Journal of the University of Zielona Góra

International Journal of Applied Mathematics and Computer Science

Int.Jnl Appl.Math.Comp.Sci.ONL

<abstract xml:lang="en"><title style='display:none'>A well-posed multiscale regularization scheme for digital image denoising</title>We propose an edge adaptive digital image denoising and restoration scheme based on space dependent regularization. Traditional gradient based schemes use an edge map computed from gradients alone to drive the regularization. This may lead to the oversmoothing of the input image, and noise along edges can be amplified. To avoid these drawbacks, we make use of a multiscale descriptor given by a contextual edge detector obtained from local variances. Using a smooth transition from the computed edges, the proposed scheme removes noise in flat regions and preserves edges without oscillations. By incorporating a space dependent adaptive regularization parameter, image smoothing is driven along probable edges and not across them. The well-posedness of the corresponding minimization problem is proved in the space of functions of bounded variation. The corresponding gradient descent scheme is implemented and further numerical results illustrate the advantages of using the adaptive parameter in the regularization scheme. Compared with similar edge preserving regularization schemes, the proposed adaptive weight based scheme provides a better multiscale edge map, which in turn produces better restoration.</abstract>

A well-posed multiscale regularization scheme for digital image denoising

Department of Mathematics, University of Coimbra, Apartado 3008, 3001-454 Coimbra, Portugal

Keywords

<article-title>A well-posed multiscale regularization scheme for digital image denoising</article-title>

{"article-title":"A well-posed multiscale regularization scheme for digital image denoising"}

<abstract xml:lang="en"><title style='display:none'>Intelligent decision-making system for autonomous robots</title>The paper gives an account of research results concerning a project on creating a fully autonomous robotic decision-making system, able to interact with its environment and based on a mathematical model of human cognitive-behavioural psychology, with some key elements of personality psychology included. The principal idea of the paper is focused on the concept of needs, with a certain instrumental role of emotions.</abstract>

Intelligent decision-making system for autonomous robots

Decision Systems Department, Faculty of Electronics, Telecommunications and Informatics Gdańsk University of Technology, Narutowicza 11/12, 80-233, Gdańsk, Poland

<article-title>Intelligent decision-making system for autonomous robots</article-title>

{"article-title":"Intelligent decision-making system for autonomous robots"}

<abstract xml:lang="en"><title style='display:none'>Adaptive control scheme based on the least squares support vector machine network</title>Recently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified structure of LS-SVM neural networks called the multi-resolution wavelet least squares support vector machine network (MRWLS-SVM) as a predictor model, and the controller part that is developed to track a reference trajectory. By means of the Lyapunov stability criterion, stability analysis for the tracking errors is performed. Finally, simulation studies are performed to demonstrate the capability of the developed approach in controlling a pH process.</abstract>

Adaptive control scheme based on the least squares support vector machine network

Industrial Electronics and Control Engineering Department Faculty of Electronic Engineering, Menoufia University, Menouf 32952, El-Menoufiya, Egypt

<article-title>Adaptive control scheme based on the least squares support vector machine network</article-title>

<abstract xml:lang="en"><title style='display:none'>LMI-based adaptive fuzzy integral sliding mode control of mismatched uncertain systems</title>Integral sliding mode design is considered for a class of uncertain systems in the presence of mismatched uncertainties in both state and input matrices, as well as norm-bounded nonlinearities and external disturbances. A sufficient condition for the robust stability of the sliding manifold is derived by means of linear matrix inequalities. The initial existence of the sliding mode is guaranteed by the proposed control law. The improvement of the proposed control scheme performances, such as chattering elimination and estimation of norm bounds of uncertainties, is then considered with the application of an adaptive fuzzy integral sliding mode control law. The validity and efficiency of the proposed approaches are investigated through a sixth order uncertain mechanical system.</abstract>

LMI-based adaptive fuzzy integral sliding mode control of mismatched uncertain systems

Research Unit in Automatic Control and Industrial Computing, URAII National Institute of Applied Sciences and Technology, INSAT Carthage University, Zone urbaine Nord, BP 676, Tunis Cedex, 1080, Tunisia

<article-title>LMI-based adaptive fuzzy integral sliding mode control of mismatched uncertain systems</article-title>

