Broad-RBFNN-Based Intelligence Adaptive Antidisturbance Formation Control for a Class of Cluster Aerospace Unmanned Systems with Multiple High-Dynamic Uncertainties
This paper investigates the antidisturbance formation control problem for a class of cluster aerospace unmanned systems (CAUSs) suffering from multisource high-dynamic uncertainties. Firstly, to estimate and compensate the uncertainties existing in CAUS coordinate dynamics, an adaptive antidisturban...
Saved in:
| Main Authors: | Erxin Gao, Xin Ning, Zheng Wang, Xiaokui Yue |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/6634175 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Discrete-Time Algorithm for Stiffness Extraction from sEMG and Its Application in Antidisturbance Teleoperation
by: Peidong Liang, et al.
Published: (2016-01-01) -
GWO-RBFNN Dual-parameter Collaborative Intelligent Optimal Control of Chaotic Motion of a Class of Permanent Magnet Synchronous Motor
by: LI Ningzhou, et al.
Published: (2024-06-01) -
Uncertainty and Sensitivity in the Development Lifecycle of Advanced Aerospace Systems
by: Timothy L. Eddy, et al.
Published: (2025-01-01) -
Obstacle avoidance control for cluster-based unmanned aerial vehicle formation with multiple constraints
by: Wenjie Zhou, et al.
Published: (2025-06-01) -
An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis
by: Syed Saad Azhar Ali, et al.
Published: (2014-01-01)