References
Xu B, Gao D X, Wang S X. Adaptive neural control based on HGO for hypersonic flight vehicles. Sci China Inf Sci, 2011, 54: 511–520
Wang D, Mu C X. Developing nonlinear adaptive optimal regulators through an improved neural learning mechanism. Sci China Inf Sci, 2017, 60: 058201
Zargarzadeh H, Dierks T, Jagannathan S. Optimal control of nonlinear continuous-time systems in strictfeedback form. IEEE Trans Neural Netw Learn Syst, 2015, 26: 2535–2549
Yang X, Liu D R, Wei Q L, et al. Guaranteed cost neural tracking control for a class of uncertain nonlinear systems using adaptive dynamic programming. Neurocomputing, 2016, 198: 80–90
Chen W H, Yang J, Guo L, et al. Disturbanceobserver-based control and related methods-an overview. IEEE Trans Ind Electron, 2016, 63: 1083–1095
Zhao Z H, Yang J, Liu C J, et al. Nonlinear composite bilateral control framework for n-DOF teleoperation systems with disturbances. Sci China Inf Sci, 2018, 61: 070221
Nodland D, Zargarzadeh H, Jagannathan S. Neural network-based optimal adaptive output feedback control of a helicopter UAV. IEEE Trans Neural Netw Learn Syst, 2013, 24: 1061–1073
Acknowledgements
This work was supported by Aeronautical Science Foundation of China (Grant No. 20165752049) and Natural Science Foundation of Jiangsu Province (Grant No. BK20171417).
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Xia, R., Wu, Q. & Chen, M. Disturbance observer-based optimal longitudinal trajectory control of near space vehicle. Sci. China Inf. Sci. 62, 50212 (2019). https://doi.org/10.1007/s11432-018-9683-y
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DOI: https://doi.org/10.1007/s11432-018-9683-y