Rivista e Edizione

Volume 32 (2022): Edizione 2 (June 2022)
Towards Self-Healing Systems through Diagnostics, Fault-Tolerance and Design (Special section, pp. 171-269), Marcin Witczak and Ralf Stetter (Eds.)

Volume 32 (2022): Edizione 1 (March 2022)

Volume 31 (2021): Edizione 4 (December 2021)
Advanced Machine Learning Techniques in Data Analysis (special section, pp. 549-611), Maciej Kusy, Rafał Scherer, and Adam Krzyżak (Eds.)

Volume 31 (2021): Edizione 3 (September 2021)

Volume 31 (2021): Edizione 2 (June 2021)

Volume 31 (2021): Edizione 1 (March 2021)

Volume 30 (2020): Edizione 4 (December 2020)

Volume 30 (2020): Edizione 3 (September 2020)
Big Data and Signal Processing (Special section, pp. 399-473), Joanna Kołodziej, Sabri Pllana, Salvatore Vitabile (Eds.)

Volume 30 (2020): Edizione 2 (June 2020)

Volume 30 (2020): Edizione 1 (March 2020)

Volume 29 (2019): Edizione 4 (December 2019)
New Perspectives in Nonlinear and Intelligent Control (In Honor of Alexander P. Kurdyukov) (special section, pp. 629-712), Julio B. Clempner, Enso Ikonen, Alexander P. Kurdyukov (Eds.)

Volume 29 (2019): Edizione 3 (September 2019)
Information Technology for Systems Research (special section, pp. 427-515), Piotr Kulczycki, Janusz Kacprzyk, László T. Kóczy, Radko Mesiar (Eds.)

Volume 29 (2019): Edizione 2 (June 2019)
Advances in Complex Cloud and Service Oriented Computing (special section, pp. 213-274), Anna Kobusińska, Ching-Hsien Hsu, Kwei-Jay Lin (Eds.)

Volume 29 (2019): Edizione 1 (March 2019)
Exploring Complex and Big Data (special section, pp. 7-91), Johann Gamper, Robert Wrembel (Eds.)

Volume 28 (2018): Edizione 4 (December 2018)

Volume 28 (2018): Edizione 3 (September 2018)

Volume 28 (2018): Edizione 2 (June 2018)
Advanced Diagnosis and Fault-Tolerant Control Methods (special section, pp. 233-333), Vicenç Puig, Dominique Sauter, Christophe Aubrun, Horst Schulte (Eds.)

Volume 28 (2018): Edizione 1 (March 2018)
Ediziones in Parameter Identification and Control (special section, pp. 9-122), Abdel Aitouche (Ed.)

Volume 27 (2017): Edizione 4 (December 2017)

Volume 27 (2017): Edizione 3 (September 2017)
Systems Analysis: Modeling and Control (special section, pp. 457-499), Vyacheslav Maksimov and Boris Mordukhovich (Eds.)

Volume 27 (2017): Edizione 2 (June 2017)

Volume 27 (2017): Edizione 1 (March 2017)

Volume 26 (2016): Edizione 4 (December 2016)

Volume 26 (2016): Edizione 3 (September 2016)

Volume 26 (2016): Edizione 2 (June 2016)

Volume 26 (2016): Edizione 1 (March 2016)

Volume 25 (2015): Edizione 4 (December 2015)
Special issue: Complex Problems in High-Performance Computing Systems, Editors: Mauro Iacono, Joanna Kołodziej

Volume 25 (2015): Edizione 3 (September 2015)

Volume 25 (2015): Edizione 2 (June 2015)

Volume 25 (2015): Edizione 1 (March 2015)
Safety, Fault Diagnosis and Fault Tolerant Control in Aerospace Systems, Silvio Simani, Paolo Castaldi (Eds.)

Volume 24 (2014): Edizione 4 (December 2014)

Volume 24 (2014): Edizione 3 (September 2014)
Modelling and Simulation of High Performance Information Systems (special section, pp. 453-566), Pavel Abaev, Rostislav Razumchik, Joanna Kołodziej (Eds.)

Volume 24 (2014): Edizione 2 (June 2014)
Signals and Systems (special section, pp. 233-312), Ryszard Makowski and Jan Zarzycki (Eds.)

Volume 24 (2014): Edizione 1 (March 2014)
Selected Problems of Biomedical Engineering (special section, pp. 7 - 63), Marek Kowal and Józef Korbicz (Eds.)

Volume 23 (2013): Edizione 4 (December 2013)

Volume 23 (2013): Edizione 3 (September 2013)

Volume 23 (2013): Edizione 2 (June 2013)

Volume 23 (2013): Edizione 1 (March 2013)

Volume 22 (2012): Edizione 4 (December 2012)
Hybrid and Ensemble Methods in Machine Learning (special section, pp. 787 - 881), Oscar Cordón and Przemysław Kazienko (Eds.)

Volume 22 (2012): Edizione 3 (September 2012)

Volume 22 (2012): Edizione 2 (June 2012)
Analysis and Control of Spatiotemporal Dynamic Systems (special section, pp. 245 - 326), Dariusz Uciński and Józef Korbicz (Eds.)

Volume 22 (2012): Edizione 1 (March 2012)
Advances in Control and Fault-Tolerant Systems (special issue), Józef Korbicz, Didier Maquin and Didier Theilliol (Eds.)

Volume 21 (2011): Edizione 4 (December 2011)

Volume 21 (2011): Edizione 3 (September 2011)
Ediziones in Advanced Control and Diagnosis (special section, pp. 423 - 486), Vicenç Puig and Marcin Witczak (Eds.)

Volume 21 (2011): Edizione 2 (June 2011)
Efficient Resource Management for Grid-Enabled Applications (special section, pp. 219 - 306), Joanna Kołodziej and Fatos Xhafa (Eds.)

Volume 21 (2011): Edizione 1 (March 2011)
Semantic Knowledge Engineering (special section, pp. 9 - 95), Grzegorz J. Nalepa and Antoni Ligęza (Eds.)