<abstract xml:lang="en"><title style='display:none'>Delay-dependent generalized <italic>H</italic>2 control for discrete T-S fuzzy large-scale stochastic systems with mixed delays</title>This paper is concerned with the problem of stochastic stability and generalized <italic>H</italic>2 control for discrete-time fuzzy large-scale stochastic systems with time-varying and infinite-distributed delays. Large-scale interconnected systems consist of a number of discrete-time interconnected Takagi-Sugeno (T-S) subsystems. First, a novel Delay-Dependent Piecewise Lyapunov-Krasovskii Functional (DDPLKF) is proposed, in which both the upper and the lower bound of delays are considered. Then, two improved delay-dependent stability conditions are established based on this DDPLKF in terms of Linear Matrix Inequalities (LMIs). The merit of the proposed conditions lies in its reduced conservatism, which is achieved by circumventing the utilization of some bounding inequalities for cross products of two vectors and by considering the interactions among the fuzzy subsystems in each subregion. A decentralized generalized <italic>H</italic>2 state feedback fuzzy controller is designed for each subsystem. It is shown that the mean-square stability for discrete T-S fuzzy large-scale stochastic systems can be established if a DDPLKF can be constructed and a decentralized controller can be obtained by solving a set of LMIs. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed method.</abstract>

Delay-dependent generalized  control for discrete T-S fuzzy large-scale stochastic systems with mixed delays

School of Science, Xidian University, South Taibai Rd 2, Xi'an, 710071, PR China

College of Mathematics and Computer Science, Yanan University, Yangjialing, Yan'an, 716000, PR China

School of Mathematics and Information Engineering, Taizhou University, Shifu Rd 1139, Taizhou, 317000, PR China

<article-title>Delay-dependent generalized <italic>H</italic>2 control for discrete T-S fuzzy large-scale stochastic systems with mixed delays</article-title>

<abstract xml:lang="en"><title style='display:none'>Evolving small-board Go players using coevolutionary temporal difference learning with archives</title>We apply Coevolutionary Temporal Difference Learning (CTDL) to learn small-board Go strategies represented as weighted piece counters. CTDL is a randomized learning technique which interweaves two search processes that operate in the intra-game and inter-game mode. Intra-game learning is driven by gradient-descent Temporal Difference Learning (TDL), a reinforcement learning method that updates the board evaluation function according to differences observed between its values for consecutively visited game states. For the inter-game learning component, we provide a coevolutionary algorithm that maintains a sample of strategies and uses the outcomes of games played between them to iteratively modify the probability distribution, according to which new strategies are generated and added to the sample. We analyze CTDL's sensitivity to all important parameters, including the trace decay constant that controls the lookahead horizon of TDL, and the relative intensity of intra-game and inter-game learning. We also investigate how the presence of memory (an archive) affects the search performance, and find out that the archived approach is superior to other techniques considered here and produces strategies that outperform a handcrafted weighted piece counter strategy and simple liberty-based heuristics. This encouraging result can be potentially generalized not only to other strategy representations used for small-board Go, but also to various games and a broader class of problems, because CTDL is generic and does not rely on any problem-specific knowledge.</abstract>

Evolving small-board Go players using coevolutionary temporal difference learning with archives

Institute of Computing Science, Poznań University of Technology, ul. Piotrowo 2, 60-965 Poznań, Poland

<article-title>Evolving small-board Go players using coevolutionary temporal difference learning with archives</article-title>

<abstract xml:lang="en"><title style='display:none'>Optimization-based approach to path planning for closed chain robot systems</title>An application of advanced optimization techniques to solve the path planning problem for closed chain robot systems is proposed. The approach to path planning is formulated as a "quasi-dynamic" NonLinear Programming (NLP) problem with equality and inequality constraints in terms of the joint variables. The essence of the method is to find joint paths which satisfy the given constraints and minimize the proposed performance index. For numerical solution of the NLP problem, the IPOPT solver is used, which implements a nonlinear primal-dual interior-point method, one of the leading techniques for large-scale nonlinear optimization.</abstract>

Optimization-based approach to path planning for closed chain robot systems

Institute of Control and Computation Engineering, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665 Warsaw, Poland

Research and Academic Computer Network (NASK), ul. Wąwozowa 18, 02-796 Warsaw, Poland

<article-title>Optimization-based approach to path planning for closed chain robot systems</article-title>

{"article-title":"Optimization-based approach to path planning for closed chain robot systems"}

