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Cited by 38 publications
(9 citation statements)
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“…The existence of these factors makes it challenging to design an autonomous attitude controller, which is required to ensure a fast convergence rate of the tracking errors and satisfactory flight performance of the controlled spacecraft. To handle the uncertainties existing in the system dynamics, some function approximators including neural networks (NNs) and fuzzy logic systems (FLSs) are usually involved in the adaptive controllers design (see [13][14][15][16][17][18][19][20], and references therein). In [19], a Chebyshev neural network-based finite-time control scheme was developed by constructing a terminal sliding mode surface, such that the uniform ultimate boundedness (UUB) of attitude tracking errors was guaranteed.…”
Section: Introductionmentioning
confidence: 99%
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“…The existence of these factors makes it challenging to design an autonomous attitude controller, which is required to ensure a fast convergence rate of the tracking errors and satisfactory flight performance of the controlled spacecraft. To handle the uncertainties existing in the system dynamics, some function approximators including neural networks (NNs) and fuzzy logic systems (FLSs) are usually involved in the adaptive controllers design (see [13][14][15][16][17][18][19][20], and references therein). In [19], a Chebyshev neural network-based finite-time control scheme was developed by constructing a terminal sliding mode surface, such that the uniform ultimate boundedness (UUB) of attitude tracking errors was guaranteed.…”
Section: Introductionmentioning
confidence: 99%
“…In [20], a fast nonsingular terminal sliding mode control law was designed for rigid spacecraft, and the lumped system uncertainty including unknown inertia matrix and thrusters faults was approximated by the FLSs. Nevertheless, those approximation-based control approaches in literatures [13][14][15][16][17][18][19][20] may impose demanding computational burden due to their complicated structures in the implementation.…”
Section: Introductionmentioning
confidence: 99%
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“…In recent years, intelligent algorithms are designed and analyzed in many domains such as the attitude tracking and control of uncertain rigid spacecraft [6][7][8], the control of wind energy conversion systems [9,10], and the analysis and design of high step-down converters [11]. With the rapid progress of artificial intelligence, more and more researchers use machine learning techniques for stock market forecast.…”
Section: Introductionmentioning
confidence: 99%
“…At present, an enormous number of advanced control algorithms for the trajectory tracking problem of mobile robots have been proposed, such as neural network control, 5,6 fuzzy control, 7,8 sliding mode control, 9 backstepping control, 10 and adaptive control. 11 Zou et al 12 analyzed the dynamic modeling and movement control of tracked vehicles undergoing skid-steering on horizontal.…”
Section: Introductionmentioning
confidence: 99%