Neural Network Based Adaptive Consensus of Multi-quadrotor System
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-3998-3_157
Reference20 articles.
1. Pratama, B., Muis, A., Subiantoro, A.: Improved distributed formation control and trajectory tracking of multi quadrotor in leader-follower formation. In: 2019 5th International Conference on New Media Studies (CONMEDIA), pp. 129–134 (2019). https://doi.org/10.1109/CONMEDIA46929.2019.8981827
2. Wang, Y., Sun, J., Wang, Q., Dong, L.: Distributed formation control for multi-quadrotor system. In: Chinese Control Conference (CCC) 2019, pp. 6076–6081 (2019). https://doi.org/10.23919/ChiCC.2019.8865180
3. Shen, D., Lu, Q., Xie, X., Wang, J., Ni, H.: Layered formation control for multi-quadrotors. In: IEEE International Conference on Real-time Computing and Robotics (RCAR) 2019, pp. 638–643 (2019). https://doi.org/10.1109/RCAR47638.2019.9044101
4. Abbasi, E., Ghayour, M., Danesh, M., Amiri, P., Yoosefian, M.H.: Formation flight control and path tracking of a multi-quadrotor system in the presence of measurement noise and disturbances. In: 2018 6th RSI International Conference on Robotics and Mechatronics (IcRoM), pp. 273–279 (2018). https://doi.org/10.1109/ICRoM.2018.8657620
5. Shen, D., Lu, Q.: Hierarchical formation control with applications to multi-quadrotor systems. IEEE Access 7, 130599–130609 (2019). https://doi.org/10.1109/ACCESS.2019.2934746
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