Volume 20 (2010): Edizione 4 (December 2010)

Volume 20 (2010): Edizione 3 (September 2010)

Volume 20 (2010): Edizione 2 (June 2010)

Volume 20 (2010): Edizione 1 (March 2010)
Computational Intelligence in Modern Control Systems (special section, pp. 7 - 84), Józef Korbicz and Dariusz Uciński (Eds.)

Volume 19 (2009): Edizione 4 (December 2009)
Robot Control Theory (special section, pp. 519 - 588), Cezary Zieliński (Ed.)

Volume 19 (2009): Edizione 3 (September 2009)
Verified Methods: Applications in Medicine and Engineering (special issue), Andreas Rauh, Ekaterina Auer, Eberhard P. Hofer and Wolfram Luther (Eds.)

Volume 19 (2009): Edizione 2 (June 2009)

Volume 19 (2009): Edizione 1 (March 2009)

Volume 18 (2008): Edizione 4 (December 2008)
Ediziones in Fault Diagnosis and Fault Tolerant Control (special issue), Józef Korbicz and Dominique Sauter (Eds.)

Volume 18 (2008): Edizione 3 (September 2008)
Selected Problems of Computer Science and Control (special issue), Krzysztof Gałkowski, Eric Rogers and Jan Willems (Eds.)

Volume 18 (2008): Edizione 2 (June 2008)
Selected Topics in Biological Cybernetics (special section, pp. 117 - 170), Andrzej Kasiński and Filip Ponulak (Eds.)

Volume 18 (2008): Edizione 1 (March 2008)
Applied Image Processing (special issue), Anton Kummert and Ewaryst Rafajłowicz (Eds.)

Volume 17 (2007): Edizione 4 (December 2007)

Volume 17 (2007): Edizione 3 (September 2007)
Scientific Computation for Fluid Mechanics and Hyperbolic Systems (special issue), Jan Sokołowski and Eric Sonnendrücker (Eds.)

Volume 17 (2007): Edizione 2 (June 2007)

Volume 17 (2007): Edizione 1 (March 2007)

Dettagli della rivista
Formato
Rivista
eISSN
2083-8492
Pubblicato per la prima volta
05 Apr 2007
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

Volume 22 (2012): Edizione 3 (September 2012)

Dettagli della rivista
Formato
Rivista
eISSN
2083-8492
Pubblicato per la prima volta
05 Apr 2007
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

20 Articoli
Accesso libero

An approach to the analysis of observability and controllability in nonlinear systems via linear methods

Pubblicato online: 28 Sep 2012
Pagine: 507 - 522

Astratto

Abstract

The paper is devoted to the problem of observability and controllability analysis in nonlinear dynamic systems. Both continuous- and discrete-time systems described by nonlinear differential or difference equations, respectively, are considered. A new approach is developed to solve this problem whose features include (i) consideration of systems with non-differentiable nonlinearities and (ii) the use of relatively simple linear methods which may be supported by existing programming systems, e.g.,Matlab. Sufficient conditions are given for nonlinear unobservability/uncontrollability analysis. To apply these conditions, one isolates the linear part of the system which is checked to be unobservable/uncontrollable and, if the answer is positive, it is examined whether or not existing nonlinear terms violate the unobservability/uncontrollability property.

Parole chiave

  • nonlinear dynamic systems
  • observability
  • controllability
  • linear systems
  • decomposition
Accesso libero

On the controllability of fractional dynamical systems

Pubblicato online: 28 Sep 2012
Pagine: 523 - 531

Astratto

Abstract

This paper is concerned with the controllability of linear and nonlinear fractional dynamical systems in finite dimensional spaces. Sufficient conditions for controllability are obtained using Schauder’s fixed point theorem and the controllability Grammian matrix which is defined by the Mittag-Leffler matrix function. Examples are given to illustrate the effectiveness of the theory.

Parole chiave

  • controllability
  • fractional differential equations
  • Mittag-Leffler function
Accesso libero

Equivalent descriptions of a discrete-time fractional-order linear system and its stability domains

Pubblicato online: 28 Sep 2012
Pagine: 533 - 538

Astratto

Abstract

Two description forms of a linear fractional-order discrete system are considered. The first one is by a fractional-order difference equation, whereas the second by a fractional-order state-space equation. In relation to the two above-mentioned description forms, stability domains are evaluated. Several simulations of stable, marginally stable and unstable unit step responses of fractional-order systems due to different values of system parameters are presented.

Parole chiave

  • fractional calculus
  • linear discrete-time system
  • stability domain
Accesso libero

A multi-model approach to Saint-Venant equations: A stability study by LMIs

Pubblicato online: 28 Sep 2012
Pagine: 539 - 550

Astratto

Abstract

This paper deals with the stability study of the nonlinear Saint-Venant Partial Differential Equation (PDE). The proposed approach is based on the multi-model concept which takes into account some Linear Time Invariant (LTI) models defined around a set of operating points. This method allows describing the dynamics of this nonlinear system in an infinite dimensional space over a wide operating range. A stability analysis of the nonlinear Saint-Venant PDE is proposed both by using Linear Matrix Inequalities (LMIs) and an Internal Model Boundary Control (IMBC) structure. The method is applied both in simulations and real experiments through a microchannel, illustrating thus the theoretical results developed in the paper.

Parole chiave

  • Saint-Venant equation
  • multi-model
  • LMIs
  • infinite dimensional system
  • exponential stability
  • strongly continuous semigroup
  • internal model boundary control
Accesso libero

H control of discrete-time linear systems constrained in state by equality constraints

Pubblicato online: 28 Sep 2012
Pagine: 551 - 560

Astratto

Abstract

In this paper, stabilizing problems in control design are addressed for linear discrete-time systems, reflecting equality constraints tying together some state variables. Based on an enhanced representation of the bounded real lemma for discretetime systems, the existence of a state feedback control for such conditioned stabilization is proven, and an LMI-based design procedure is provided. The control law gain computation method used circumvents generally an ill-conditioned singular design task. The principle, when compared with previously published results, indicates that the proposed method outperforms the existing approaches, guarantees feasibility, and improves the steady-state accuracy of the control. Furthermore, better performance is achieved with essentially reduced design effort. The approach is illustrated on simulation examples, where the validity of the proposed method is demonstrated using one state equality constraint.