<abstract xml:lang="en"><title style='display:none'>Fault tolerance in networked control systems under intermittent observations</title>This paper presents an approach to fault tolerant control based on the sensor masking principle in the case of wireless networked control systems. With wireless transmission, packet losses act as sensor faults. In the presence of such faults, the faulty measurements corrupt directly the behaviour of closed-loop systems. Since the controller aims at cancelling the error between the measurement and its reference input, the real outputs will, in such a networked control system, deviate from the desired value and may drive the system to its physical limitations or even to instability. The proposed method facilitates fault compensation based on an interacting multiple model approach developed in the framework of channel errors or network congestion equivalent to multiple sensors failures. The interacting multiple model method involved in a networked control system provides simultaneously detection and isolation of on-line packet losses, and also performs a suitable state estimation. Based on particular knowledge of packet losses, sensor fault-tolerant controls are obtained by computing a new control law using fault-free estimation of the faulty element to avoid intermittent observations that might develop into failures and to minimize the effects on system performance and safety.</abstract>

Fault tolerance in networked control systems under intermittent observations

Nancy Research Centre for Automatic Control, Nancy University, CNRS, B.P. 70239 F-54506 Vandœuvre les Nancy, France

Automatic Control, Computer Science and Signal Processing Laboratory, LAGIS FRE CNRS 3303 Polytech'Lille, Bât. D, 59655 Villeneuve d'Ascq Cedex, France

<article-title>Fault tolerance in networked control systems under intermittent observations</article-title>

{"article-title":"Fault tolerance in networked control systems under intermittent observations"}

<abstract xml:lang="en"><title style='display:none'>Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays</title>Fuzzy cellular neural networks with time-varying delays are considered. Some sufficient conditions for the existence and exponential stability of periodic solutions are obtained by using the continuation theorem based on the coincidence degree and the differential inequality technique. The sufficient conditions are easy to use in pattern recognition and automatic control. Finally, an example is given to show the feasibility and effectiveness of our methods.</abstract>

Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays

Guizhou Key Laboratory of Economic Systems Simulation, School of Mathematics and Statistics, Guizhou College of Finance and Economics, Guiyang, Guizhou 550004, PR China

Department of Mathematics, Hunan City University, Yiyang, Hunan 413000, PR China

Basic Science Department, Hunan Institute of Technology, Hengyang, Hunan 421002, PR China

<article-title>Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays</article-title>

<abstract xml:lang="en"><title style='display:none'>Knowledge discovery in data using formal concept analysis and random projections</title>In this paper our objective is to propose a random projections based formal concept analysis for knowledge discovery in data. We demonstrate the implementation of the proposed method on two real world healthcare datasets. Formal Concept Analysis (FCA) is a mathematical framework that offers a conceptual knowledge representation through hierarchical conceptual structures called concept lattices. However, during the design of a concept lattice, complexity plays a major role.</abstract>

Knowledge discovery in data using formal concept analysis and random projections

Networks and Information Security Division, School of Information Technology and Engineering, VIT University, Vellore, India

<article-title>Knowledge discovery in data using formal concept analysis and random projections</article-title>

{"article-title":"Knowledge discovery in data using formal concept analysis and random projections"}

<abstract xml:lang="en"><title style='display:none'>Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances</title>This paper studies recursive optimal filtering as well as robust fault and state estimation for linear stochastic systems with unknown disturbances. It proposes a new recursive optimal filter structure with transformation of the original system. This transformation is based on the singular value decomposition of the direct feedthrough matrix distribution of the fault which is assumed to be of arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum-variance criteria. Two numerical examples are given in order to illustrate the proposed method, in particular to solve the estimation of the simultaneous actuator and sensor fault problem and to make a comparison with the existing literature results.</abstract>

Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances

Research Unit on Control, Monitoring and Safety of Systems (C3S), High School of Sciences and Techniques of Tunis (ESSTT), 5 av. Taha Hussein, BP 56-1008 Tunis, Tunisia

Research Centre in Automation of Nancy (CRAN), Nancy University, CNRS, BP 239, 54506 Vandoeuvre Cedex, France

<article-title>Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances</article-title>

