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Adaptive control of cluster-based Web systems using neuro-fuzzy models

Krzysztof Zatwarnicki (2012)

International Journal of Applied Mathematics and Computer Science

A significant development of Web technologies requires the application of more and more complex systems and algorithms for maintaining high quality of Web services. Presently, not only simple decision-making tools but also complex adaptation algorithms using artificial intelligence techniques are applied for controlling HTTP request traffic. The paper presents a new LFNRD (Local Fuzzy-Neural Adaptive Request Distribution) algorithm for request distribution in cluster-based Web systems using neuro-fuzzy...

Adaptive control of discrete time Markov processes by the large deviations method

T. Duncan, B. Pasik-Duncan, Łukasz Stettner (2000)

Applicationes Mathematicae

Some discrete time controlled Markov processes in a locally compact metric space whose transition operators depend on an unknown parameter are described. The adaptive controls are constructed using the large deviations of empirical distributions which are uniform in the parameter that takes values in a compact set. The adaptive procedure uses a finite family of continuous, almost optimal controls. Using the large deviations property it is shown that an adaptive control which is a fixed almost optimal...

Adaptive control of uncertain nonholonomic systems in finite time

Jiankui Wang, Guoshan Zhang, Hongyi Li (2009)

Kybernetika

In this paper, the finite-time stabilization problem of chained form systems with parametric uncertainties is investigated. A novel switching control strategy is proposed for adaptive finite-time control design with the help of Lyapunov-based method and time-rescaling technique. With the proposed control law, the uncertain closed-loop system under consideration is finite-time stable within a given settling time. An illustrative example is also given to show the effectiveness of the proposed controller....

Adaptive control scheme based on the least squares support vector machine network

Tarek A. Mahmoud (2011)

International Journal of Applied Mathematics and Computer Science

Recently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified structure of LS-SVM neural networks called the multi-resolution wavelet least squares support vector machine...

Adaptive high gain observer extension and its application to bioprocess monitoring

Sergej Čelikovský, Jorge Antonio Torres-Muñoz, Alma Rosa Dominguez-Bocanegra (2018)

Kybernetika

The adaptive version of the high gain observer for the strictly triangular systems subjected to constant unknown disturbances is proposed here. The adaptive feature is necessary due to the fact that the unknown disturbance enters in a way that cannot be suppressed by the high gain technique. The developed observers are then applied to a culture of microorganism in a bioreactor, namely, to the model of the continuous culture of Spirulina maxima. It is a common practice that just the biomass (or substrate)...

Adaptive modeling of reliability properties for control and supervision purposes

Kai-Uwe Dettmann, Dirk Söffker (2011)

International Journal of Applied Mathematics and Computer Science

Modeling of reliability characteristics typically assumes that components and systems fail if a certain individual damage level is exceeded. Every (mechanical) system damage increases irreversibly due to employed loading and (mechanical) stress, respectively. The main issue of damage estimation is adequate determination of the actual state-of-damage. Several mathematical modeling approaches are known in the literature, focusing on the task of how loading effects damage progression (e.g., Wöhler,...

Adaptive Parameter Estimation of Hyperbolic Distributed Parameter Systems: Non-symmetric Damping and Slowly Time Varying Systems

H. T. Banks, M. A. Demetriou (2010)

ESAIM: Control, Optimisation and Calculus of Variations

In this paper a model reference-based adaptive parameter estimator for a wide class of hyperbolic distributed parameter systems is considered. The proposed state and parameter estimator can handle hyperbolic systems in which the damping sesquilinear form may not be symmetric (or even present) and a modification to the standard adaptive law is introduced to account for this lack of symmetry (or absence) in the damping form. In addition, the proposed scheme is modified for systems in which the input...

Adaptive prediction of stock exchange indices by state space wavelet networks

Mietek A. Brdyś, Adam Borowa, Piotr Idźkowiak, Marcin T. Brdyś (2009)

International Journal of Applied Mathematics and Computer Science

The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session ahead and five sessions ahead adaptive predictors of the WIG20 index...

Adaptive stabilization of coupled PDE–ODE systems with multiple uncertainties

Jian Li, Yungang Liu (2014)

ESAIM: Control, Optimisation and Calculus of Variations

The adaptive stabilization is investigated for a class of coupled PDE-ODE systems with multiple uncertainties. The presence of the multiple uncertainties and the interaction between the sub-systems makes the systems to be considered more general and representative, and moreover it may result in the ineffectiveness of the conventional methods on this topic. Motivated by the existing literature, an infinite-dimensional backsteppping transformation with new kernel functions is first introduced to change...

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