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 30 (2020): Edizione 1 (March 2020)

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

15 Articoli
Accesso libero

Input Reconstruction by Feedback Control for the Schlögl and FitzHugh–Nagumo Equations

Pubblicato online: 03 Apr 2020
Pagine: 5 - 22

Astratto

Abstract

Dynamical reconstruction of unknown time-varying controls from inexact measurements of the state function is investigated for a semilinear parabolic equation with memory. This system includes as particular cases the Schlögl model and the FitzHugh–Nagumo equations. A numerical method is suggested that is based on techniques of feedback control. An error analysis is performed. Numerical examples confirm the theoretical predictions.

Parole chiave

  • semilinear parabolic equation
  • input reconstruction
Accesso libero

An Information Based Approach to Stochastic Control Problems

Pubblicato online: 03 Apr 2020
Pagine: 23 - 34

Astratto

Abstract

An information based method for solving stochastic control problems with partial observation is proposed. First, information-theoretic lower bounds of the cost function are analysed. It is shown, under rather weak assumptions, that reduction in the expected cost with closed-loop control compared with the best open-loop strategy is upper bounded by a non-decreasing function of mutual information between control variables and the state trajectory. On the basis of this result, an information based control (IBC) method is developed. The main idea of IBC consists in replacing the original control task by a sequence of control problems that are relatively easy to solve and such that information about the system state is actively generated. Two examples of the IBC operation are given. It is shown that the method is able to find an optimal solution without using dynamic programming at least in these examples. Hence the computational complexity of IBC is substantially smaller than that of dynamic programming, which is the main advantage of the proposed method.

Parole chiave

  • stochastic control
  • feedback
  • information
  • entropy
Accesso libero

Nonlinear Model Predictive Control for Processes with Complex Dynamics: A Parameterisation Approach Using Laguerre Functions

Pubblicato online: 03 Apr 2020
Pagine: 35 - 46

Astratto

Abstract

Classical model predictive control (MPC) algorithms need very long horizons when the controlled process has complex dynamics. In particular, the control horizon, which determines the number of decision variables optimised on-line at each sampling instant, is crucial since it significantly affects computational complexity. This work discusses a nonlinear MPC algorithm with on-line trajectory linearisation, which makes it possible to formulate a quadratic optimisation problem, as well as parameterisation using Laguerre functions, which reduces the number of decision variables. Simulation results of classical (not parameterised) MPC algorithms and some strategies with parameterisation are thoroughly compared. It is shown that for a benchmark system the MPC algorithm with on-line linearisation and parameterisation gives very good quality of control, comparable with that possible in classical MPC with long horizons and nonlinear optimisation.

Parole chiave

  • process control
  • nonlinear model predictive control
  • Laguerre functions
  • linearisation
Accesso libero

Health–Aware and Fault–Tolerant Control of an Octorotor UAV System Based on Actuator Reliability

Pubblicato online: 03 Apr 2020
Pagine: 47 - 59

Astratto

Abstract

A major goal in modern flight control systems is the need for improving reliability. This work presents a health-aware and fault-tolerant control approach for an octorotor UAV that allows distributing the control effort among the available actuators based on their health information. However, it is worth mentioning that, in the case of actuator fault occurrence, a reliability improvement can come into conflict with UAV controllability. Therefore, system reliability sensitivity is redefined and modified to prevent uncontrollable situations during the UAV’s mission. The priority given to each actuator is related to its importance in system reliability. Moreover, the proposed approach can reconfigure the controller to compensate actuator faults and improve the overall system reliability or delay maintenance tasks.

