References
K. S. Fu. Learning control systems: review and outlook. IEEE Transactions on Automatic Control, 1970, 15(3): 210–221.
K. J. Astrom, P. R. Kumar. Control: a perspective. Automatica, 2014, 50(1):3–43.
P. J. Antsaklis, A. Rahnama. Control and machine intelligence for system autonomy. Journal of Intelligent & Robotic Systems, 2018, 91(1): 23–34.
C. Wang, D. J. Hill. Learning form neural control. IEEE Transactions on Neural Networks, 2006, 17(1): 130–146.
C. Wang, D. J. Hill. Deterministic Learning Theory for Identification, Recognition and Control. Boca Raton: CRC Press, 2009.
T. Liu, C. Wang, D. J. Hill. Learning from neural control of nonlinear systems in normal form. Systems Control & Letters, 2009, 58(9): 633–638.
C. Wang, M. Wang, T. Liu, et al. Learning from ISS-modular adaptive NN control of nonlinear strict-feedback systems. IEEE Transactions on Neural Networks and Learning Systems, 2012, 23(10): 1539–1550.
M. Wang, C. Wang. Learning from adaptive neural dynamic surface control of strict-feedback systems. IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(6): 1247–1259.
S.-L. Dai, M. Wang, C. Wang, et al. Learning from adaptive neural network output feedback control of uncertain ocean surface ship dynamics. International Journal of Adaptive Control and Signal Processing, 2014, 28(3): 341–365.
S.-L. Dai, C. Wang, M. Wang. Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, 2014, 25(1): 111–123.
F. Yang, C. Wang. Pattern-based NN control of a class of uncertain nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(4): 1108–1119.
M. Wang, C. Wang, P. Shi, et al. Dynamic learning from neural control for strict-feedback systems with guaranteed predefined performance. IEEE Transactions on Neural Networks and Learning Systems, 2016, 27(12): 2564–2576.
M. Wang, A. Yang. Dynamic learning from adaptive neural control of robot manipulators with prescribed performance. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(8): 2244–2255.
S.-L. Dai, M. Wang, C. Wang. Neural learning control of marine surface vessels with guaranteed transient tracking performance. IEEE Transactions on Industrial Electronics, 2016, 63(3): 1717–1727.
S. He, M. Wang, S.-L. Dai, et al. Leader-follower formation control of USVs with prescribed performance and collision avoidance. IEEE Transactions on Industrial Informatics, 2019, 15(1): 572–581.
M. Wang, Y. Zhang, C. Wang. Learning from neural control for non-affine Systems with full state constraints using command filtering. International Journal of Control, 2018: DOI https://doi.org/10.1080/00207179.2018.1558285.
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Min WANG received the B.Sc. and M.Sc. degrees from Bohai University in 2003 and 2006, respectively, and the Ph.D. degree from Qingdao University in 2009. She was a visiting scholar with the Department of Computer Science, Brunel University London from 2017 to 2018. She is currently a professor with the School of Automation Science and Engineering, South China University of Technology, Guangzhou, China. She has authored or coauthored over 40 papers published in international journals. Her current research interests include intelligent control, dynamic learning, robot control, and event-triggered control.
Cong WANG received the B.E. and M.E. degrees from Beijing University of Aeronautic & Astronautics in 1989 and 1997, respectively, and the Ph.D. degree from the Department of Electrical & Computer Engineering, National University of Singapore in 2002. From 2001 to 2004, he did his postdoctoral research at the Department of Electronic Engineering, City University of Hong Kong. He is the co-author of the book “Deterministic Learning Theory for Identification, Recognition and Control” (CRC Press, 2009). His research interests include dynamical pattern recognition, pattern-based intelligent control, oscillation fault diagnosis, and early detection of myocardial ischemia.
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Wang, M., Wang, C. Recent advances on dynamic learning from adaptive NN control. Control Theory Technol. 18, 107–109 (2020). https://doi.org/10.1007/s11768-020-9292-1
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DOI: https://doi.org/10.1007/s11768-020-9292-1