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Sliding Mode and Neuro Networks Control of Flexible Satellite Attitude Maneuvering

Author: CaoYing
Tutor: WangYan
School: Harbin Institute of Technology
Course: Control Science and Engineering
Keywords: Flexible Satellite Maneuver Cerebellum of network Sliding Mode Control
CLC: V448.22
Type: Master's thesis
Year: 2010
Downloads: 66
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Abstract


Satellite attitude control system is a the uncertain nonlinear coupling system . These uncertainties exist so flexible satellite large angle attitude maneuver control problem is further complicated by model parameter uncertainty and the impact of various interference torque satellites in orbit . Therefore, in order to complete the attitude control task , the need to design the control law has the higher robustness . The article is in this context , from both theoretical and applied aspects of satellite attitude control system control algorithms in-depth study . Mainly to complete the work of the following aspects : First , the sliding mode control has many advantages , such as robustness , small amount of calculation , real-time response speed . Therefore , using the sliding mode control method to control the flexible satellite attitude saturation function instead of the symbolic function to eliminate chattering . Secondly, the flexible spacecraft control , sliding mode variable structure neural network compensation uncertainty , improve system robustness . Traditional brain network to approximate the uncertainty , this network is not prone to the phenomenon of local minima . Poor generalization ability of traditional small brain network real-time are not good enough shortcomings Gaussian basis functions brain networks , the use of Gaussian basis functions instead of the traditional small brain network to quantify the 0 or 1 . Computationally intensive for Gaussian basis functions brain network , application is inconvenient, fast learning algorithm based hypercube subspace , which greatly improves the learning speed of the network . Above the network needs to know the input range , so that the application of the network under certain restrictions , self-organizing network do not need to know the input range , nodes and weights can be automatically updated based on the input value of the small brain . This flexible satellite attitude control system parameters change through design to meet the accuracy requirements .

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CLC: > Aviation, aerospace > Aerospace ( Astronauts ) > Space instrument,spacecraft devices,spacecraft guidance and control > Guidance and Control > Spacecraft guidance and control > Attitude Control System
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