Parole chiave

  • equality constraints
  • discrete-time systems
  • linear matrix inequality
  • state feedback
  • control algorithms, quadratic stability
  • singular systems
Accesso libero

Enclosures for the solution set of parametric interval linear systems

Pubblicato online: 28 Sep 2012
Pagine: 561 - 574

Astratto

Abstract

We investigate parametric interval linear systems of equations. The main result is a generalization of the Bauer–Skeel and the Hansen–Bliek–Rohn bounds for this case, comparing and refinement of both. We show that the latter bounds are not provable better, and that they are also sometimes too pessimistic. The presented form of both methods is suitable for combining them into one to get a more efficient algorithm. Some numerical experiments are carried out to illustrate performances of the methods.

Parole chiave

  • linear interval systems
  • solution set
  • interval matrix
Accesso libero

Variable structure observer design for a class of uncertain systems with a time-varying delay

Pubblicato online: 28 Sep 2012
Pagine: 575 - 583

Astratto

Abstract

Design of a state observer is an important issue in control systems and signal processing. It is well known that it is difficult to obtain the desired properties of state feedback control if some or all of the system states cannot be directly measured. Moreover, the existence of a lumped perturbation and/or a time delay usually reduces the system performance or even produces an instability in the closed-loop system. Therefore, in this paper, a new Variable Structure Observer (VSO) is proposed for a class of uncertain systems subjected to a time varying delay and a lumped perturbation. Based on the strictly positive real concept, the stability of the equivalent error system is verified. Based on the generalized matrix inverse approach, the global reaching condition of the sliding mode of the error system is guaranteed. Also, the proposed variable structure observer will be shown to possess the invariance property in relation to the lumped perturbation, as the traditional variable structure controller does. Furthermore, two illustrative examples with a series of computer simulation studies are given to demonstrate the effectiveness of the proposed design method.

Parole chiave

  • variable structure observer
  • invariance property
  • generalized matrix inverse approach
Accesso libero

Bayesian reliability models of Weibull systems: State of the art

Pubblicato online: 28 Sep 2012
Pagine: 585 - 600

Astratto

Abstract

In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the use of fault trees and reliability diagrams is not possible. To overcome this problem, Bayesian approaches offer a considerable efficiency in this context. This paper introduces recent contributions in the field of reliability modeling with the Bayesian network approach. Bayesian reliability models are applied to systems with Weibull distribution of failure. To achieve the formulation of the reliability model, Bayesian estimation of Weibull parameters and the model’s goodness-of-fit are evoked. The advantages of this modelling approach are presented in the case of systems with an unknown reliability structure, those with a common cause of failures and redundant ones. Finally, we raise the issue of the use of BNs in the fault diagnosis area.

Parole chiave

  • hierarchical modeling
  • reliability
  • Weibull
  • Bayesian networks
  • fault diagnosis
Accesso libero

Modelling and control of an omnidirectional mobile manipulator

Pubblicato online: 28 Sep 2012
Pagine: 601 - 616

Astratto

Abstract

A new approach to control an omnidirectional mobile manipulator is developed. The robot is considered to be an individual agent aimed at performing robotic tasks described in terms of a displacement and a force interaction with the environment. A reactive architecture and impedance control are used to ensure reliable task execution in response to environment stimuli. The mechanical structure of our holonomic mobile manipulator is built of two joint manipulators mounted on a holonomic vehicle. The vehicle is equipped with three driven axles with two spherical orthogonal wheels. Taking into account the dynamical interaction between the base and the manipulator, one can define the dynamics of the mobile manipulator and design a nonlinear controller using the input-state linearization method. The control structure of the robot is built in order to demonstrate the main capabilities regarding navigation and obstacle avoidance. Several simulations were conducted to prove the effectiveness of this approach.

Parole chiave

  • holonome mobile manipulators
  • input state linearization
  • virtual impedance control
  • fuzzy logic
Accesso libero

A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization

Pubblicato online: 28 Sep 2012
Pagine: 617 - 628

Astratto

Abstract

This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Then, particle swarm optimization is employed to finally tune parameters of the obtained fuzzy model. The orthogonal least squares method is used to identify the unknown parameters of the local linear model. Finally, validation results of two examples are given to demonstrate the effectiveness and practicality of the proposed algorithm.

Parole chiave

  • Takagi–Sugeno fuzzy model
  • noise clustering algorithm
  • fuzzy c-regression model
  • orthogonal least squares
  • particle swarm optimization
Accesso libero

Optimal estimator of hypothesis probability for data mining problems with small samples

Pubblicato online: 28 Sep 2012
Pagine: 629 - 645

Astratto

Abstract

The paper presents a new (to the best of the authors’ knowledge) estimator of probability called the “Eph √ 2 completeness estimator” along with a theoretical derivation of its optimality. The estimator is especially suitable for a small number of sample items, which is the feature of many real problems characterized by data insufficiency. The control parameter of the estimator is not assumed in an a priori, subjective way, but was determined on the basis of an optimization criterion (the least absolute errors).The estimator was compared with the universally used frequency estimator of probability and with Cestnik’s m-estimator with respect to accuracy. The comparison was realized both theoretically and experimentally. The results show the superiority of the Eph √ 2 completeness estimator over the frequency estimator for the probability interval ph ∈ (0.1, 0.9). The frequency estimator is better for ph ∈ [0, 0.1] and ph ∈ [0.9, 1].

