2022
DOI: 10.1016/j.ast.2022.107572
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Neural network disturbance observer with extended weight matrix for spacecraft disturbance attenuation

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Cited by 11 publications
(4 citation statements)
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“…As shown in Figure 5, there are three layers of an RBF neural network. If the hidden layer includes enough neurons, the RBF can approximate any continuous function with an arbitrary accuracy and is a neural network with good local nonlinear approximation [46].…”
Section: Rbf Neural Network Disturbance Estimator Designmentioning
confidence: 99%
“…As shown in Figure 5, there are three layers of an RBF neural network. If the hidden layer includes enough neurons, the RBF can approximate any continuous function with an arbitrary accuracy and is a neural network with good local nonlinear approximation [46].…”
Section: Rbf Neural Network Disturbance Estimator Designmentioning
confidence: 99%
“…Currently, two main approaches address the impact of disturbances on spacecraft attitude control [7][8][9][10]. The first one compensates for disturbance torques through precise modeling or establishing observers.…”
Section: Introductionmentioning
confidence: 99%
“…Currently, two main approaches address the impact of disturbances on spacecraft attitude control [7][8][9][10]. The first one compensates for disturbance torques through precise modeling or by establishing observers.…”
Section: Introductionmentioning
confidence: 99%