267 Non linear attitude control law of a space plane application of hermes

A study is described that compares the performance of a self-organizing fuzzy logic control law (SOC) with that of the more traditional P + D algorithm. The multivariate problem used for the investigation is the attitude control of a flexible satellite that has significant dynamic coupling of the axes. It is demonstrated that the SOC can provide good control, requires limited process knowledge and compares favorably with the P + D algorithm.

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Nonlinear Hybrid Controller for a Quadrotor Based on Sliding Mode and Backstepping

IAES International Journal of Robotics and Automation (IJRA) ◽

10.11591/ijra.v4i3.pp209-218 ◽

2015 ◽

Vol 4 (3) ◽

pp. 209

Author(s):

Chuan Lian Zhang ◽

Kil To Chong

Keyword(s):

Attitude Control ◽

Position Control ◽

Sliding Mode ◽

Lyapunov Theory ◽

Control Law ◽

Dynamics Modeling ◽

Hybrid Controller ◽

Navigation Simulation ◽

Waypoint Navigation ◽

Nonlinear Hybrid

<span>In this paper, one nonlinear hybrid controller, based on backstepping and sliding mode, was developed and applied to a quadrotor for waypoint navigation application. After dynamics modeling, the whole quadrotor dynamics system could be divided into two subsystems: rotational system and translational system. Backstepping control law was derived for attitude control whereas sliding mode control law was developed for position control. By using Lyapunov theory and satisfying sliding stable rules, the convergence of system could be guaranteed. A nonlinear equation was proposed to solve the under-actuated problem. To validate the effectiveness of proposed nonlinear hybrid controller, waypoint navigation simulation was performed on the nonlinear hybrid controller. Results showed that the nonlinear hybrid controller finished waypoint navigation successfully.</span>

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Adaptive Backstepping Attitude Control Law with L2-Gain Performance for Flexible Spacecraft

International Journal of Aerospace Engineering ◽

10.1155/2019/6392175 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11

Author(s):

Rui-Qi Dong ◽

Yu-Yao Wu ◽

Ying Zhang ◽

Ai-Guo Wu

Keyword(s):

Attitude Control ◽

External Disturbance ◽

Performance Criterion ◽

Lyapunov Theory ◽

Flexible Spacecraft ◽

Control Law ◽

Adaptive Backstepping ◽

Unknown Parameters ◽

Inertia Matrix ◽

Attitude Maneuver

In this paper, an observer-based adaptive backstepping attitude maneuver controller (briefly, OBABC) for flexible spacecraft is presented. First, an observer is constructed to estimate the flexible modal variables. Based on the proposed observer, a backstepping control law is presented for the case where the inertia matrix is known. Further, an adaptive law is developed to estimate the unknown parameters of the inertia matrix of the flexible spacecraft. By utilizing Lyapunov theory, the proposed OBABC law can guarantee the asymptotical convergence of the closed-loop system in the presence of the external disturbance, incorporating with the L2-gain performance criterion constraint. Simulation results show that the attitude maneuver can be achieved by the proposed observer-based adaptive backstepping attitude control law.

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The Satellite Attitude Control Law Design Based on Machine Learning

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.519-520.741 ◽

2014 ◽

Vol 519-520 ◽

pp. 741-746 ◽

Cited By ~ 2

Author(s):

Guo Jiang Sun ◽

Jin Hui Li ◽

Shi Ming Chen ◽

Yun Feng Dong

Keyword(s):

Machine Learning ◽

Attitude Control ◽

Fitness Function ◽

Control Law ◽

Sensors And Actuators ◽

Control Laws ◽

Satellite Attitude ◽

Control Precision ◽

Attitude Error ◽

Satellite Attitude Control

Traditional optimization algorithms can only optimize parameters in control laws. Machine learning method can optimize parameters and evolve satellite attitude control law automatically under certain criterion. Single axis satellite attitude simulation system with noise was built up, which included satellite attitude dynamic model, sensors and actuators model. The control laws inputs were attitude error, attitude errors integral and angular velocity error, and outputs were actuators control instructions. Control laws fitness function was an attitude errors statistical function. With suitable function set selected for genetic programming (GP) and parse tree used to represent a control law expression, GP was used to evolve control law expression automatically. Simulation result shows that this method can evolve control law with uncertainties noise better. The evolved control law response and control precision are better than PID, and it can be used in satellite attitude control.

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Adaptive Neural Network-Based Satellite Attitude Control by Using the Dynamic Inversion Technique and a VSCMG Pyramidal Cluster

Complexity ◽

10.1155/2019/1645042 ◽

2019 ◽

Vol 2019 ◽

pp. 1-16 ◽

Cited By ~ 5

Author(s):

Mihai Lungu ◽

Romulus Lungu

Keyword(s):

Neural Network ◽

Attitude Control ◽

Approximation Error ◽

Inversion Method ◽

Dynamic Inversion ◽

Control Law ◽

Feed Forward Neural Network ◽

Small Satellites ◽

Control Moment ◽

Satellite Attitude Control

The paper presents an adaptive system for the control of small satellites’ attitude by using a pyramidal cluster of four variable-speed control moment gyros as actuators. Starting from the dynamic model of the pyramidal cluster, an adaptive control law is designed by means of the dynamic inversion method and a feed-forward neural network-based nonlinear subsystem; the control law has a proportional-integrator component (for the control of the reduced-order linear subsystem) and an adaptive component (for the compensation of the approximation error associated with the function describing the dynamics of the nonlinear system). The software implementation and validation of the new control architecture are achieved by using the Matlab/Simulink environment.

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