Parole chiave

  • single-case problem
  • probability
  • probability estimation
  • frequency interpretation of probability
  • completeness interpretation of probability
  • uncertainty theory
Accesso libero

Graph-based generation of a meta-learning search space

Pubblicato online: 28 Sep 2012
Pagine: 647 - 667

Astratto

Abstract

Meta-learning is becoming more and more important in current and future research concentrated around broadly defined data mining or computational intelligence. It can solve problems that cannot be solved by any single, specialized algorithm. The overall characteristic of each meta-learning algorithm mainly depends on two elements: the learning machine space and the supervisory procedure. The former restricts the space of all possible learning machines to a subspace to be browsed by a meta-learning algorithm. The latter determines the order of selected learning machines with a module responsible for machine complexity evaluation, organizes tests and performs analysis of results. In this article we present a framework for meta-learning search that can be seen as a method of sophisticated description and evaluation of functional search spaces of learning machine configurations used in meta-learning. Machine spaces will be defined by specially defined graphs where vertices are specialized machine configuration generators. By using such graphs the learning machine space may be modeled in a much more flexible way, depending on the characteristics of the problem considered and a priori knowledge. The presented method of search space description is used together with an advanced algorithm which orders test tasks according to their complexities.

Parole chiave

  • meta-learning
  • data mining
  • learning machines
  • complexity of learning
  • complexity of learning machines
  • computational intelligence
Accesso libero

Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses

Pubblicato online: 28 Sep 2012
Pagine: 669 - 684

Astratto

Abstract

The increased production of Reactive Oxygen Species (ROS) in plant leaf tissues is a hallmark of a plant’s reaction to various environmental stresses. This paper describes an automatic segmentation method for scanned images of cucurbits leaves stained to visualise ROS accumulation sites featured by specific colour hues and intensities. The leaves placed separately in the scanner view field on a colour background are extracted by thresholding in the RGB colour space, then cleaned from petioles to obtain a leaf blade mask. The second stage of the method consists in the classification of within mask pixels in a hue-saturation plane using two classes, determined by leaf regions with and without colour products of the ROS reaction. At this stage a two-layer, hybrid artificial neural network is applied with the first layer as a self-organising Kohonen type network and a linear perceptron output layer (counter propagation network type). The WTA-based, fast competitive learning of the first layer was improved to increase clustering reliability. Widrow–Hoff supervised training used at the output layer utilises manually labelled patterns prepared from training images. The generalisation ability of the network model has been verified by K-fold cross-validation. The method significantly accelerates the measurement of leaf regions containing the ROS reaction colour products and improves measurement accuracy.

Parole chiave

  • image segmentation
  • colour space
  • morphological processing
  • image thresholding
  • artificial neural network
  • WTA learning
  • Widrow–Hoff learning
  • Cucurbita species
  • plant stress
  • ROS detection
Accesso libero

Neural network based identification of hysteresis in human meridian systems

Pubblicato online: 28 Sep 2012
Pagine: 685 - 694

Astratto

Abstract

Developing a model based digital human meridian system is one of the interesting ways of understanding and improving acupuncture treatment, safety analysis for acupuncture operation, doctor training, or treatment scheme evaluation. In accomplishing this task, how to construct a proper model to describe the behavior of human meridian systems is one of the very important issues. From experiments, it has been found that the hysteresis phenomenon occurs in the relations between stimulation input and the corresponding response of meridian systems. Therefore, the modeling of hysteresis in a human meridian system is an unavoidable task for the construction of model based digital human meridian systems. As hysteresis is a nonsmooth, nonlinear and dynamic system with a multi-valued mapping, the conventional identification method is difficult to be employed to model its behavior directly. In this paper, a neural network based identification method of hysteresis occurring in human meridian systems is presented. In this modeling scheme, an expanded input space is constructed to transform the multi-valued mapping of hysteresis into a one-to-one mapping. For this purpose, a modified hysteretic operator is proposed to handle the extremum-missing problem. Then, based on the constructed expanded input space with the modified hysteretic operator, the so-called Extreme Learning Machine (ELM) neural network is utilized to model hysteresis inherent in human meridian systems. As hysteresis in meridian system is a dynamic system, a dynamic ELMneural network is developed. In the proposed dynamic ELMneural network, the output state of each hidden neuron is fed back to its own input to describe the dynamic behavior of hysteresis. The training of the recurrent ELM neural network is based on the least-squares algorithm with QR decomposition.

Parole chiave

  • acupuncture point
  • hysteresis
  • identification
  • neural networks
  • human meridian
  • traditional Chinese medicine
Accesso libero

A survey of subpixel edge detection methods for images of heat-emitting metal specimens

Pubblicato online: 28 Sep 2012
Pagine: 695 - 710

Astratto

Abstract

In this paper the problem of accurate edge detection in images of heat-emitting specimens of metals is discussed. The images are provided by the computerized system for high temperature measurements of surface properties of metals and alloys. Subpixel edge detection is applied in the system considered in order to improve the accuracy of surface tension determination. A reconstructive method for subpixel edge detection is introduced. The method uses a Gaussian function in order to reconstruct the gradient function in the neighborhood of a coarse edge and to determine its subpixel position. Results of applying the proposed method in the measurement system considered are presented and compared with those obtained using different methods for subpixel edge detection.

Parole chiave

  • subpixel accuracy
  • edge detection
  • surface property
  • approximation
  • Gaussian function
Accesso libero

KIS: An automated attribute induction method for classification of DNA sequences

Pubblicato online: 28 Sep 2012
Pagine: 711 - 721

Astratto

Abstract

This paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites. We also show how to use the algorithm to find a human readable model of the IRE (Iron-Responsive Element) and to find IRE sequences. The method, although universal, yields results which are of quality comparable to those obtained by reference methods. In contrast to reference methods, this approach uses models that operate on sequence patterns, which facilitates interpretation of the results by humans.

