Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Guo Xing Wen"'
Publikováno v:
In Water Science and Engineering April 2014 7(2):133-142
Akademický článek
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Autor:
Jun Feng, Guo-Xing Wen
Publikováno v:
Neurocomputing. 151:288-295
This paper proposes a novel robust adaptive consensus tracking control approach for a class of nonlinear multi-agent systems with modeling uncertainties and external disturbances. Radial Basis Function Neural Networks (RBFNNs) are used to approximate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::659bc8865d9ec72499e1431ee47a4c4a
https://doi.org/10.1016/j.neucom.2014.09.037
https://doi.org/10.1016/j.neucom.2014.09.037
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 25:1217-1226
Because of the complicity of consensus control of nonlinear multiagent systems in state time-delay, most of previous works focused only on linear systems with input time-delay. An adaptive neural network (NN) consensus control method for a class of n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff8d8bb270221a2b713a4128aab63763
https://doi.org/10.1109/tnnls.2014.2302477
https://doi.org/10.1109/tnnls.2014.2302477
Publikováno v:
IEEE Transactions on Cybernetics. 44:583-593
This paper studies an adaptive tracking control for a class of nonlinear stochastic systems with unknown functions. The considered systems are in the nonaffine pure-feedback form, and it is the first to control this class of systems with stochastic d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84b88d0d48e5b25d6b0390b24373d12c
https://doi.org/10.1109/tcyb.2013.2262935
https://doi.org/10.1109/tcyb.2013.2262935
Akademický článek
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Akademický článek
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Autor:
Guo-Xing Wen, Yan-Jun Liu
Publikováno v:
Nonlinear Dynamics. 66:745-753
In this paper, an adaptive fuzzy-neural control scheme is investigated for a class of single-input single-output (SISO) discrete-time nonlinear systems in the presence of bounded disturbances. The SISO systems are in the form of the nonlinear autoreg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d1a6f954f2df68be8e570d226c6869f
https://doi.org/10.1007/s11071-011-9947-z
https://doi.org/10.1007/s11071-011-9947-z
Publikováno v:
Nonlinear Dynamics. 65:65-75
Based on the backstepping technique, an adaptive neural network (NN) based output feedback controller is proposed to achieve a desired tracking performance for a class of discrete-time nonlinear systems, which are represented in non-strict-feedback f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0b615355555704a0d15b6bfc8d62b18
https://doi.org/10.1007/s11071-010-9874-4
https://doi.org/10.1007/s11071-010-9874-4
Publikováno v:
Neurocomputing. 73:2498-2505
Based on the backstepping technique, a direct adaptive neural network control algorithm is proposed for a class of uncertain nonlinear discrete-time systems in the strict-feedback form. Neural networks are utilized to approximate unknown functions, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ae11cf5947a1b3661a3d31a09163862
https://doi.org/10.1016/j.neucom.2010.06.001
https://doi.org/10.1016/j.neucom.2010.06.001