Neural networks approximation for sub-optimal gains of a nonlinear satellite attitude controller

2021 ◽  
Author(s):  
Salman Ali Thepdawala
Keyword(s):  
Neural Networks ◽  
Satellite Attitude ◽  
Optimal Gains ◽  
Attitude Controller

scholarly journals An implementation of optimal control methods (LQI, LQG, LTR) for geostationary satellite attitude control

2019 ◽  
Vol 9 (6) ◽  
pp. 4728
Author(s):  
Farid Djaballah ◽  
M. A. Si Mohammed ◽  
Nabil Boughanmi
Keyword(s):  
Numerical Simulation ◽  
Dynamic Model ◽  
Attitude Control ◽  
Geostationary Satellite ◽  
Attitude Motion ◽  
Linear Quadratic ◽  
Integer Order ◽  
Satellite Attitude ◽  
Satellite Attitude Control ◽  
Attitude Controller

<p>This paper investigates a new strategy for geostationary satellite attitude control using<strong> </strong>Linear Quadratic Gaussian (LQG), Loop Transfer Recovery (LTR), and Linear Quadratic Integral (LQI) control techniques. The sub-system satellite attitude determination and control of a geostationary satellite in the presence of external disturbances, the dynamic model of sub-satellite motion is firstly established by Euler equations. During the flight mission at 35000 Km attitude, the stability characteristics of attitude motion are analyzed with a large margin error of pointing, then a height performance-order LQI, LQG and LTR attitude controller are proposed to achieve stable control of the sub-satellite attitude, which dynamic model is linearized by using feedback linearization method.<strong> </strong>Finally, validity of the LTR order controller and the advantages over an integer order controller are examined by numerical simulation. Comparing with the corresponding integer order controller (LQI, LQG), numerical simulation results indicate that the proposed sub-satellite attitude controller based on LTR order can not only stabilize the sub-satellite attitude, but also respond faster with smaller overshoot.</p><p> </p>

Developments of attitude determination and control system of microsats: A survey

2020 ◽  
pp. 095965181989517
Author(s):  
Liang He ◽  
Wenjie Ma ◽  
Pengyu Guo ◽  
Tao Sheng
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Deep Neural Networks ◽  
Attitude Determination ◽  
Alignment Error ◽  
Control Methods ◽  
Satellite Attitude ◽  
Determination Methods ◽  
And Control

This study surveys the developments in satellite attitude determination and control system, especially for microsats. This survey is not intended to be complete but is limited to the most significant developments of sensors, actuators, and algorithms in the last two decades. First, attitude determination methods including algorithms and sensors together with actuator-based control methods are introduced. Furthermore, current problems in alignment error, flexible satellites, and low redundancy of microsats attitude determination and control system are discussed. Moreover, developments of some deep-neural-networks-based methods, which have great potential in solving current problems, are summarized.

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