Parole chiave

  • prognostics and health management
  • health-aware control
  • fault-tolerant control
  • reliability analysis
  • octorotor
  • UAV
Accesso libero

Fault Tolerant Multicontrollers for Nonlinear Systems: A Real Validation on a Chemical Process

Pubblicato online: 03 Apr 2020
Pagine: 61 - 74

Astratto

Abstract

An active sensor fault tolerant controller for nonlinear systems represented by a decoupled multimodel is proposed. Active fault tolerant control requires accurate fault estimation. Thus, to estimate both state variables and sensor faults, a discrete unknown input multiobserver, based on an augmented state multimodel, is designed. The multiobserver gains are computed by solving linear matrix inequalities with equality constraints. A multicontrol strategy is proposed for the compensation of the sensor fault and recovering the desired performances. This strategy integrates a bank of controllers, corresponding to a set of partial models, to generate a set of control laws compensating the fault effect. Then, a switching strategy between the generated local control laws is established in order to apply the most suitable control law that tolerates the fault and maintains good closed loop performances. The effectiveness of the proposed strategy is proven through a numerical example and also through a real time application on a chemical reactor. The obtained results confirm satisfactory closed loop performance in terms of trajectory tracking and fault tolerance.

Parole chiave

  • multicontroller
  • experimental validation
  • transesterification reactor
  • discrete unknown input multiobserver
  • fault tolerant control
  • sensor fault estimation
Accesso libero

Extremal Properties of Linear Dynamic Systems Controlled by Dirac’s Impulse

Pubblicato online: 03 Apr 2020
Pagine: 75 - 81

Astratto

Abstract

The paper concerns the properties of linear dynamical systems described by linear differential equations, excited by the Dirac delta function. A differential equation of the form anx(n)(t)+···+a1x′ (t)+a0x(t)= bmu(m)(t)+···+b1u′ (t)+b0u(t) is considered with ai, bj > 0. In the paper we assume that the polynomials Mn(s)= ansn + ··· + a1s + a0 and Lm(s)= bmsm + ··· + b1s + b0 partly interlace. The solution of the above equation is denoted by x(t, Lm,Mn). It is proved that the function x(t, Lm,Mn) is nonnegative for t ∈ (0, ∞), and does not have more than one local extremum in the interval (0, ∞) (Theorems 1, 3 and 4). Besides, certain relationships are proved which occur between local extrema of the function x(t, Lm,Mn), depending on the degree of the polynomial Mn(s) or Lm(s) (Theorems 5 and 6).

Parole chiave

  • extremal properties
  • Dirac’s impulse
  • linear systems
  • transfer function
Accesso libero

Anti–Periodic Solutions for Clifford–Valued High–Order Hopfield Neural Networks with State–Dependent and Leakage Delays

Pubblicato online: 03 Apr 2020
Pagine: 83 - 98

Astratto

Abstract

A class of Clifford-valued high-order Hopfield neural networks (HHNNs) with state-dependent and leakage delays is considered. First, by using a continuation theorem of coincidence degree theory and the Wirtinger inequality, we obtain the existence of anti-periodic solutions of the networks considered. Then, by using the proof by contradiction, we obtain the global exponential stability of the anti-periodic solutions. Finally, two numerical examples are given to illustrate the feasibility of our results.

Parole chiave

  • Clifford-valued high-order Hopfield neural network
  • anti-periodic solution
  • coincidence degree
  • time-varying delay
Accesso libero

Finding Robust Transfer Features for Unsupervised Domain Adaptation

Pubblicato online: 03 Apr 2020
Pagine: 99 - 112

Astratto

Abstract

An insufficient number or lack of training samples is a bottleneck in traditional machine learning and object recognition. Recently, unsupervised domain adaptation has been proposed and then widely applied for cross-domain object recognition, which can utilize the labeled samples from a source domain to improve the classification performance in a target domain where no labeled sample is available. The two domains have the same feature and label spaces but different distributions. Most existing approaches aim to learn new representations of samples in source and target domains by reducing the distribution discrepancy between domains while maximizing the covariance of all samples. However, they ignore subspace discrimination, which is essential for classification. Recently, some approaches have incorporated discriminative information of source samples, but the learned space tends to be overfitted on these samples, because they do not consider the structure information of target samples. Therefore, we propose a feature reduction approach to learn robust transfer features for reducing the distribution discrepancy between domains and preserving discriminative information of the source domain and the local structure of the target domain. Experimental results on several well-known cross-domain datasets show that the proposed method outperforms state-of-the-art techniques in most cases.

