Adaptive Neural Network Control of a Flapping Wing Micro Aerial Vehicle With Disturbance Observer
By Wei He, Zichen Yan, Changyin Sun, Yunan Chen. IEEE Transactions on Cybernetics, 2017
296 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computational Theory and Mathematics, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/abc3dd46d6733b45caf1ad623a8f3382e9647553
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In Aerospace Engineering
In Computational Theory and Mathematics
In Control and Systems Engineering
Citations in the corpus
- Adaptive Neural Network Tracking Control for Robotic Manipulators With Dead Zone (2019, methodology): “Therefore, many methods have been studied [49]–[53] to remove these obstacles.”
- Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence (2018, methodology): “A S ONE of the most promising techniques, robotics have been extensively studied by industrial and academic communities in recent years [1]–[5], while automated robots have been widely allocated in the modern manufacturing and factories, e.”
- Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay (2019, background): “Recently, a significant breakthrough was made in control system design by using the adaptive technique for the flapping-wing flying robot [6].”
- Theory and Experiment on Formation-Containment Control of Multiple Multirotor Unmanned Aerial Vehicle Systems (2019, background): “COOPERATIVE control of multiple unmanned aerial vehicle (UAV) systems has been a hot research topic in recent years due to its broad potential applications in many practical areas, such as source seeking [1], [2], load transportation [3], localization [4], drag reduction [5], surveillance [6], [7], ”