Observer-based adaptive finite-time prescribed performance NN control for nonstrict-feedback nonlinear systems
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-07123-6.pdf
Reference49 articles.
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2. Yang Y, Peng JCH, Ye C, Ye Z, Ding Y (2021) A criterion and stochastic unit commitment towards frequency resilience of power systems. IEEE Trans Power Syst. https://doi.org/10.1109/TPWRS.2021.3095180
3. Liu H, Pan Y, Cao J, Wang H, Zhou Y (2020) Adaptive neural network backstepping control of fractional-order nonlinear systems with actuator faults. IEEE Trans Neural Netw Learn Syst 31(12):5166–5177
4. Wen G, Chen CP, Ge SS (2020) Simplified optimized backstepping control for a class of nonlinear strict-feedback systems with unknown dynamic functions. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2020.3002108
5. Tymoshchuk P (2019) A neural circuit model of adaptive robust tracking control for continuous-time nonlinear systems. In: International Conference on Artificial Neural Networks, pp: 819–835. Springer
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