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• W2007473161 abstract "This brief proposes a novel statistic information tracking control framework for complex stochastic processes with a dynamic neural network (DNN) identifier and multiple dead zone actuators. The new driven information for the tracking problem is a series of statistic information sets (SISs) of the stochastic output signal. By using an adaptive method to adjust the weight matrices and to compensate the unknown parameters, a new control input is built with the Nussbaum gain matrix and feedback control gain. It is shown that both the identification errors of DNNs and the closed-loop SIS tracking errors converge to zero. Finally, a numerical example is included to illustrate the effectiveness of the theoretical results." @default.
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• W2007473161 date "2013-11-01" @default.
• W2007473161 modified "2023-10-17" @default.
• W2007473161 title "Improved Results on Statistic Information Control With a Dynamic Neural Network Identifier" @default.
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• W2007473161 doi "https://doi.org/10.1109/tcsii.2013.2281693" @default.
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