Adaptive neural network control of second-order underactuated systems with prescribed performance constraints
Author:
Affiliation:
1. College of Electrical and Information Engineering , Hunan University , Hunan 410082 , China
2. College of Computer Science and Electronic Engineering , Hunan University , Changsha , 410082 , China
Abstract
Publisher
Walter de Gruyter GmbH
Subject
Applied Mathematics,General Physics and Astronomy,Mechanics of Materials,Engineering (miscellaneous),Modeling and Simulation,Computational Mechanics,Statistical and Nonlinear Physics
Link
https://www.degruyter.com/document/doi/10.1515/ijnsns-2020-0141/pdf
Reference44 articles.
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2. X. Wu, K. Xu, M. Ma, et al.., “Output feedback control for an underactuated benchmark system with bounded torques,” Asian J. Control, 2020. https://doi.org/10.1002/asjc.2295.
3. Y. Zeng, J. Xu, and R. Zhang, “Energy minimization for wireless communication with rotary-wing UAV,” IEEE Trans. Wireless Commun., vol. 18, no. 4, pp. 2329–2345, 2019. https://doi.org/10.1109/twc.2019.2902559.
4. Y. Song, L. He, D. Zhang, et al.., “Neuroadaptive fault-tolerant control of quadrotor UAVs: a more affordable solution,” IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 7, pp. 1975–1983, 2018. https://doi.org/10.1109/TNNLS.2018.2876130.
5. Z. Zhou, H. Wang, Z. Hu, et al.., “Distributed event-triggered consensus for multiple underactuated systems under Markovian switching topologies,” Asian J. Contr., vol. 22, no. 1, pp. 590–599, 2020. https://doi.org/10.1002/asjc.1864.
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