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

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

Kybernetika

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 note on impulsive control of Feller processes with costly information

Dariusz Gątarek (1990)

Aplikace matematiky

The paper deals with the optimal inspections and maintenance problem with costly information for a Markov process with positive discount factor. The associated dynamic programming equation is a quasi-variational inequality with first order differential terms. In this paper we study its different formulations: strong, visousity and evolutionary. The case of impulsive control of purely jump Markov processes is studied as a special case.

A sample-time adjusted feedback for robust bounded output stabilization

Patricio Ordaz, Hussain Alazki, Alexander Poznyak (2013)

Kybernetika

This paper deals with a bounded control design for a class of nonlinear systems where the mathematical model may be not explicitly given. This class of uncertain nonlinear systems governed by a system of ODE with quasi-Lipschitz right-hand side and containing external perturbations as well. The Attractive Ellipsoid Method (AEM) application permits to describe the class of nonlinear feedbacks (containing a nonlinear projection operator, a linear state estimator and a feedback matrix-gain) guaranteeing...

An algorithm for reducing the dimension and size of a sample for data exploration procedures

Piotr Kulczycki, Szymon Łukasik (2014)

International Journal of Applied Mathematics and Computer Science

The paper deals with the issue of reducing the dimension and size of a data set (random sample) for exploratory data analysis procedures. The concept of the algorithm investigated here is based on linear transformation to a space of a smaller dimension, while retaining as much as possible the same distances between particular elements. Elements of the transformation matrix are computed using the metaheuristics of parallel fast simulated annealing. Moreover, elimination of or a decrease in importance...

Argument increment stability criterion for linear delta models

Milan Hofreiter, Pavel Zítek (2003)

International Journal of Applied Mathematics and Computer Science

Currently used stability criteria for linear sampled-data systems refer to the standard linear difference equation form of the system model. This paper presents a stability criterion based on the argument increment rule modified for the delta operator form of the sampled-data model. For the asymptotic stability of this system form it is necessary and sufficient that the roots of the appropriate characteristic equation lie inside a circle in the left half of the complex plane, the radius of which...

Continuous-time input-output decoupling for sampled-data systems

Osvaldo Maria Grasselli, Laura Menini (1999)

Kybernetika

The problem of obtaining a continuous-time (i. e., ripple-free) input-output decoupled control system for a continuous-time linear time-invariant plant, by means of a purely discrete-time compensator, is stated and solved in the case of a unity feedback control system. Such a control system is hybrid, since the plant is continuous-time and the compensator is discrete-time. A necessary and sufficient condition for the existence of a solution of such a problem is given, which reduces the mentioned...

Double-stepped adaptive control for hybrid systems with unknown Markov jumps and stochastic noises

Shuping Tan, Ji-Feng Zhang (2009)

ESAIM: Control, Optimisation and Calculus of Variations

This paper is concerned with the sampled-data based adaptive linear quadratic (LQ) control of hybrid systems with both unmeasurable Markov jump processes and stochastic noises. By the least matching error estimation algorithm, parameter estimates are presented. By a double-step (DS) sampling approach and the certainty equivalence principle, a sampled-data based adaptive LQ control is designed. The DS-approach is characterized by a comparatively large estimation step for parameter estimation and...

Double-stepped adaptive control for hybrid systems with unknown Markov jumps and stochastic noises

Shuping Tan, Ji-Feng Zhang (2008)

ESAIM: Control, Optimisation and Calculus of Variations

This paper is concerned with the sampled-data based adaptive linear quadratic (LQ) control of hybrid systems with both unmeasurable Markov jump processes and stochastic noises. By the least matching error estimation algorithm, parameter estimates are presented. By a double-step (DS) sampling approach and the certainty equivalence principle, a sampled-data based adaptive LQ control is designed. The DS-approach is characterized by a comparatively large estimation step for parameter estimation and...

Flow control in connection-oriented networks: a time-varying sampling period system case study

Przemysław Ignaciuk, Andrzej Bartoszewicz (2008)

Kybernetika

In this paper congestion control problem in connection-oriented communication network with multiple data sources is addressed. In the considered network the feedback necessary for the flow regulation is provided by means of management units, which are sent by each source once every M data packets. The management units, carrying the information about the current network state, return to their origin round trip time RTT after they were sent. Since the source rate is adjusted only at the instant of...

Fuzzy empirical distribution function: Properties and application

Gholamreza Hesamian, S. M. Taheri (2013)

Kybernetika

The concepts of cumulative distribution function and empirical distribution function are investigated for fuzzy random variables. Some limit theorems related to such functions are established. As an application of the obtained results, a method of handling fuzziness upon the usual method of Kolmogorov-Smirnov one-sample test is proposed. We transact the α -level set of imprecise observations in order to extend the usual method of Kolmogorov-Smirnov one-sample test. To do this, the concepts of fuzzy...

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