<abstract xml:lang="en"><title style='display:none'>A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems</title>Constraint programming is a powerful software technology for solving numerous real-life problems. Many of these problems can be modeled as Constraint Satisfaction Problems (CSPs) and solved using constraint programming techniques. However, solving a CSP is NP-complete so filtering techniques to reduce the search space are still necessary. Arc-consistency algorithms are widely used to prune the search space. The concept of arc-consistency is bidirectional, i.e., it must be ensured in both directions of the constraint (direct and inverse constraints). Two of the most well-known and frequently used arc-consistency algorithms for filtering CSPs are AC3 and AC4. These algorithms repeatedly carry out revisions and require support checks for identifying and deleting all unsupported values from the domains. Nevertheless, many revisions are ineffective, i.e., they cannot delete any value and consume a lot of checks and time. In this paper, we present AC4-OP, an optimized version of AC4 that manages the binary and non-normalized constraints in only one direction, storing the inverse founded supports for their later evaluation. Thus, it reduces the propagation phase avoiding unnecessary or ineffective checking. The use of AC4-OP reduces the number of constraint checks by 50% while pruning the same search space as AC4. The evaluation section shows the improvement of AC4-OP over AC4, AC6 and AC7 in random and non-normalized instances.</abstract>

A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems

Institute of Industrial Informatics and Automatics, Technical University of Valencia, Camino de Vera, s/n. 46020 Valencia, Spain

<article-title>A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems</article-title>

<abstract xml:lang="en"><title style='display:none'>Estimation of feedwater heater parameters based on a grey-box approach</title>The first-principle modeling of a feedwater heater operating in a coal-fired power unit is presented, along with a theoretical discussion concerning its structural simplifications, parameter estimation, and dynamical validation. The model is a part of the component library of modeling environments, called the Virtual Power Plant (VPP). The main purpose of the VPP is simulation of power generation installations intended for early warning diagnostic applications. The model was developed in the Matlab/Simulink package. There are two common problems associated with the modeling of dynamic systems. If an analytical model is chosen, it is very costly to determine all model parameters and that often prevents this approach from being used. If a data model is chosen, one does not have a clear interpretation of the model parameters. The paper uses the so-called grey-box approach, which combines first-principle and data-driven models. The model is represented by nonlinear state-space equations with geometrical and physical parameters deduced from the available documentation of a feedwater heater, as well as adjustable phenomenological parameters (i.e., heat transfer coefficients) that are estimated from measurement data. The paper presents the background of the method, its implementation in the Matlab/Simulink environment, the results of parameter estimation, and a discussion concerning the accuracy of the method.</abstract>

Estimation of feedwater heater parameters based on a grey-box approach

Department of Robotics and Mechatronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Cracow, Poland

<article-title>Estimation of feedwater heater parameters based on a grey-box approach</article-title>

{"article-title":"Estimation of feedwater heater parameters based on a grey-box approach"}

<abstract xml:lang="en"><title style='display:none'>Observer-based fault-tolerant control against sensor failures for fuzzy systems with time delays</title>This paper addresses the problems of robust fault estimation and fault-tolerant control for Takagi-Sugeno (T-S) fuzzy systems with time delays and unknown sensor faults. A fuzzy augmented state and fault observer is designed to achieve the system state and sensor fault estimates simultaneously. Furthermore, based on the information of on-line fault estimates, an observer-based dynamic output feedback fault-tolerant controller is developed to compensate for the effect of faults by stabilizing the resulting closed-loop system. Sufficient conditions for the existence of both a state observer and a fault-tolerant controller are given in terms of linear matrix inequalities. A simulation example is given to illustrate the effectiveness of the proposed approach.</abstract>

Observer-based fault-tolerant control against sensor failures for fuzzy systems with time delays

Department of Mathematics, Liaoning University of Technology, 169 Shiying Street, Guta District, Jinzhou, 121001, PR China

<article-title>Observer-based fault-tolerant control against sensor failures for fuzzy systems with time delays</article-title>

<abstract xml:lang="en"><title style='display:none'>Partitioned iterated function systems with division and a fractal dependence graph in recognition of 2D shapes</title>One of the approaches in pattern recognition is the use of fractal geometry. The property of self-similarity of fractals has been used as a feature in several pattern recognition methods. All fractal recognition methods use global analysis of the shape. In this paper we present some drawbacks of these methods and propose fractal local analysis using partitioned iterated function systems with division. Moreover, we introduce a new fractal recognition method based on a dependence graph obtained from the partitioned iterated function system. The proposed method uses local analysis of the shape, which improves the recognition rate. The effectiveness of our method is shown on two test databases. The first one was created by the authors and the second one is the MPEG7 CE-Shape-1 PartB database. The obtained results show that the proposed methodology has led to a significant improvement in the recognition rate.</abstract>