Parole chiave

  • classification
  • optimization
  • annotation
  • patterns
Accesso libero

Modeling nonlinear road traffic networks for junction control

Pubblicato online: 28 Sep 2012
Pagine: 723 - 732

Astratto

Abstract

The paper introduces a method of mathematical modeling of high scale road traffic networks, where a new special hypermatrix structure is intended to be used. The structure describes the inner–inner, inner–outer and outer–outer relations, and laws of a network area. The research examines the nonlinear equation system. The analysed model can be applied to the testing and planning of large-scale road traffic networks and the regulation of traffic systems. The elaborated model is in state space form, where the states are vehicle densities on a particular lane and the dynamics are described by a nonlinear state constrained positive system. This model can be used directly for simulation and analysis and as a starting point for investigating various control strategies. The stability of the traffic over the network can be analyzed by constructing a linear Lyapunov function and the associated theory. The model points out that in intersection control one must take the traffic density values of both the input and the output sections into account. Generally, the control of any domain has to take the density of input and output sections into consideration.

Parole chiave

  • mathematical modeling and control
  • traffic networks
  • nonlinear positive system
  • linear Lyapunov function
Accesso libero

Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems

Pubblicato online: 28 Sep 2012
Pagine: 733 - 748

Astratto

Abstract

Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P approach to distribute results of computational projects, i.e., results are transmitted in the system like in P2P file sharing systems (e.g., BitTorrent). In this work, we concentrate on offline optimization of the P2P computing system including two elements: scheduling of computations and data distribution. The objective is to minimize the system OPEX cost related to data processing and data transmission. We formulate an Integer Linear Problem (ILP) to model the system and apply this formulation to obtain optimal results using the CPLEX solver. Next, we propose two heuristic algorithms that provide results very

Parole chiave

  • P2P computing system
  • distributed computing
  • optimization
  • heuristics
  • evolutionary algorithms
Accesso libero

Joint queue-perturbed and weakly coupled power control for wireless backbone networks

Pubblicato online: 28 Sep 2012
Pagine: 749 - 764

Astratto

Abstract

Wireless Backbone Networks (WBNs) equipped with Multi-Radio Multi-Channel (MRMC) configurations do experience power control problems such as the inter-channel and co-channel interference, high energy consumption at multiple queues and unscalable network connectivity. Such network problems can be conveniently modelled using the theory of queue perturbation in the multiple queue systems and also as a weak coupling in a multiple channel wireless network. Consequently, this paper proposes a queue perturbation and weakly coupled based power control approach forWBNs. The ultimate objectives are to increase energy efficiency and the overall network capacity. In order to achieve this objective, a Markov chain model is first presented to describe the behaviour of the steady state probability distribution of the queue energy and buffer states. The singular perturbation parameter is approximated from the coefficients of the Taylor series expansion of the probability distribution. The impact of such queue perturbations on the transmission probability, given some transmission power values, is also analysed. Secondly, the inter-channel interference is modelled as a weakly coupled wireless system. Thirdly, Nash differential games are applied to derive optimal power control signals for each user subject to power constraints at each node. Finally, analytical models and numerical examples show the efficacy of the proposed model in solving power control problems in WBNs.

Parole chiave

  • decentralized power control
  • singular perturbation theory
  • weak coupling theory
  • wireless backbone networks
  • optimal control theory
Accesso libero

The Fan–Raspaud conjecture: A randomized algorithmic approach and application to the pair assignment problem in cubic networks

Pubblicato online: 06 Oct 2012
Pagine: 765 - 778

Astratto

Abstract

It was conjectured by Fan and Raspaud (1994) that every bridgeless cubic graph contains three perfect matchings such that every edge belongs to at most two of them. We show a randomized algorithmic way of finding Fan–Raspaud colorings of a given cubic graph and, analyzing the computer results, we try to find and describe the Fan–Raspaud colorings for some selected classes of cubic graphs. The presented algorithms can then be applied to the pair assignment problem in cubic computer networks. Another possible application of the algorithms is that of being a tool for mathematicians working in the field of cubic graph theory, for discovering edge colorings with certain mathematical properties and formulating new conjectures related to the Fan–Raspaud conjecture.

Parole chiave

  • cubic graph
  • edge coloring
  • perfect matching
  • randomized algorithms
  • computer networks
20 Articoli
Accesso libero

An approach to the analysis of observability and controllability in nonlinear systems via linear methods

Pubblicato online: 28 Sep 2012
Pagine: 507 - 522

Astratto

Abstract

The paper is devoted to the problem of observability and controllability analysis in nonlinear dynamic systems. Both continuous- and discrete-time systems described by nonlinear differential or difference equations, respectively, are considered. A new approach is developed to solve this problem whose features include (i) consideration of systems with non-differentiable nonlinearities and (ii) the use of relatively simple linear methods which may be supported by existing programming systems, e.g.,Matlab. Sufficient conditions are given for nonlinear unobservability/uncontrollability analysis. To apply these conditions, one isolates the linear part of the system which is checked to be unobservable/uncontrollable and, if the answer is positive, it is examined whether or not existing nonlinear terms violate the unobservability/uncontrollability property.

Parole chiave

  • nonlinear dynamic systems
  • observability
  • controllability
  • linear systems
  • decomposition
Accesso libero

On the controllability of fractional dynamical systems

Pubblicato online: 28 Sep 2012
Pagine: 523 - 531

Astratto

Abstract

This paper is concerned with the controllability of linear and nonlinear fractional dynamical systems in finite dimensional spaces. Sufficient conditions for controllability are obtained using Schauder’s fixed point theorem and the controllability Grammian matrix which is defined by the Mittag-Leffler matrix function. Examples are given to illustrate the effectiveness of the theory.