Parole chiave

  • unsupervised domain adaptation
  • feature reduction
  • generalized eigenvalue decomposition
  • object recognition
Accesso libero

A Second–Order TV–Based Coupling Model and an ADMM Algorithm for MR Image Reconstruction

Pubblicato online: 03 Apr 2020
Pagine: 113 - 122

Astratto

Abstract

Motivated by ideas from two-step models and combining second-order TV regularization in the LLT model, we propose a coupling model for MR image reconstruction. By applying the variables splitting technique, the split Bregman iterative scheme, and the alternating minimization method twice, we can divide the proposed model into several subproblems only related to second-order PDEs so as to avoid solving a fourth-order PDE. The solution of every subproblem is based on generalized shrinkage formulas, the shrink operator or the diagonalization technique of the Fourier transform, and hence can be obtained very easily. By means of the Barzilai–Borwein step size selection scheme, an ADMM type algorithm is proposed to solve the equations underlying the proposed model. The results of numerical implementation demonstrate the feasibility and effectiveness of the proposed model and algorithm.

Parole chiave

  • MRI reconstruction
  • LLT model
  • LOT model
  • coupling model
  • ADMM
  • split Bregman
  • wavelet transform
Accesso libero

Curve Skeleton Extraction Via K–Nearest–Neighbors Based Contraction

Pubblicato online: 03 Apr 2020
Pagine: 123 - 132

Astratto

Abstract

We propose a skeletonization algorithm that is based on an iterative points contraction. We make an observation that the local center that is obtained via optimizing the sum of the distance to k nearest neighbors possesses good properties of robustness to noise and incomplete data. Based on such an observation, we devise a skeletonization algorithm that mainly consists of two stages: points contraction and skeleton nodes connection. Extensive experiments show that our method can work on raw scans of real-world objects and exhibits better robustness than the previous results in terms of extracting topology-preserving curve skeletons.

Parole chiave

  • curve skeleton
  • points contraction
  • point cloud
  • nearest neighbors
Accesso libero

A Quaternion Clustering Framework

Pubblicato online: 03 Apr 2020
Pagine: 133 - 147

Astratto

Abstract

Data clustering is one of the most popular methods of data mining and cluster analysis. The goal of clustering algorithms is to partition a data set into a specific number of clusters for compressing or summarizing original values. There are a variety of clustering algorithms available in the related literature. However, the research on the clustering of data parametrized by unit quaternions, which are commonly used to represent 3D rotations, is limited. In this paper we present a quaternion clustering methodology including an algorithm proposal for quaternion based k-means along with quaternion clustering quality measures provided by an enhancement of known indices and an automated procedure of optimal cluster number selection. The validity of the proposed framework has been tested in experiments performed on generated and real data, including human gait sequences recorded using a motion capture technique.

Parole chiave

  • data clustering
  • quaternions data processing
  • human gait data processing
Accesso libero

An Algorithm for Quaternion–Based 3D Rotation

Pubblicato online: 03 Apr 2020
Pagine: 149 - 160

Astratto

Abstract

In this work a new algorithm for quaternion-based spatial rotation is presented which reduces the number of underlying real multiplications. The performing of a quaternion-based rotation using a rotation matrix takes 15 ordinary multiplications, 6 trivial multiplications by 2 (left-shifts), 21 additions, and 4 squarings of real numbers, while the proposed algorithm can compute the same result in only 14 real multiplications (or multipliers—in a hardware implementation case), 43 additions, 4 right-shifts (multiplications by 1/4), and 3 left-shifts (multiplications by 2).

Parole chiave

  • quaternions
  • space rotation
  • design of algorithms
Accesso libero

Heuristic Search of Exact Biclusters in Binary Data

Pubblicato online: 03 Apr 2020
Pagine: 161 - 171

Astratto

Abstract

The biclustering of two-dimensional homogeneous data consists in finding a subset of rows and a subset of columns whose intersection provides a set of cells whose values fulfil a specified condition. Usually it is defined as equality or comparability. One of the presented approaches is based on the model of Boolean reasoning, in which finding biclusters in binary or discrete data comes down to the problem of finding prime implicants of some Boolean function. Due to the high computational complexity of this task, the application of some heuristics should be considered. In the paper, a modification of the well-known Johnson strategy for prime implicant approximation induction is presented, which is necessary for the biclustering problem. The new method is applied to artificial and biomedical datasets.

