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Ecological-Economic Model of the Region: Information Technology, Forecasting and Optimal Control

V. Gurman, V. Baturin (2009)

Mathematical Modelling of Natural Phenomena

The paper considers a methodology of mathematical modeling of ecological-economic processes at the regional level. The basis of the model is formed by equations, which describe two interacting blocks: economic and ecological ones. Equations of the economic block are represented by relations of generalized inter-branch balance, while the ecological part is described in terms of differential equations with deviations with respect to some given state of natural resources. Issues of i) information...

Economic assessment of the Champagne wine qualitative stock mecanism

Jacques Laye, Maximilien Laye (2006)

RAIRO - Operations Research

In the wine AOC system, the regulation of quantities performed by the professional organizations is aimed to smooth the variations of the quality of the wine due to the variations in the climate that affect the quality of the grapes. Nevertheless, this regulation could be damaging to the consumers due to the price increase resulting from the reduction of the quantities sold on the market. We propose a stochastic control model and a simulation tool able to measure the effects of this mechanism...

Effective dual-mode fuzzy DMC algorithms with on-line quadratic optimization and guaranteed stability

Piotr M. Marusak, Piotr Tatjewski (2009)

International Journal of Applied Mathematics and Computer Science

Dual-mode fuzzy dynamic matrix control (fuzzy DMC-FDMC) algorithms with guaranteed nominal stability for constrained nonlinear plants are presented. The algorithms join the advantages of fuzzy Takagi-Sugeno modeling and the predictive dual-mode approach in a computationally efficient version. Thus, they can bring an improvement in control quality compared with predictive controllers based on linear models and, at the same time, control performance similar to that obtained using more demanding algorithms...

Efficiency analysis of control algorithms in spatially distributed systems with chaotic behavior

Łukasz Korus (2014)

International Journal of Applied Mathematics and Computer Science

The paper presents results of examination of control algorithms for the purpose of controlling chaos in spatially distributed systems like the coupled map lattice (CML). The mathematical definition of the CML, stability analysis as well as some basic results of numerical simulation exposing complex, spatiotemporal and chaotic behavior of the CML were already presented in another paper. The main purpose of this article is to compare the efficiency of controlling chaos by simple classical algorithms...

Efficient measurement of higher-order statistics of stochastic processes

Wladyslaw Magiera, Urszula Libal, Agnieszka Wielgus (2018)

Kybernetika

This paper is devoted to analysis of block multi-indexed higher-order covariance matrices, which can be used for the least-squares estimation problem. The formulation of linear and nonlinear least squares estimation problems is proposed, showing that their statements and solutions lead to generalized `normal equations', employing covariance matrices of the underlying processes. Then, we provide a class of efficient algorithms to estimate higher-order statistics (generalized multi-indexed covariance...

Efficient nonlinear predictive control based on structured neural models

Maciej Ławryńczuk (2009)

International Journal of Applied Mathematics and Computer Science

This paper describes structured neural models and a computationally efficient (suboptimal) nonlinear Model Predictive Control (MPC) algorithm based on such models. The structured neural model has the ability to make future predictions of the process without being used recursively. Thanks to the nature of the model, the prediction error is not propagated. This is particularly important in the case of noise and underparameterisation. Structured models have much better long-range prediction accuracy...

Efficient numerical algorithms for balanced stochastic truncation

Peter Benner, Enrique Quintana-Ortí, Gregorio Quintana-Ortí (2001)

International Journal of Applied Mathematics and Computer Science

We propose an efficient numerical algorithm for relative error model reduction based on balanced stochastic truncation. The method uses full-rank factors of the Gramians to be balanced versus each other and exploits the fact that for large-scale systems these Gramians are often of low numerical rank. We use the easy-to-parallelize sign function method as the major computational tool in determining these full-rank factors and demonstrate the numerical performance of the suggested implementation of...

Efficient RGB-D data processing for feature-based self-localization of mobile robots

Marek Kraft, Michał Nowicki, Rudi Penne, Adam Schmidt, Piotr Skrzypczyński (2016)

International Journal of Applied Mathematics and Computer Science

The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on efficient point feature extraction algorithms and on methods for the management of a set of features in a single RGB-D data frame. While the fast, RGB-D-based visual odometry system described in this paper builds upon our previous results as to the general...

Eigenspace of a three-dimensional max-Łukasiewicz fuzzy matrix

Imran Rashid, Martin Gavalec, Sergeĭ Sergeev (2012)

Kybernetika

Eigenvectors of a fuzzy matrix correspond to stable states of a complex discrete-events system, characterized by a given transition matrix and fuzzy state vectors. Description of the eigenspace (set of all eigenvectors) for matrices in max-min or max-drast fuzzy algebra was presented in previous papers. In this paper the eigenspace of a three-dimensional fuzzy matrix in max-Łukasiewicz algebra is investigated. Necessary and sufficient conditions are shown under which the eigenspace restricted to...

Eigenstructure assignment by proportional-plus-derivative feedback for second-order linear control systems

Taha H. S. Abdelaziz, Michael Valášek (2005)

Kybernetika

This paper introduces a complete parametric approach for solving the eigenstructure assignment problem using proportional-plus-derivative feedback for second-order linear control systems. In this work, necessary and sufficient conditions that ensure the solvability for the second-order system are derived. A parametric solution to the feedback gain matrix is introduced that describes the available degrees of freedom offered by the proportional-plus-derivative feedback in selecting the associated...

Elimination of finite eigenvalues of the 2D Roesser model by state feedbacks

Tadeusz Kaczorek (2001)

International Journal of Applied Mathematics and Computer Science

A new problem of decreasing the degree of the closed-loop characteristic polynomial of the 2D Roesser model by a suitable choice of state feedbacks is formulated. Sufficient conditions are established under which it is possible to choose state feedbacks such that the non-zero closed-loop characteristic polynomial has degree zero. A procedure for computation of the feedback gain matrices is presented and illustrated by a numerical example.

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