Partitioned iterated function systems with division and a fractal dependence graph in recognition of 2D shapes

Institute of Computer Science, University of Silesia, Będzińska 39, 41-200 Sosnowiec, Poland

<article-title>Partitioned iterated function systems with division and a fractal dependence graph in recognition of 2D shapes</article-title>

<abstract xml:lang="en"><title style='display:none'>Positive stable realizations of fractional continuous-time linear systems</title>Conditions for the existence of positive stable realizations with system Metzler matrices for fractional continuous-time linear systems are established. A procedure based on the Gilbert method for computation of positive stable realizations of proper transfer matrices is proposed. It is shown that linear minimum-phase systems with real negative poles and zeros always have positive stable realizations.</abstract>

Positive stable realizations of fractional continuous-time linear systems

Faculty of Electrical Engineering, Białystok Technical University, ul. Wiejska 45D, 15-351 Białystok, Poland

<article-title>Positive stable realizations of fractional continuous-time linear systems</article-title>

{"article-title":"Positive stable realizations of fractional continuous-time linear systems"}

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Editor-in-Chief <A href="http://staff.uz.zgora.pl/jkorbicz/">Józef Korbicz</A>, University of Zielona Góra, Poland Deputy Editor <A href="http://staff.uz.zgora.pl/ducinski/viewpage.php?page_id=12">Dariusz Uciński</A>, University of Zielona Góra, Poland Associate Editors Harald ASCHEMANN, University of Rostock, Germany Jérôme CIESLAK, University of Bordeaux, France Martin GUGAT, Friedrich-Alexander University of Erlangen-Nuremberg, Germany Marios M. POLYCARPOU, University of Cyprus, Nicosia, Cyprus Silvio SIMANI, University of Ferrara, Italy Jerzy STEFANOWSKI, Poznań University of Technology, Poland Guisheng ZHAI, Shibaura Institute of Technology, Tokyo, Japan Board Members Cherukuri ASWANI KUMAR, VIT University, Vellore, India Czesław BAJER, Polish Academy of Sciences, Warsaw, Poland Andrzej BARTOSZEWICZ, Technical University of Łódź, Poland Miguel BERNAL, Sonora Institute of Technology (ITSON), Obregón, Mexico Kishore BINGI, Vellore Institute of Technology, India Paolo CASTALDI, University of Bologna, Italy Zhaohui CEN, Qatar Enviroment and Energy Research Institute, Ar Rayyan, Qatar Bogusław CYGANEK, AGH University of Science and Technology, Cracow, Poland Stefan DOMEK, West Pomeranian University of Technology in Szczecin, Poland Andrzej DZIELIŃSKI, Warsaw University of Technology, Poland Anna FABIJAŃSKA, Lodz University of Technology, Poland Marcin GORAWSKI, Silesian University of Technology, Gliwice, Poland Michał GROCHOWSKI, Gdańsk University of Technology, Poland Xiao HE, Tsinghua University, Beijing, China Janusz KACPRZYK, Polish Academy of Sciences, Warsaw, Poland Jerzy KLAMKA, Polish Academy of Sciences, Gliwice, Poland Jacek KLUSKA, Rzeszów University of Technology, Poland Joanna KOŁODZIEJ, Cracow University of Technology, Poland Jan M. KOŚCIELNY, Warsaw University of Technology, Poland Zdzisław KOWALCZUK, Gdańsk University of Technology, Poland Adam KRZYZAK, Concordia University, Montreal, Canada Piotr KULCZYCKI, AGH University of Science and Technology, Cracow, Poland Maciej KUSY, Rzeszów University of Technology, Poland Francisco-Ronay LÓPEZ-ESTRADA, Technological Institute of Tuxtla Gutiérrez, Mexico Maciej ŁAWRYŃCZUK, Warsaw University of Technology, Poland Vyacheslav MAKSIMOV, Russian Academy of Sciences, Ekaterinburg, Russia Krzysztof MALINOWSKI, Warsaw University of Technology, Poland Wojciech MITKOWSKI, AGH University of Science and Technology, Cracow, Poland Gang NIU, Tongji University, Shanghai, China Ronald J. PATTON, University of Hull, UK Jimoh O. PEDRO, University of the Witwatersrand, Johannesburg, South Africa Witold PEDRYCZ, University of Alberta, Edmonton, Canada Piotr PORWIK, University of Silesia in Katowice, Poland Vicenç PUIG, Technical University of Catalonia, Barcelona, Spain Jianbin QIU, Harbin Institute of Technology, China Ewaryst RAFAJŁOWICZ, Wrocław University of Technology, Poland Rotislav RAZUMCHIK, Russian Academy of Sciences, Moscow, Russia Leszek RUTKOWSKI, Technical University of Częstochowa, Poland Andrey V. SAVCHENKO, National Research University HSE, Nizhny Novgorod, Russia Piotr SKRZYPCZYŃSKI, Poznań University of Technology, Poland Roman SŁOWIŃSKI, Poznań University of Technology, Poland Florin STOICAN, University POLITEHNICA of Bucharest, Romania Andrzej ŚWIERNIAK, Silesian University of Technology, Gliwice, Poland Zoltán SZABÓ, Hungarian Academy of Sciences, Budapest, Hungary Ryszard TADEUSIEWICZ, AGH University of Science and Technology, Cracow, Poland Didier THEILLIOL, University of Lorraine, Nancy, France Haoping WANG, Nanjing University of Science and Technology, China Marcin WITCZAK, University of Zielona Góra, Poland Baozhen YAO, Dalian University of Technology, China Shen YIN, Harbin Institute of Technology, China Alexey ZHIRABOK, Far Eastern Federal University, Vladivostok, Russia Teresa ZIELIŃSKA, Warsaw University of Technology, Poland Jacek M. ZURADA, University of Louisville, USA Editorial Office Agnieszka Rożewska, University of Zielona Góra, Poland – Manager Agata Wiśniewska-Kubicka, University of Zielona Góra, Poland – Technical Editor Contact AMCS Editorial Office University of Zielona Góra, Institute of Control and Computation Engineering ul. prof. Z. Szafrana 2 65-516 Zielona Góra phone: +48683282506 e-mail: <A href="mailto:amcs@uz.zgora.pl">amcs@uz.zgora.pl</A> website: <A href="http://www.amcs.uz.zgora.pl/">www.amcs.uz.zgora.pl</A> Publisher De Gruyter Poland Bogumiła Zuga 32A Str. 01-811 Warsaw, Poland Acknowledgement Electronic publication of Volume 26 (2016, Nos. 1-4) has been financed with the funds of the Polish Ministry of Science and Higher Education for science promoting activities within the agreement no. 904/P-DUN/2016 <A href="http://www.nauka.gov.pl/en/"><IMG alt="" src="https://www.degruyter.com/staticfiles/images/mnisw_opt.jpg"></A>