Parole chiave

  • controllability
  • fractional differential equations
  • Mittag-Leffler function
Accesso libero

Equivalent descriptions of a discrete-time fractional-order linear system and its stability domains

Pubblicato online: 28 Sep 2012
Pagine: 533 - 538

Astratto

Abstract

Two description forms of a linear fractional-order discrete system are considered. The first one is by a fractional-order difference equation, whereas the second by a fractional-order state-space equation. In relation to the two above-mentioned description forms, stability domains are evaluated. Several simulations of stable, marginally stable and unstable unit step responses of fractional-order systems due to different values of system parameters are presented.

Parole chiave

  • fractional calculus
  • linear discrete-time system
  • stability domain
Accesso libero

A multi-model approach to Saint-Venant equations: A stability study by LMIs

Pubblicato online: 28 Sep 2012
Pagine: 539 - 550

Astratto

Abstract

This paper deals with the stability study of the nonlinear Saint-Venant Partial Differential Equation (PDE). The proposed approach is based on the multi-model concept which takes into account some Linear Time Invariant (LTI) models defined around a set of operating points. This method allows describing the dynamics of this nonlinear system in an infinite dimensional space over a wide operating range. A stability analysis of the nonlinear Saint-Venant PDE is proposed both by using Linear Matrix Inequalities (LMIs) and an Internal Model Boundary Control (IMBC) structure. The method is applied both in simulations and real experiments through a microchannel, illustrating thus the theoretical results developed in the paper.

Parole chiave

  • Saint-Venant equation
  • multi-model
  • LMIs
  • infinite dimensional system
  • exponential stability
  • strongly continuous semigroup
  • internal model boundary control
Accesso libero

H control of discrete-time linear systems constrained in state by equality constraints

Pubblicato online: 28 Sep 2012
Pagine: 551 - 560

Astratto

Abstract

In this paper, stabilizing problems in control design are addressed for linear discrete-time systems, reflecting equality constraints tying together some state variables. Based on an enhanced representation of the bounded real lemma for discretetime systems, the existence of a state feedback control for such conditioned stabilization is proven, and an LMI-based design procedure is provided. The control law gain computation method used circumvents generally an ill-conditioned singular design task. The principle, when compared with previously published results, indicates that the proposed method outperforms the existing approaches, guarantees feasibility, and improves the steady-state accuracy of the control. Furthermore, better performance is achieved with essentially reduced design effort. The approach is illustrated on simulation examples, where the validity of the proposed method is demonstrated using one state equality constraint.

Parole chiave

  • equality constraints
  • discrete-time systems
  • linear matrix inequality
  • state feedback
  • control algorithms, quadratic stability
  • singular systems
Accesso libero

Enclosures for the solution set of parametric interval linear systems

Pubblicato online: 28 Sep 2012
Pagine: 561 - 574

Astratto

Abstract

We investigate parametric interval linear systems of equations. The main result is a generalization of the Bauer–Skeel and the Hansen–Bliek–Rohn bounds for this case, comparing and refinement of both. We show that the latter bounds are not provable better, and that they are also sometimes too pessimistic. The presented form of both methods is suitable for combining them into one to get a more efficient algorithm. Some numerical experiments are carried out to illustrate performances of the methods.

Parole chiave

  • linear interval systems
  • solution set
  • interval matrix
Accesso libero

Variable structure observer design for a class of uncertain systems with a time-varying delay

Pubblicato online: 28 Sep 2012
Pagine: 575 - 583

Astratto

Abstract

Design of a state observer is an important issue in control systems and signal processing. It is well known that it is difficult to obtain the desired properties of state feedback control if some or all of the system states cannot be directly measured. Moreover, the existence of a lumped perturbation and/or a time delay usually reduces the system performance or even produces an instability in the closed-loop system. Therefore, in this paper, a new Variable Structure Observer (VSO) is proposed for a class of uncertain systems subjected to a time varying delay and a lumped perturbation. Based on the strictly positive real concept, the stability of the equivalent error system is verified. Based on the generalized matrix inverse approach, the global reaching condition of the sliding mode of the error system is guaranteed. Also, the proposed variable structure observer will be shown to possess the invariance property in relation to the lumped perturbation, as the traditional variable structure controller does. Furthermore, two illustrative examples with a series of computer simulation studies are given to demonstrate the effectiveness of the proposed design method.

Parole chiave

  • variable structure observer
  • invariance property
  • generalized matrix inverse approach
Accesso libero

Bayesian reliability models of Weibull systems: State of the art

Pubblicato online: 28 Sep 2012
Pagine: 585 - 600

Astratto

Abstract

In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the use of fault trees and reliability diagrams is not possible. To overcome this problem, Bayesian approaches offer a considerable efficiency in this context. This paper introduces recent contributions in the field of reliability modeling with the Bayesian network approach. Bayesian reliability models are applied to systems with Weibull distribution of failure. To achieve the formulation of the reliability model, Bayesian estimation of Weibull parameters and the model’s goodness-of-fit are evoked. The advantages of this modelling approach are presented in the case of systems with an unknown reliability structure, those with a common cause of failures and redundant ones. Finally, we raise the issue of the use of BNs in the fault diagnosis area.

Parole chiave

  • hierarchical modeling
  • reliability
  • Weibull
  • Bayesian networks
  • fault diagnosis
Accesso libero

Modelling and control of an omnidirectional mobile manipulator

Pubblicato online: 28 Sep 2012
Pagine: 601 - 616

Astratto

Abstract

A new approach to control an omnidirectional mobile manipulator is developed. The robot is considered to be an individual agent aimed at performing robotic tasks described in terms of a displacement and a force interaction with the environment. A reactive architecture and impedance control are used to ensure reliable task execution in response to environment stimuli. The mechanical structure of our holonomic mobile manipulator is built of two joint manipulators mounted on a holonomic vehicle. The vehicle is equipped with three driven axles with two spherical orthogonal wheels. Taking into account the dynamical interaction between the base and the manipulator, one can define the dynamics of the mobile manipulator and design a nonlinear controller using the input-state linearization method. The control structure of the robot is built in order to demonstrate the main capabilities regarding navigation and obstacle avoidance. Several simulations were conducted to prove the effectiveness of this approach.

