A Sparse Neural Network-Based Control Method for Saturated Nonlinear Affine Systems

A Sparse Neural Network-Based Control Method for Saturated Nonlinear Affine Systems

Saturated nonlinear affine systems are widely encountered in many engineering fields. Currently, most control methods on saturated nonlinear affine systems are not specifically designed based on sparsity-based control methodologies, and they might require sparse identification at the beginning stage...

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Veröffentlicht in:Actuators 2024-06, Vol.13 (6), p.204
Hauptverfasser: Zhang, Jing, Yin, Baoqun, Huo, Jianwen, Guo, Hongliang, Li, Zhan
Format: Artikel
Sprache:eng
Schlagworte:
Basic converters
Control methods
Control systems
Controllers
Methods
Neural networks
nonlinear affine system
Nonlinear control
Nonlinear systems
Optimization
redundant manipulator
Robot control
Robots
saturation system
sparse neural network
Sparsity
Tracking control
Trajectory control
Wind power
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Beschreibung
Zusammenfassung:Saturated nonlinear affine systems are widely encountered in many engineering fields. Currently, most control methods on saturated nonlinear affine systems are not specifically designed based on sparsity-based control methodologies, and they might require sparse identification at the beginning stage and applying tracking control afterwards. In this paper, a sparse neural network (SNN)-based control method from an lp-norm (1≤p
ISSN:2076-0825
2076-0825
DOI:10.3390/act13060204