Click <A href="http://www.amcs.uz.zgora.pl/?action=guide">here</A> for more information. Article processing charge (APC) The authors are expected to pay a publication charge for each paper, which covers the costs of the publishing process and will be processed following paper acceptance. Details are available at <A href="https://www.amcs.uz.zgora.pl/?action=guide">https://www.amcs.uz.zgora.pl/?action=guide</A>. <A href="https://www.amcs.uz.zgora.pl/downloads/Instructions_AMCS.pdf">Instructions for authors</A> The style of papers submitted to AMCS is determined by a special LaTeX class, which is described in detail in our instructions for authors. Details are available at <A href="https://www.amcs.uz.zgora.pl/?action=guide">https://www.amcs.uz.zgora.pl/?action=guide</A>. Peer review Papers submitted for possible publication in AMCS are initially evaluated by the editors with regard to their suitability for the journal. This refers most of all to the content and its scientific quality. Papers with insufficient contribution to our fields of interest and/or poor organisation and/or not prepared in the required style are rejected without delay so that the authors can improve or submit their work elsewhere. The manuscripts that are ultimately registered are submitted to 3-4 qualified, impartial reviewers for half-blind thorough scientific evaluation via the AMCS online editorial system. Papers are accepted unconditionally if the reviewers agree that they may be published in their present form. Otherwise, the reviews are forwarded to the authors for paper revision and comments on the reviewers' remarks. Paper revisions are submitted for re-review if requested by the reviewers or justified by the editors. The final decision on paper publication (accept/reject) is made by the editors and is not subject to appeal nor justification. The full review process takes approximately 4 months, but the editors do not set a deadline for the final decision. A general list of all reviewers for a given volume will be published on the journal website and in the closing issue. Details are available at <A href="https://www.amcs.uz.zgora.pl/?action=guide">https://www.amcs.uz.zgora.pl/?action=guide</A>. Open access statement The journal is an Open Access journal that allows a free unlimited access to all its contents without any restrictions upon publication to all users. <A href="https://www.amcs.uz.zgora.pl/downloads/License_AMCS.pdf">Open access license</A> The authors must sign the license to publish upon paper acceptance. The license governs in detail the commercial and non-commercial use of papers published by our journal, and determines user and author rights. Copyrights policy Papers published currently are available for non-commercial use under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 (CC BY-NC-ND 3.0) license. Details are available at <A href="https://www.amcs.uz.zgora.pl/?action=online">https://www.amcs.uz.zgora.pl/?action=online</A>.