Parole chiave

  • biclustering
  • Boolean reasoning
  • prime implicant approximation
  • biomedical data analysis
  • Johnson heuristic
Accesso libero

A Genetic Algorithm for the Maximum 2–Packing Set Problem

Pubblicato online: 03 Apr 2020
Pagine: 173 - 184

Astratto

Abstract

Given an undirected connected graph G = (V, E), a subset of vertices S is a maximum 2-packing set if the number of edges in the shortest path between any pair of vertices in S is at least 3 and S has the maximum cardinality. In this paper, we present a genetic algorithm for the maximum 2-packing set problem on arbitrary graphs, which is an NP-hard problem. To the best of our knowledge, this work is a pioneering effort to tackle this problem for arbitrary graphs. For comparison, we extended and outperformed a well-known genetic algorithm originally designed for the maximum independent set problem. We also compared our genetic algorithm with a polynomial-time one for the maximum 2-packing set problem on cactus graphs. Empirical results show that our genetic algorithm is capable of finding 2-packing sets with a cardinality relatively close (or equal) to that of the maximum 2-packing sets. Moreover, the cardinality of the 2-packing sets found by our genetic algorithm increases linearly with the number of vertices and with a larger population and a larger number of generations. Furthermore, we provide a theoretical proof demonstrating that our genetic algorithm increases the fitness for each candidate solution when certain conditions are met.

Parole chiave

  • maximum 2-packing set
  • genetic algorithms
  • graph algorithms
Accesso libero

A Decomposition Approach to Type 2 Interval Arithmetic

Pubblicato online: 03 Apr 2020
Pagine: 185 - 201

Astratto

Abstract

The classic interval has precise borders A=[a_,a¯]A = \left[ {\underline{a},\bar a} \right]. Therefore, it can be called a type 1 interval. Because of great practical importance of such interval data, several versions of type 1 interval arithmetic have been created. However, sometimes precise borders a_\underline{a} and ā of intervals cannot be determined in practice. If the borders are uncertain, then we have to do with type 2 intervals. A type 2 interval can be denoted as AT2=[[a_L,a_R],[a¯L,a¯R]]{A_{T2}} = \left[ {\left[ {{\underline{a}_L},{\underline{a}_R}} \right],\left[ {{{\bar a}_L},{{\bar a}_R}} \right]} \right]. The paper presents multidimensional decomposition RDM type 2 interval arithmetic (D-RDM-T2-I arithmetic), where RDM means relative-distance measure. The decomposition approach considerably simplifies calculations and is transparent for users. Apart from this arithmetic, examples of its applications are also presented. To the authors’ best knowledge, no papers on this arithmetic exist. D-RDM-T2-I arithmetic is necessary to create type 2 fuzzy arithmetic based on horizontal μ-cuts, which the authors aim to do.

Parole chiave

  • multi-dimensional RDM interval arithmetic
  • type 2 interval arithmetic
  • RDM type 2 interval arithmetic
  • decomposition type 2 interval arithmetic
  • interval arithmetic
15 Articoli
Accesso libero

Input Reconstruction by Feedback Control for the Schlögl and FitzHugh–Nagumo Equations

Pubblicato online: 03 Apr 2020
Pagine: 5 - 22

Astratto

Abstract

Dynamical reconstruction of unknown time-varying controls from inexact measurements of the state function is investigated for a semilinear parabolic equation with memory. This system includes as particular cases the Schlögl model and the FitzHugh–Nagumo equations. A numerical method is suggested that is based on techniques of feedback control. An error analysis is performed. Numerical examples confirm the theoretical predictions.

