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Král Ladislav and Šimandl Miroslav : Neural Network Based Bicriterial Dual Control with Multiple Linearization . IFAC-PapersOnline, vol. 10, p. 1-6, 2010.


A suboptimal dual controller for discrete nonlinear stochastic systems based on the bicriterial approach is proposed and discussed. Two individual criteria are designed and used to introduce one of the conflicting efforts between estimation and control; caution and probing. A nonlinear system is modeled using a neural network (NN) of perceptron type. The unknown parameters of the network are estimated by a global estimation method, the Gaussian sum method (GSM), which allows to determine conditional probability density function (pdf) of the NNs parameters. The GSM in association with an idea of multiple linearization is chosen and utilized in the bicriterial dual control (BDC) approach. The probing component of the control law is determined for each local mode of estimated pdf separately and respects accuracy of each local estimate inherent in the estimated pdf. A comparison of the proposed modified BDC and the BDC which uses a global point estimate only is shown in a numerical example.

Detail of publication

Title: Neural Network Based Bicriterial Dual Control with Multiple Linearization
Author: Král Ladislav ; Šimandl Miroslav
Language: English
Year: 2010
Type of publication: Papers in journals
Title of journal or book: IFAC-PapersOnline
Číslo vydání: 10
Page: 1 - 6
ISSN: 1474-6670
2011-03-15 16:21:56 / 2011-03-15 16:21:56 / 1


Neural Networks, Intelligent Control, Adaptive Control, Stochastic Systems, Parameter Estimation, Nonlinear Filtering


 author = {Kr\'{a}l Ladislav and \v{S}imandl Miroslav},
 title = {Neural Network Based Bicriterial Dual Control with Multiple Linearization},
 year = {2010},
 journal = {IFAC-PapersOnline},
 volume = {10},
 pages = {1-6},
 ISSN = {1474-6670},
 url = {},