<DIV align=left> The International Journal of Applied Mathematics and Computer Science is a quarterly published in Poland since 1991 by the University of Zielona Góra in partnership with De Gruyter Poland (Sciendo) and historically with Lubuskie Scientific Society, under the auspices of the Committee on Automatic Control and Robotics of the Polish Academy of Sciences. The journal strives to meet the demand for the presentation of interdisciplinary research in various fields related to control theory, applied mathematics, scientific computing and computer science. In particular, it publishes high quality original research results in the following areas: <UL> <LI>modern control theory and practice, </LI> <LI>artificial intelligence methods and their applications, </LI> <LI>applied mathematics and mathematical optimisation techniques, </LI> <LI>mathematical methods in engineering, computer science, and biology. </LI> </UL> We are primarily interested in presenting theoretical and application-orientated full-length research papers dealing with the following topics: <UL> <LI>control theory, including optimal control, system identification, adaptive and robust control, multivariable control, and non-linear systems, </LI> <LI>dynamical systems, including spatiotemporal processes, control problems, state and parameter estimation, and sensor networks, </LI> <LI>fault detection and diagnosis, including model-based approaches, observers, and classifiers, </LI> <LI>fault-tolerant control, including the control of continuous-variable and quantised systems, </LI> <LI>robotics, including modelling and simulation, mobile robots, and optimal trajectory planning, </LI> <LI>mathematical modelling and simulation, including numerical algorithms, </LI> <LI>optimisation, including mathematical optimisation techniques, global optimisation, and evolutionary algorithms, </LI> <LI>artificial intelligence, including machine and deep learning, neural networks, knowledge engineering, fuzzy systems, and search methods, </LI> <LI>data mining, data and image processing, and big data, </LI> <LI>classification and pattern recognition, </LI> <LI>biomedical engineering and biomathematics, </LI> <LI>applications in engineering and medicine. </LI> </UL> The editors welcome proposals for exchange between similar journals. Also, all persons interested in bringing out special issues or sections of AMCS are encouraged to contact the Editor-in-Chief. Specials may be published on any important and timely subject within the scope of the journal. All papers proposed for special issues or sections will be refereed and have to meet the same criteria for scientific quality as articles presented in regular issues. Also, all journal rules and guidelines refer to papers published in specials without any exceptions. ISSN: 1641-876X (print version), 2083-8492 (online version) Why subscribe and read <UL> <LI>Premier source of high quality research from all over the world, with special emphasis on papers from Central and Eastern Europe, </LI> <LI>over twenty years of experience in publishing original articles dealing with various aspects of applying mathematical methods to computer science and engineering, </LI> <LI>extensive scope covering, among other things, control systems, optimization, robotics, mathematical and numerical modeling, artificial intelligence, knowledge processing, fault detection and diagnostics, </LI> <LI>one of the fastest growing journals published in Central and Eastern Europe. </LI></UL> Why submit <UL> <LI>Fast, fair, competent and comprehensive peer review (two or three referees are designated for the assessment of each manuscript), </LI> <LI>fast and efficient publication process, </LI> <LI>thorough language correction for authors who are not native English speakers, </LI> <LI>polishing the structure and technical format of each submission, </LI> <LI>promotion of published papers in the vast scientific community of researchers working in the field. </LI></UL> Archiving Sciendo archives the contents of this journal in <A href="https://www.portico.org/">Portico</A> - digital long-term preservation service of scholarly books, journals and collections. Plagiarism policy The editorial board is participating in a growing community of <A href="https://www.crossref.org/services/similarity-check/">Similarity Check System's</A> users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. </DIV>

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

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

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

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Volumen 21 (2011): Heft 4 (December 2011)

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