Parole chiave

  • semilinear parabolic equation
  • input reconstruction
Accesso libero

An Information Based Approach to Stochastic Control Problems

Pubblicato online: 03 Apr 2020
Pagine: 23 - 34

Astratto

Abstract

An information based method for solving stochastic control problems with partial observation is proposed. First, information-theoretic lower bounds of the cost function are analysed. It is shown, under rather weak assumptions, that reduction in the expected cost with closed-loop control compared with the best open-loop strategy is upper bounded by a non-decreasing function of mutual information between control variables and the state trajectory. On the basis of this result, an information based control (IBC) method is developed. The main idea of IBC consists in replacing the original control task by a sequence of control problems that are relatively easy to solve and such that information about the system state is actively generated. Two examples of the IBC operation are given. It is shown that the method is able to find an optimal solution without using dynamic programming at least in these examples. Hence the computational complexity of IBC is substantially smaller than that of dynamic programming, which is the main advantage of the proposed method.

Parole chiave

  • stochastic control
  • feedback
  • information
  • entropy
Accesso libero

Nonlinear Model Predictive Control for Processes with Complex Dynamics: A Parameterisation Approach Using Laguerre Functions

Pubblicato online: 03 Apr 2020
Pagine: 35 - 46

Astratto

Abstract

Classical model predictive control (MPC) algorithms need very long horizons when the controlled process has complex dynamics. In particular, the control horizon, which determines the number of decision variables optimised on-line at each sampling instant, is crucial since it significantly affects computational complexity. This work discusses a nonlinear MPC algorithm with on-line trajectory linearisation, which makes it possible to formulate a quadratic optimisation problem, as well as parameterisation using Laguerre functions, which reduces the number of decision variables. Simulation results of classical (not parameterised) MPC algorithms and some strategies with parameterisation are thoroughly compared. It is shown that for a benchmark system the MPC algorithm with on-line linearisation and parameterisation gives very good quality of control, comparable with that possible in classical MPC with long horizons and nonlinear optimisation.

Parole chiave

  • process control
  • nonlinear model predictive control
  • Laguerre functions
  • linearisation
Accesso libero

Health–Aware and Fault–Tolerant Control of an Octorotor UAV System Based on Actuator Reliability

Pubblicato online: 03 Apr 2020
Pagine: 47 - 59

Astratto

Abstract

A major goal in modern flight control systems is the need for improving reliability. This work presents a health-aware and fault-tolerant control approach for an octorotor UAV that allows distributing the control effort among the available actuators based on their health information. However, it is worth mentioning that, in the case of actuator fault occurrence, a reliability improvement can come into conflict with UAV controllability. Therefore, system reliability sensitivity is redefined and modified to prevent uncontrollable situations during the UAV’s mission. The priority given to each actuator is related to its importance in system reliability. Moreover, the proposed approach can reconfigure the controller to compensate actuator faults and improve the overall system reliability or delay maintenance tasks.

Parole chiave

  • prognostics and health management
  • health-aware control
  • fault-tolerant control
  • reliability analysis
  • octorotor
  • UAV
Accesso libero

Fault Tolerant Multicontrollers for Nonlinear Systems: A Real Validation on a Chemical Process

Pubblicato online: 03 Apr 2020
Pagine: 61 - 74

Astratto

Abstract

An active sensor fault tolerant controller for nonlinear systems represented by a decoupled multimodel is proposed. Active fault tolerant control requires accurate fault estimation. Thus, to estimate both state variables and sensor faults, a discrete unknown input multiobserver, based on an augmented state multimodel, is designed. The multiobserver gains are computed by solving linear matrix inequalities with equality constraints. A multicontrol strategy is proposed for the compensation of the sensor fault and recovering the desired performances. This strategy integrates a bank of controllers, corresponding to a set of partial models, to generate a set of control laws compensating the fault effect. Then, a switching strategy between the generated local control laws is established in order to apply the most suitable control law that tolerates the fault and maintains good closed loop performances. The effectiveness of the proposed strategy is proven through a numerical example and also through a real time application on a chemical reactor. The obtained results confirm satisfactory closed loop performance in terms of trajectory tracking and fault tolerance.

