Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial Vehicles
This brief addresses the position and attitude tracking fixed-time practical control for quadrotor unmanned aerial vehicles (UAVs) subject to nonlinear dynamics. First, by combining the radial basis function neural networks (NNs) with virtual parameter estimating algorithms, a NN adaptive control sc...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/8828453 |
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| _version_ | 1832555103325782016 |
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| author | Jianhua Zhang Yang Li Wenbo Fei |
| author_facet | Jianhua Zhang Yang Li Wenbo Fei |
| author_sort | Jianhua Zhang |
| collection | DOAJ |
| description | This brief addresses the position and attitude tracking fixed-time practical control for quadrotor unmanned aerial vehicles (UAVs) subject to nonlinear dynamics. First, by combining the radial basis function neural networks (NNs) with virtual parameter estimating algorithms, a NN adaptive control scheme is developed for UAVs. Then, a fixed-time adaptive law is proposed for neural networks to achieve fixed-time stability, and convergence time is dependent only on control gain parameters. Based on Lyapunov analyses and fixed-time stability theory, it is proved that the fixed-time adaptive neural network control is finite-time stable and convergence time is dependent with control parameters without initial conditions. The effectiveness of the NN fixed-time control is given through a simulation of the UAV system. |
| format | Article |
| id | doaj-art-3e5d64e494e747c0b76c331190ac3fdd |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-3e5d64e494e747c0b76c331190ac3fdd2025-02-03T05:49:34ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/88284538828453Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial VehiclesJianhua Zhang0Yang Li1Wenbo Fei2School of Information and Control Engineering, Qingdao University of Technology, Qingdao, Shandong 266525, ChinaSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao, Shandong 266525, ChinaHebei University of Science and Technology, Shijiazhuang, Hebei 050018, ChinaThis brief addresses the position and attitude tracking fixed-time practical control for quadrotor unmanned aerial vehicles (UAVs) subject to nonlinear dynamics. First, by combining the radial basis function neural networks (NNs) with virtual parameter estimating algorithms, a NN adaptive control scheme is developed for UAVs. Then, a fixed-time adaptive law is proposed for neural networks to achieve fixed-time stability, and convergence time is dependent only on control gain parameters. Based on Lyapunov analyses and fixed-time stability theory, it is proved that the fixed-time adaptive neural network control is finite-time stable and convergence time is dependent with control parameters without initial conditions. The effectiveness of the NN fixed-time control is given through a simulation of the UAV system.http://dx.doi.org/10.1155/2020/8828453 |
| spellingShingle | Jianhua Zhang Yang Li Wenbo Fei Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial Vehicles Complexity |
| title | Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial Vehicles |
| title_full | Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial Vehicles |
| title_fullStr | Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial Vehicles |
| title_full_unstemmed | Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial Vehicles |
| title_short | Neural Network-Based Nonlinear Fixed-Time Adaptive Practical Tracking Control for Quadrotor Unmanned Aerial Vehicles |
| title_sort | neural network based nonlinear fixed time adaptive practical tracking control for quadrotor unmanned aerial vehicles |
| url | http://dx.doi.org/10.1155/2020/8828453 |
| work_keys_str_mv | AT jianhuazhang neuralnetworkbasednonlinearfixedtimeadaptivepracticaltrackingcontrolforquadrotorunmannedaerialvehicles AT yangli neuralnetworkbasednonlinearfixedtimeadaptivepracticaltrackingcontrolforquadrotorunmannedaerialvehicles AT wenbofei neuralnetworkbasednonlinearfixedtimeadaptivepracticaltrackingcontrolforquadrotorunmannedaerialvehicles |