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Wyszukujesz frazę "Poznyak, Alexander" wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Robust Control of Linear Stochastic Systems with Fully Observable State
Autorzy:
Poznyak, Alexander
Taksar, M.
Powiązania:
https://bibliotekanauki.pl/articles/1339291.pdf
Data publikacji:
1996
Wydawca:
Polska Akademia Nauk. Instytut Matematyczny PAN
Tematy:
robust control
Riccati equation
stochastic differential equations
stochastic control
Opis:
We consider a multidimensional linear system with additive inputs (control) and Brownian noise. There is a cost associated with each control. The aim is to minimize the cost. However, we work with the model in which the parameters of the system may change in time and in addition the exact form of these parameters is not known, only intervals within which they vary are given. In the situation where minimization of a functional over the class of admissible controls makes no sense since the value of such a functional is different for different systems within the class, we should deal not with a single problem but with a family of problems. The objective in such a setting is twofold. First, we intend to establish existence of a state feedback linear robust control which stabilizes any system within the class. Then among all robust controls we find the one which yields the lowest bound on the cost within the class of all systems under consideration. We give the answer in terms of a solution to a matrix Riccati equation and we present necessary and sufficient conditions for such a solution to exist. We also state a criterion when the obtained bound on the cost is sharp, that is, the control we construct is actually a solution to the minimax problem.
Źródło:
Applicationes Mathematicae; 1996-1997, 24, 1; 35-46
1233-7234
Pojawia się w:
Applicationes Mathematicae
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Computing a mechanism for a Bayesian and partially observable Markov approach
Autorzy:
Clempner, Julio B.
Poznyak, Alexander S.
Powiązania:
https://bibliotekanauki.pl/articles/24200692.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
dynamic mechanism design
partially observable Markov chains
games with private information
Bayesian equilibrium
mechanizm dynamiczny
łańcuchy Markova
równowaga Bayesa
Opis:
The design of incentive-compatible mechanisms for a certain class of finite Bayesian partially observable Markov games is proposed using a dynamic framework. We set forth a formal method that maintains the incomplete knowledge of both the Bayesian model and the Markov system’s states. We suggest a methodology that uses Tikhonov’s regularization technique to compute a Bayesian Nash equilibrium and the accompanying game mechanism. Our framework centers on a penalty function approach, which guarantees strong convexity of the regularized reward function and the existence of a singular solution involving equality and inequality constraints in the game. We demonstrate that the approach leads to a resolution with the smallest weighted norm. The resulting individually rational and ex post periodic incentive compatible system satisfies this requirement. We arrive at the analytical equations needed to compute the game’s mechanism and equilibrium. Finally, using a supply chain network for a profit maximization problem, we demonstrate the viability of the proposed mechanism design.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 3; 463--478
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust extremum seeking for a second order uncertain plant using a sliding mode controller
Autorzy:
Solis, Cesar
Clempner, Julio
Poznyak, Alexander
Powiązania:
https://bibliotekanauki.pl/articles/330477.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
convex optimization
extremum seeking
continuous time gradient algorithm
dynamical constrained optimization
unknown function
optymalizacja wypukła
poszukiwanie ekstremum
algorytm gradientowy
optymalizacja ograniczona
Opis:
This paper suggests a novel continuous-time robust extremum seeking algorithm for an unknown convex function constrained by a dynamical plant with uncertainties. The main idea of the proposed method is to develop a robust closed-loop controller based on sliding modes where the sliding surface takes the trajectory around a zone of the optimal point. We assume that the output of the plant is given by the states and a measure of the function. We show the stability and zone-convergence of the proposed algorithm. In order to validate the proposed method, we present a numerical example.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2019, 29, 4; 703-712
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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