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• W2066811036 abstract "The article deals with a challenging problem of adaptive control design for multivariable stochastic systems with a functional uncertainty. Model of the system is based on multi-layered perceptron neural networks where both the unknown parameters and the structure are found in real time without a necessity of any off-line training process. The unknown parameters are estimated by a global estimation method, the Gaussian sum filter, and the structure of the neural network model is optimized by a proposed pruning method. The control law is based on a bicriterial approach to the suboptimal dual control. Two individual criteria are designed and used to introduce conflicting efforts between the estimation and control; probing and caution. A comparison of the proposed dual control and its alternative with an implementation of the pruning algorithm is shown in a numerical example. Copyright © 2011 John Wiley & Sons, Ltd." @default.
• W2066811036 created "2016-06-24" @default.
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• W2066811036 date "2011-05-03" @default.
• W2066811036 modified "2023-10-18" @default.
• W2066811036 title "Functional adaptive controller for multivariable stochastic systems with dynamic structure of neural network" @default.
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• W2066811036 doi "https://doi.org/10.1002/acs.1250" @default.
• W2066811036 hasPublicationYear "2011" @default.
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