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To improve the dynamical property and decoupling capability for a class of spacecraft system with strong coupling, a
neuron-network controller based on online tracing identification is established to meet the decoupling requirements of
multivariable system. The model with new structure and learning algorithm has significance for weight matrices and
makes training process of weights become more distinct and straightforward. The new neural network is then applied to
identification of nonlinear dynamics system, which the speed of learning and convergence is improved greatly for using
the priori input-output state knowledge. The results of simulation show that the neuron network decoupling controller
based on online tracing identification can effectively reduce the identification errors caused by the different sampling
data, and improve prominently the precision and the reliability of neural network in the system identification. The
controller has powerful self-learning and self-adaptive decouple capabilities.
Jianling Zhang andJinwen An
"Spacecraft's automatic landing control based on online tracing
identification method of neural network", Proc. SPIE 6795, Second International Conference on Space Information Technology, 67954Z (10 November 2007); https://doi.org/10.1117/12.775005
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Jianling Zhang, Jinwen An, "Spacecraft's automatic landing control based on online tracing identification method of neural network," Proc. SPIE 6795, Second International Conference on Space Information Technology, 67954Z (10 November 2007); https://doi.org/10.1117/12.775005