References
- E. Ott, C. Grebogi, J.A. Yorke, ‘Controlling chaos’, Phys. Rev. Lett. 1990, 64, 1196–1199, DOI: 10.1103/PhysRevLett.64.1196.
- Y. Tang, J. Kurths, W. Lin, E. Ott, and L. Kocarev, ‘Introduction to Focus Issue: When machine learning meets complex systems: Networks, chaos, and nonlinear dynamics’, Chaos 2020, 30 (6), 063151, DOI: 10.1063/5.0016505.
- H. Jaeger and H. Haas, ‘Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication’, Science 2004, 304 (5667), 78–80, DOI: 10.1126/science.109127.
- Y. LeCun, Y. Bengio, and G. Hinton, ‘Deep learning’, Nature 2015, 521, 436–444. https://doi.org/10.1038/nature14539.
- A.A. Ferreira, T.B. Ludermir, and R.R.B. De Aquino, ‘An approach to reservoir computing design and training’, Expert Syst. Appl. 2013, 40(10), 4172-4182, DOI: 10.1016/j.eswa.2013.01.029.
- G. Boffetta, M. Cencini, M. Falcioni, and A. Vulpiani, ‘Predictability: A way to characterize complexity’, Phys. Rep. 2002, 356, 367–474, DOI: 10.1016/S0370-1573(01)00025-4.
- S.D. Lee, B.D.H. Phuc, X. Xu, and S.S. You, ‘Roll suppression of marine vessels using adaptive super-twisting sliding mode control synthesis’, Ocean. Eng. 2020, 195, 106724, DOI: 10.1016/j.oceaneng.2019.106724.
- A.A. Pyrkin, A.A. Bobtsov, S.A. Kolyubin and A.A. Vedyakov, ‘Precise frequency estimator for noised periodical signals’, 2012 IEEE International Conference on Control Applications. 2012, 92-97, DOI: 10.1109/CCA.2012.6402392.
- N. Jing, Y. Juan, W. Jing and G. Yu, ‘Adaptive parameter identification of sinusoidal signals’, 2013 IFAC Conference on Intelligent Control and Automation Science ICONS, 2013, 624-629, DOI: 10.3182/20130902-3-CN-3020.00096.
- M. Hou, ‘Parameter identification of sinusoids’, IEEE Transactions on Automatic Control. 2012, 57(2), 467–472, DOI: 10.1109/TAC.2011.2164736.
- J. Na, J. Yang, X. Wu, and Y. Guo, ‘Robust adaptive parameter estimation of sinusoidal signals’, Automatica. 2015, 53, 376-384, DOI:10.1016/j.automatica.2015.01.019.
- V. Adetola and M. Guay, ‘Performance Improvement in Adaptive Control of Linearly Parameterized Nonlinear Systems’, IEEE Transactions on Automatic Control. 2010, 55(9), 2182-2186, DOI: 10.1109/TAC.2010.2052149.
- S.D. Lee, Y.S. Song, D.H. Kim, and M.R. Kang, ‘Path following control of an underactuated catamaran for recovery maneuvers’, Sensors. 2022, 22, 2233, doi.org/10.3390/s22062233.
- A.A. Pyrkin, ‘Adaptive algorithm to compensate parametrically uncertain biased disturbance of a linear plant with delay in the control channel’, Autom Remote Control. 2010, 71, 1562–1577.
- M. Lukoševičius, ‘A Practical Guide to Applying Echo State Networks. In: Montavon, G., Orr, G.B., Müller, KR. (eds) Neural Networks: Tricks of the Trade. Lecture Notes in Computer Science’, 2012, vol 7700. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35289-8_36.
- S.D. Lee, S.S. You, X. Xu, and T.N. Cuong, ‘Active control synthesis of nonlinear pitch-roll motions for marine vessels’. Ocean Eng. 2021, 221, 108537, DOI: 10.1016/j.oceaneng.2020.108537.
- S. Lynch, ‘Poincaré Maps and Nonautonomous Systems in the Plane. In: Dynamical Systems with Applications using MATLAB®’, 2014, Birkhäuser, Cham, DOI: 10.1007/978-3-319-06820-6_15.
- E. Ott, ‘Chaos in Dynamical Systems (2nd ed.)’, Cambridge: Cambridge University Press. 2002. DOI: 10.1017/CBO9780511803260.
- S. Lynch, ‘Electromagnetic Waves and Optical Resonators. In: Dynamical Systems with Applications using MATLAB®’, 2014, Birkhäuser, Cham, DOI: 10.1007/978-3-319-06820-6_5.
- K.K. Dey and G.A. Sekh, ‘Effects of Random Excitations on the Dynamical Response of Duffing Systems’, J Stat Phys. 2021, 182, 18, DOI: 10.1007/s10955-020-02694-x.
- B.S. Ahmed, ‘A practical test for noisy chaotic dynamics’, SoftwareX. 2015, 3–4, 1-5, DOI: 10.1016/j.softx.2015.08.002.
- J.J. Bramburger and J. Nathan Kutz, ‘Poincaré maps for multiscale physics discovery and nonlinear Floquet theory’, Physica D: Nonlinear Phenomena. 2020, 408,132479, DOI: 10.1016/j.physd.2020.132479.