Neural-Network-Based Adaptive Finite-Time Output Feedback Control for Spacecraft Attitude Tracking

This brief is concerned with neural network (NN)-based adaptive finite-time output feedback attitude tracking control for rigid spacecraft in the presence of actuator saturation, inertial uncertainty, and external disturbance. First, a neural state observer is designed to estimate the unknown state....

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems Vol. 34; no. 10; pp. 8116 - 8123
Main Authors: Zhao, Lin, Yu, Jinpeng, Chen, Xinkai
Format: Journal Article
Language:English
Published: United States IEEE 01.10.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Actuators
Adaptive control
Adaptive neural control
Algorithms
Artificial neural networks
Attitude control
Attitude stability
attitude tracking control
Backstepping
Closed loops
Feedback
Feedback control
finite-time convergence
Neural networks
Observers
Output feedback
Space vehicles
Spacecraft
Spacecraft attitude control
Spacecraft tracking
State observers
Tracking control
Tracking errors
Uncertainty
ISSN:2162-237X, 2162-2388, 2162-2388
Online Access:Get full text
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Summary:This brief is concerned with neural network (NN)-based adaptive finite-time output feedback attitude tracking control for rigid spacecraft in the presence of actuator saturation, inertial uncertainty, and external disturbance. First, a neural state observer is designed to estimate the unknown state. Then, based on the estimated state, the adaptive neural finite-time command filtered backstepping (CFB) is applied to construct virtual control signal and controller with updating law. The finite-time command filter is given to avoid the computation complexity problem in traditional backstepping, and the compensation signals based on fractional power are constructed to remove filtering errors. Using Lyapunov stability theory, we show that the attitude tracking error (TE) can converge into the desired neighborhood of the origin in finite time and all the signals in the closed-loop system are bounded in finite time although input saturation exists. The numerical simulations are used to show the effectiveness of the given algorithm.
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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2022.3144493