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A generalization of Ueno's inequality for n-step transition probabilities

Andrzej Nowak (1998)

Applicationes Mathematicae

We provide a generalization of Ueno's inequality for n-step transition probabilities of Markov chains in a general state space. Our result is relevant to the study of adaptive control problems and approximation problems in the theory of discrete-time Markov decision processes and stochastic games.

A mathematical framework for learning and adaption: (generalized) random systems with complete connections.

Ulrich Herkenrath, Radu Theodorescu (1981)

Trabajos de Estadística e Investigación Operativa

The aim of this paper is to show that the theory of (generalized) random systems with complete connection may serve as a mathematical framework for learning and adaption. Chapter 1 is of an introductory nature and gives a general description of the problems with which one is faced. In Chapter 2 the mathematical model and some results about it are explained. Chapter 3 deals with special learning and adaption models.

A new indirect adaptive pole placer for possibly non-minimum phase MIMO linear systems

Kostas G. Arvanitis, Grigoris Kalogeropoulos, I. K. Kookos (2000)


The use of generalized sampled-data hold functions, in order to synthesize adaptive pole placers for linear multiple-input, multiple-output systems with unknown parameters, is investigated in this paper, for the first time. Such a control scheme relies on a periodically varying controller, which suitably modulates the sampled outputs of the controlled plant. The proposed control strategy allows us to assign the poles of the sampled closed-loop system arbitrarily in desired locations, and does not...

A scratch removal method

Michal Haindl, Stanislava Šimberová (1998)


We present a new type of scratch removal algorithm based on a causal adaptive multidimensional prediction. The predictor use available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data but not any information from failed pixel itself. Predictor parameters cannot be directly identified so a special approximation is introduced.

Adaptive compensators for perturbed positive real infinite-dimensional systems

Ruth Curtain, Michael Demetriou, Kazufumi Ito (2003)

International Journal of Applied Mathematics and Computer Science

The aim of this investigation is to construct an adaptive observer and an adaptive compensator for a class of infinite-dimensional plants having a known exogenous input and a structured perturbation with an unknown constant parameter, such as the case of static output feedback with an unknown gain. The adaptive observer uses the nominal dynamics of the unperturbed plant and an adaptation law based on the Lyapunov redesign method. We obtain conditions on the system to ensure uniform boundedness of...

Adaptive control for discrete-time Markov processes with unbounded costs: Discounted criterion

Evgueni I. Gordienko, J. Adolfo Minjárez-Sosa (1998)


We study the adaptive control problem for discrete-time Markov control processes with Borel state and action spaces and possibly unbounded one-stage costs. The processes are given by recurrent equations x t + 1 = F ( x t , a t , ξ t ) , t = 0 , 1 , ... with i.i.d. k -valued random vectors ξ t whose density ρ is unknown. Assuming observability of ξ t we propose the procedure of statistical estimation of ρ that allows us to prove discounted asymptotic optimality of two types of adaptive policies used early for the processes with bounded costs.

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)


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....

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