Parole chiave

  • holonome mobile manipulators
  • input state linearization
  • virtual impedance control
  • fuzzy logic
Accesso libero

A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization

Pubblicato online: 28 Sep 2012
Pagine: 617 - 628

Astratto

Abstract

This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Then, particle swarm optimization is employed to finally tune parameters of the obtained fuzzy model. The orthogonal least squares method is used to identify the unknown parameters of the local linear model. Finally, validation results of two examples are given to demonstrate the effectiveness and practicality of the proposed algorithm.

Parole chiave

  • Takagi–Sugeno fuzzy model
  • noise clustering algorithm
  • fuzzy c-regression model
  • orthogonal least squares
  • particle swarm optimization
Accesso libero

Optimal estimator of hypothesis probability for data mining problems with small samples

Pubblicato online: 28 Sep 2012
Pagine: 629 - 645

Astratto

Abstract

The paper presents a new (to the best of the authors’ knowledge) estimator of probability called the “Eph √ 2 completeness estimator” along with a theoretical derivation of its optimality. The estimator is especially suitable for a small number of sample items, which is the feature of many real problems characterized by data insufficiency. The control parameter of the estimator is not assumed in an a priori, subjective way, but was determined on the basis of an optimization criterion (the least absolute errors).The estimator was compared with the universally used frequency estimator of probability and with Cestnik’s m-estimator with respect to accuracy. The comparison was realized both theoretically and experimentally. The results show the superiority of the Eph √ 2 completeness estimator over the frequency estimator for the probability interval ph ∈ (0.1, 0.9). The frequency estimator is better for ph ∈ [0, 0.1] and ph ∈ [0.9, 1].

Parole chiave

  • single-case problem
  • probability
  • probability estimation
  • frequency interpretation of probability
  • completeness interpretation of probability
  • uncertainty theory
Accesso libero

Graph-based generation of a meta-learning search space

Pubblicato online: 28 Sep 2012
Pagine: 647 - 667

Astratto

Abstract

Meta-learning is becoming more and more important in current and future research concentrated around broadly defined data mining or computational intelligence. It can solve problems that cannot be solved by any single, specialized algorithm. The overall characteristic of each meta-learning algorithm mainly depends on two elements: the learning machine space and the supervisory procedure. The former restricts the space of all possible learning machines to a subspace to be browsed by a meta-learning algorithm. The latter determines the order of selected learning machines with a module responsible for machine complexity evaluation, organizes tests and performs analysis of results. In this article we present a framework for meta-learning search that can be seen as a method of sophisticated description and evaluation of functional search spaces of learning machine configurations used in meta-learning. Machine spaces will be defined by specially defined graphs where vertices are specialized machine configuration generators. By using such graphs the learning machine space may be modeled in a much more flexible way, depending on the characteristics of the problem considered and a priori knowledge. The presented method of search space description is used together with an advanced algorithm which orders test tasks according to their complexities.

Parole chiave

  • meta-learning
  • data mining
  • learning machines
  • complexity of learning
  • complexity of learning machines
  • computational intelligence
Accesso libero

Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses

Pubblicato online: 28 Sep 2012
Pagine: 669 - 684

Astratto

Abstract

The increased production of Reactive Oxygen Species (ROS) in plant leaf tissues is a hallmark of a plant’s reaction to various environmental stresses. This paper describes an automatic segmentation method for scanned images of cucurbits leaves stained to visualise ROS accumulation sites featured by specific colour hues and intensities. The leaves placed separately in the scanner view field on a colour background are extracted by thresholding in the RGB colour space, then cleaned from petioles to obtain a leaf blade mask. The second stage of the method consists in the classification of within mask pixels in a hue-saturation plane using two classes, determined by leaf regions with and without colour products of the ROS reaction. At this stage a two-layer, hybrid artificial neural network is applied with the first layer as a self-organising Kohonen type network and a linear perceptron output layer (counter propagation network type). The WTA-based, fast competitive learning of the first layer was improved to increase clustering reliability. Widrow–Hoff supervised training used at the output layer utilises manually labelled patterns prepared from training images. The generalisation ability of the network model has been verified by K-fold cross-validation. The method significantly accelerates the measurement of leaf regions containing the ROS reaction colour products and improves measurement accuracy.

Parole chiave

  • image segmentation
  • colour space
  • morphological processing
  • image thresholding
  • artificial neural network
  • WTA learning
  • Widrow–Hoff learning
  • Cucurbita species
  • plant stress
  • ROS detection
Accesso libero

Neural network based identification of hysteresis in human meridian systems

Pubblicato online: 28 Sep 2012
Pagine: 685 - 694

Astratto

Abstract

Developing a model based digital human meridian system is one of the interesting ways of understanding and improving acupuncture treatment, safety analysis for acupuncture operation, doctor training, or treatment scheme evaluation. In accomplishing this task, how to construct a proper model to describe the behavior of human meridian systems is one of the very important issues. From experiments, it has been found that the hysteresis phenomenon occurs in the relations between stimulation input and the corresponding response of meridian systems. Therefore, the modeling of hysteresis in a human meridian system is an unavoidable task for the construction of model based digital human meridian systems. As hysteresis is a nonsmooth, nonlinear and dynamic system with a multi-valued mapping, the conventional identification method is difficult to be employed to model its behavior directly. In this paper, a neural network based identification method of hysteresis occurring in human meridian systems is presented. In this modeling scheme, an expanded input space is constructed to transform the multi-valued mapping of hysteresis into a one-to-one mapping. For this purpose, a modified hysteretic operator is proposed to handle the extremum-missing problem. Then, based on the constructed expanded input space with the modified hysteretic operator, the so-called Extreme Learning Machine (ELM) neural network is utilized to model hysteresis inherent in human meridian systems. As hysteresis in meridian system is a dynamic system, a dynamic ELMneural network is developed. In the proposed dynamic ELMneural network, the output state of each hidden neuron is fed back to its own input to describe the dynamic behavior of hysteresis. The training of the recurrent ELM neural network is based on the least-squares algorithm with QR decomposition.

