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Range identification for a perspective dynamic system with a single homogeneous observation

Lili Ma, Yangquan Chen, Kevin Moore (2005)

International Journal of Applied Mathematics and Computer Science

Perspective problems arise in machine vision when using a camera to observe the scene. Essential problems include the identification of unknown states and/or unknown parameters from perspective observations. Range identification is used to estimate the states/positions of a moving object with known motion parameters. Range estimation has been discussed in the literature using nonlinear observers with full homogeneous observations derived from the image plane. In this paper, the same range identification...

Recursive identification algorithm for dynamic systems with output backlash and its convergence

Ruili Dong, Qingyuan Tan, Yonghong Tan (2009)

International Journal of Applied Mathematics and Computer Science

This paper proposes a recursive identification method for systems with output backlash that can be described by a pseudoWiener model. In this method, a novel description of the nonlinear part of the system, i.e., backlash, is developed. In this case, the nonlinear system is decomposed into a piecewise linearized model. Then, a modified recursive general identification algorithm (MRGIA) is employed to estimate the parameters of the proposed model. Furthermore, the convergence of the MRGIA for the...

Recursive identification of Wiener systems

Włodzimierz Greblicki (2001)

International Journal of Applied Mathematics and Computer Science

A Wiener system, i.e. a cascade system consisting of a linear dynamic subsystem and a nonlinear memoryless subsystem is identified. The a priori information is nonparametric, i.e. neither the functional form of the nonlinear characteristic nor the order of the dynamic part are known. Both the input signal and the disturbance are Gaussian white random processes. Recursive algorithms to estimate the nonlinear characteristic are proposed and their convergence is shown. Results of numerical simulation...

Rejection of nonharmonic disturbances in nonlinear systems

Shutang Liu, Yuan Jiang, Ping Liu (2010)

Kybernetika

This paper proposes an asymptotic rejection algorithm on the rejection of nonharmonic periodic disturbances for general nonlinear systems. The disturbances, which are produced by nonlinear exosystems, are nonharmonic and periodic. A new nonlinear internal model is proposed to deal with the disturbances. Further, a state feedback controller is designed to ensure that the system's state variables can asymptotically converge to zero, and the disturbances can be completely rejected. The proposed algorithm...

Relative cost curves: An alternative to AUC and an extension to 3-class problems

Olga Montvida, Frank Klawonn (2014)

Kybernetika

Performance evaluation of classifiers is a crucial step for selecting the best classifier or the best set of parameters for a classifier. Receiver Operating Characteristic (ROC) curves and Area Under the ROC Curve (AUC) are widely used to analyse performance of a classifier. However, the approach does not take into account that misclassification for different classes might have more or less serious consequences. On the other hand, it is often difficult to specify exactly the consequences or costs...

Relaxed stability conditions for interval type-2 fuzzy-model-based control systems

Tao Zhao, Jian Xiao, Jialin Ding, Xuesong Deng, Song Wang (2014)

Kybernetika

This paper proposes new stability conditions for interval type-2 fuzzy-model-based (FMB) control systems. The type-1 T-S fuzzy model has been widely studied because it can represent a wide class of nonlinear systems. Many favorable results for type-1 T-S fuzzy model have been reported. However, most of conclusions for type-1 T-S fuzzy model can not be applied to nonlinear systems subject to parameter uncertainties. In fact, Most of the practical applications are subject to parameters uncertainties....

Residual generator fuzzy identification for automotive diesel engine fault diagnosis

Silvio Simani (2013)

International Journal of Applied Mathematics and Computer Science

Safety in dynamic processes is a concern of rising importance, especially if people would be endangered by serious system failure. Moreover, as the control devices which are now exploited to improve the overall performance of processes include both sophisticated control strategies and complex hardware (input-output sensors, actuators, components and processing units), there is an increased probability of faults. As a direct consequence of this, automatic supervision systems should be taken into...

Robust control of chaos in modified FitzHugh-Nagumo neuron model under external electrical stimulation based on internal model principle

Yuan Jiang, Jiyang Dai (2011)

Kybernetika

This paper treats the question of robust control of chaos in modified FitzHugh-Nagumo neuron model under external electrical stimulation based on internal model principle. We first present the solution of the global robust output regulation problem for output feedback system with nonlinear exosystem. Then we show that the robust control problem for the modified FitzHugh-Nagumo neuron model can be formulated as the global robust output regulation problem and the solvability conditions for the output...

Robust pole placement for second-order systems: an LMI approach

Didier Henrion, Michael Šebek, Vladimír Kučera (2005)

Kybernetika

Based on recently developed sufficient conditions for stability of polynomial matrices, an LMI technique is described to perform robust pole placement by proportional-derivative feedback on second-order linear systems affected by polytopic or norm-bounded uncertainty. As illustrated by several numerical examples, at the core of the approach is the choice of a nominal, or central quadratic polynomial matrix.

Sensor network design for the estimation of spatially distributed processes

Dariusz Uciński, Maciej Patan (2010)

International Journal of Applied Mathematics and Computer Science

In a typical moving contaminating source identification problem, after some type of biological or chemical contamination has occurred, there is a developing cloud of dangerous or toxic material. In order to detect and localize the contamination source, a sensor network can be used. Up to now, however, approaches aiming at guaranteeing a dense region coverage or satisfactory network connectivity have dominated this line of research and abstracted away from the mathematical description of the physical...

Sensor network scheduling for identification of spatially distributed processes

Dariusz Uciński (2012)

International Journal of Applied Mathematics and Computer Science

The work treats the problem of fault detection for processes described by partial differential equations as that of maximizing the power of a parametric hypothesis test which checks whether or not system parameters have nominal values. A simple node activation strategy is discussed for the design of a sensor network deployed in a spatial domain that is supposed to be used while detecting changes in the underlying parameters which govern the process evolution. The setting considered relates to a...

Significance tests to identify regulated proteins based on a large number of small samples

Frank Klawonn (2012)

Kybernetika

Modern biology is interested in better understanding mechanisms within cells. For this purpose, products of cells like metabolites, peptides, proteins or mRNA are measured and compared under different conditions, for instance healthy cells vs. infected cells. Such experiments usually yield regulation or expression values – the abundance or absence of a cell product in one condition compared to another one – for a large number of cell products, but with only a few replicates. In order to distinguish...

Some algorithmic aspects of subspace identificationwith inputs

Alessandro Chiuso, Giorgio Picci (2001)

International Journal of Applied Mathematics and Computer Science

It has been experimentally verified that most commonly used subspace methods for identification of linear state-space systems with exogenous inputs may, in certain experimental conditions, run into ill-conditioning and lead to ambiguous results. An analysis of the critical situations has lead us to propose a new algorithmic structure which could be used either to test difficult cases andor to implement a suitable combination of new and old algorithms presented in the literature to help fixing the...

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