Przemysław Prętki
University of Zielona Góra
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Publication
Featured researches published by Przemysław Prętki.
International Journal of Control | 2007
Marcin Witczak; Przemysław Prętki
The paper deals with the problem of designing an unknown input observer for discrete-time non-linear systems. In particular, with the use of the Lyapunov method, it is shown that the proposed observer is convergent under certain, non-restrictive conditions. Based on the achieved results, a general solution for increasing the convergence rate is proposed and implemented with the use of stochastic robustness techniques. In particular, it is shown that the problem of increasing the convergence rate of the observer can be formulated as a stochastic robustness analysis task that can be transformed into a structure selection and parameter estimation problem of a non-linear function, which can be solved with the B-spline approximation and evolutionary algorithms. The final part of the paper shows an illustrative example based on a two phase induction motor. The presented results clearly exhibit the performance of the proposed observer.
congress on evolutionary computation | 2005
Andrzej Obuchowicz; Przemysław Prętki
A subclass of Levy-stable distributions, i.e., symmetric alpha-stable distributions (SalphaS), is applied to mutation operators of evolutionary strategies (1+1)ESalpha and (1+lambda)ESalpha. The local convergence rate of algorithms is considered. Moreover, some conditions are established under which evolutionary algorithms with mutation based on distributions with heavy tails generally have better local as well as global convergence. In order to justify the theoretical deliberations, some illustrative numerical simulations are presented
international conference on artificial intelligence and soft computing | 2006
Przemysław Prętki; Andrzej Obuchowicz
In this paper, a concept of directional mutations for phenotypic evolutionary algorithms is presented. The proposed approach allows, in a very convenient way, to adapt the probability measure underlying the mutation operator during evolutionary process. Moreover, the paper provides some guidance, along with suitable theorems, which makes it possible to get a deeper understanding of the ineffectiveness of isotropic mutations for large-scale problems.
soft computing | 2010
Andrzej Obuchowicz; Przemysław Prętki
In this paper the concept of multidimensional discrete spectral measure is introduced in the context of its application to real-valued evolutionary algorithms. The notion of discrete spectral measure makes possible to uniquely define a class of multivariate heavy-tailed distributions, that have received more and more attention of evolutionary optimization commynity, recently. Simple sample illustrates advantages of such approach.
international conference on artificial neural networks | 2005
Krzysztof Patan; Józef Korbicz; Przemysław Prętki
The paper deals with a discrete-time recurrent neural network designed with dynamic neural models. Dynamics is reproduced within each single neuron, hence the considered network is a locally recurrent globally feed-forward. In the paper, conditions for global stability of the considered neural network are derived using the pole placement and Lyapunov second method.
IFAC Proceedings Volumes | 2007
Marcin Witczak; Przemysław Prętki; Józef Korbicz
Abstract The paper deals with the problem of designing an unknown input observer for discrete-time non-linear systems. General convergence conditions and a solution for increasing the observer convergence rate are proposed and implemented with the use of stochastic robustness techniques. The paper contains an illustrative example concerning state estimation and fault detection of an induction motor, which shows the high performance of the proposed observer.
international conference on artificial intelligence and soft computing | 2006
Przemysław Prętki; Andrzej Obuchowicz
One of the most serious problem concerning global optimization methods is their correct configuration. Usually algorithms are described by some number of external parameters for which optimal values strongly depend on the objective function. If there is a lack of knowledge on the function under consideration the optimization algorithms can by adjusted using trail-and-error method. Naturally, this kind of approach gives rise to many computational problems. Moreover, it can be applied only when a lot of function evaluations is allowed. In order to avoid trial-and-error method it is reasonable to use an optimization algorithm which is characterized by the highest degree of robustness according to the variations in its control parameters. In this paper, the robustness issue of evolutionary strategy with isotropic stable mutations is discussed. The experimental simulations are conducted with the help of special search environment - the so-called general search space.
international conference on artificial neural networks | 2005
Przemysław Prętki; Marcin Witczak
The paper deals with an application of the theory of optimum experimental design to the problem of selecting the data set for developing neural models. Another objective is to show that neural network trained with the samples obtained according to D-optimum design is endowed with less parameters uncertainty what allows to obtain more reliable tool for modelling purposes.
Archive | 2007
Andrzej Obuchowicz; Wiesław Wajs; Andrzej Pieczyński; Józef Korbicz; Krzysztof Patan; Marek Kowal; Dariusz Uciński; Jan Maciej Kościelny; Janusz Petrykowski; Andrzej Dyka; Roman Śmierzchalski; Henryk Welfe; Paweł Drzymała; Sławomir Wiak; Rainer Hampel; Frank Drager; Piotr Tatjewski; Maciej Ławryńczuk; Marcin Zych; Krzysztof Warnke; Paweł Raczyński; Józef Lubkiewicz; Dilek Dustegor; Mogens Blanke; Morten Laursen; Paweł Stoch; Krzysztof Rączka; Maciej Kusy; Maciej Hrebień; Rafał Józefowicz
International Journal of Applied Mathematics and Computer Science | 2004
Andrzej Obuchowicz; Przemysław Prętki