Parole chiave

  • acupuncture point
  • hysteresis
  • identification
  • neural networks
  • human meridian
  • traditional Chinese medicine
Accesso libero

A survey of subpixel edge detection methods for images of heat-emitting metal specimens

Pubblicato online: 28 Sep 2012
Pagine: 695 - 710

Astratto

Abstract

In this paper the problem of accurate edge detection in images of heat-emitting specimens of metals is discussed. The images are provided by the computerized system for high temperature measurements of surface properties of metals and alloys. Subpixel edge detection is applied in the system considered in order to improve the accuracy of surface tension determination. A reconstructive method for subpixel edge detection is introduced. The method uses a Gaussian function in order to reconstruct the gradient function in the neighborhood of a coarse edge and to determine its subpixel position. Results of applying the proposed method in the measurement system considered are presented and compared with those obtained using different methods for subpixel edge detection.

Parole chiave

  • subpixel accuracy
  • edge detection
  • surface property
  • approximation
  • Gaussian function
Accesso libero

KIS: An automated attribute induction method for classification of DNA sequences

Pubblicato online: 28 Sep 2012
Pagine: 711 - 721

Astratto

Abstract

This paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites. We also show how to use the algorithm to find a human readable model of the IRE (Iron-Responsive Element) and to find IRE sequences. The method, although universal, yields results which are of quality comparable to those obtained by reference methods. In contrast to reference methods, this approach uses models that operate on sequence patterns, which facilitates interpretation of the results by humans.

Parole chiave

  • classification
  • optimization
  • annotation
  • patterns
Accesso libero

Modeling nonlinear road traffic networks for junction control

Pubblicato online: 28 Sep 2012
Pagine: 723 - 732

Astratto

Abstract

The paper introduces a method of mathematical modeling of high scale road traffic networks, where a new special hypermatrix structure is intended to be used. The structure describes the inner–inner, inner–outer and outer–outer relations, and laws of a network area. The research examines the nonlinear equation system. The analysed model can be applied to the testing and planning of large-scale road traffic networks and the regulation of traffic systems. The elaborated model is in state space form, where the states are vehicle densities on a particular lane and the dynamics are described by a nonlinear state constrained positive system. This model can be used directly for simulation and analysis and as a starting point for investigating various control strategies. The stability of the traffic over the network can be analyzed by constructing a linear Lyapunov function and the associated theory. The model points out that in intersection control one must take the traffic density values of both the input and the output sections into account. Generally, the control of any domain has to take the density of input and output sections into consideration.

Parole chiave

  • mathematical modeling and control
  • traffic networks
  • nonlinear positive system
  • linear Lyapunov function
Accesso libero

Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems

Pubblicato online: 28 Sep 2012
Pagine: 733 - 748

Astratto

Abstract

Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P approach to distribute results of computational projects, i.e., results are transmitted in the system like in P2P file sharing systems (e.g., BitTorrent). In this work, we concentrate on offline optimization of the P2P computing system including two elements: scheduling of computations and data distribution. The objective is to minimize the system OPEX cost related to data processing and data transmission. We formulate an Integer Linear Problem (ILP) to model the system and apply this formulation to obtain optimal results using the CPLEX solver. Next, we propose two heuristic algorithms that provide results very

Parole chiave

  • P2P computing system
  • distributed computing
  • optimization
  • heuristics
  • evolutionary algorithms
Accesso libero

Joint queue-perturbed and weakly coupled power control for wireless backbone networks

Pubblicato online: 28 Sep 2012
Pagine: 749 - 764

Astratto

Abstract

Wireless Backbone Networks (WBNs) equipped with Multi-Radio Multi-Channel (MRMC) configurations do experience power control problems such as the inter-channel and co-channel interference, high energy consumption at multiple queues and unscalable network connectivity. Such network problems can be conveniently modelled using the theory of queue perturbation in the multiple queue systems and also as a weak coupling in a multiple channel wireless network. Consequently, this paper proposes a queue perturbation and weakly coupled based power control approach forWBNs. The ultimate objectives are to increase energy efficiency and the overall network capacity. In order to achieve this objective, a Markov chain model is first presented to describe the behaviour of the steady state probability distribution of the queue energy and buffer states. The singular perturbation parameter is approximated from the coefficients of the Taylor series expansion of the probability distribution. The impact of such queue perturbations on the transmission probability, given some transmission power values, is also analysed. Secondly, the inter-channel interference is modelled as a weakly coupled wireless system. Thirdly, Nash differential games are applied to derive optimal power control signals for each user subject to power constraints at each node. Finally, analytical models and numerical examples show the efficacy of the proposed model in solving power control problems in WBNs.

Parole chiave

  • decentralized power control
  • singular perturbation theory
  • weak coupling theory
  • wireless backbone networks
  • optimal control theory
Accesso libero

The Fan–Raspaud conjecture: A randomized algorithmic approach and application to the pair assignment problem in cubic networks

Pubblicato online: 06 Oct 2012
Pagine: 765 - 778

Astratto

Abstract

It was conjectured by Fan and Raspaud (1994) that every bridgeless cubic graph contains three perfect matchings such that every edge belongs to at most two of them. We show a randomized algorithmic way of finding Fan–Raspaud colorings of a given cubic graph and, analyzing the computer results, we try to find and describe the Fan–Raspaud colorings for some selected classes of cubic graphs. The presented algorithms can then be applied to the pair assignment problem in cubic computer networks. Another possible application of the algorithms is that of being a tool for mathematicians working in the field of cubic graph theory, for discovering edge colorings with certain mathematical properties and formulating new conjectures related to the Fan–Raspaud conjecture.

Parole chiave

  • cubic graph
  • edge coloring
  • perfect matching
  • randomized algorithms
  • computer networks

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