time attributes in the model to improve performance 23,38‐44 . We provided multiple authentication facilities for high priority users to access resources and services in a short time.…”

“…The real challenge is to understand the mapping between every component and incorporate priority, location, and time attributes in the model to improve performance. 23,[38][39][40][41][42][43][44] We provided multiple authentication facilities for high priority users to access resources and services in a short time. We represented underlying architecture with a proper explanation of the proposed system using a novel algorithm.…”

Autonomous Phase Control Combining EKF and Adaptive Neural Network for Remote Sensing Satellites

“…A thrusters-based attitude control method has been proposed for autonomous orbit control by Sato et al [23], employing a low-thrust, 4nozzle propulsion system and a pre-calculated thruster selection table for optimizing thrust and torque to achieve effective orbit control and maintain high-precision attitude stability for a long time. Gao et al [24] combined autonomous orbit determination with autonomous control to present an integrated design method in which the neural network state observer has been designed to estimate the inter-satellite ranging information, and the controller has been constructed autonomously by another neural network based on the estimated state and the predefined correction trajectory. Bock and Tajmar [25] adopted a self-developed electric propulsion system to realize orbit and two-axis attitude control.…”

Performance Assessment of a Turn Around Ranging in Communication Satellite Orbit Determination

“…Satellite laser ranging system uses laser light for range measurement [5]. Precise orbit determination of GEO satellites during orbit Maneuvering [6], autonomous orbit determination and orbit control for GEO satellite-based on a neural network [7], orbit determination of geostationary satellite during maneuver [8], sequential orbit determination for geostationary satellites operations [9] are most utilized orbit determination methods.…”