Parole chiave

  • multicontroller
  • experimental validation
  • transesterification reactor
  • discrete unknown input multiobserver
  • fault tolerant control
  • sensor fault estimation
Accesso libero

Extremal Properties of Linear Dynamic Systems Controlled by Dirac’s Impulse

Pubblicato online: 03 Apr 2020
Pagine: 75 - 81

Astratto

Abstract

The paper concerns the properties of linear dynamical systems described by linear differential equations, excited by the Dirac delta function. A differential equation of the form anx(n)(t)+···+a1x′ (t)+a0x(t)= bmu(m)(t)+···+b1u′ (t)+b0u(t) is considered with ai, bj > 0. In the paper we assume that the polynomials Mn(s)= ansn + ··· + a1s + a0 and Lm(s)= bmsm + ··· + b1s + b0 partly interlace. The solution of the above equation is denoted by x(t, Lm,Mn). It is proved that the function x(t, Lm,Mn) is nonnegative for t ∈ (0, ∞), and does not have more than one local extremum in the interval (0, ∞) (Theorems 1, 3 and 4). Besides, certain relationships are proved which occur between local extrema of the function x(t, Lm,Mn), depending on the degree of the polynomial Mn(s) or Lm(s) (Theorems 5 and 6).

Parole chiave

  • extremal properties
  • Dirac’s impulse
  • linear systems
  • transfer function
Accesso libero

Anti–Periodic Solutions for Clifford–Valued High–Order Hopfield Neural Networks with State–Dependent and Leakage Delays

Pubblicato online: 03 Apr 2020
Pagine: 83 - 98

Astratto

Abstract

A class of Clifford-valued high-order Hopfield neural networks (HHNNs) with state-dependent and leakage delays is considered. First, by using a continuation theorem of coincidence degree theory and the Wirtinger inequality, we obtain the existence of anti-periodic solutions of the networks considered. Then, by using the proof by contradiction, we obtain the global exponential stability of the anti-periodic solutions. Finally, two numerical examples are given to illustrate the feasibility of our results.

Parole chiave

  • Clifford-valued high-order Hopfield neural network
  • anti-periodic solution
  • coincidence degree
  • time-varying delay
Accesso libero

Finding Robust Transfer Features for Unsupervised Domain Adaptation

Pubblicato online: 03 Apr 2020
Pagine: 99 - 112

Astratto

Abstract

An insufficient number or lack of training samples is a bottleneck in traditional machine learning and object recognition. Recently, unsupervised domain adaptation has been proposed and then widely applied for cross-domain object recognition, which can utilize the labeled samples from a source domain to improve the classification performance in a target domain where no labeled sample is available. The two domains have the same feature and label spaces but different distributions. Most existing approaches aim to learn new representations of samples in source and target domains by reducing the distribution discrepancy between domains while maximizing the covariance of all samples. However, they ignore subspace discrimination, which is essential for classification. Recently, some approaches have incorporated discriminative information of source samples, but the learned space tends to be overfitted on these samples, because they do not consider the structure information of target samples. Therefore, we propose a feature reduction approach to learn robust transfer features for reducing the distribution discrepancy between domains and preserving discriminative information of the source domain and the local structure of the target domain. Experimental results on several well-known cross-domain datasets show that the proposed method outperforms state-of-the-art techniques in most cases.

Parole chiave

  • unsupervised domain adaptation
  • feature reduction
  • generalized eigenvalue decomposition
  • object recognition
Accesso libero

A Second–Order TV–Based Coupling Model and an ADMM Algorithm for MR Image Reconstruction

Pubblicato online: 03 Apr 2020
Pagine: 113 - 122

Astratto

Abstract

Motivated by ideas from two-step models and combining second-order TV regularization in the LLT model, we propose a coupling model for MR image reconstruction. By applying the variables splitting technique, the split Bregman iterative scheme, and the alternating minimization method twice, we can divide the proposed model into several subproblems only related to second-order PDEs so as to avoid solving a fourth-order PDE. The solution of every subproblem is based on generalized shrinkage formulas, the shrink operator or the diagonalization technique of the Fourier transform, and hence can be obtained very easily. By means of the Barzilai–Borwein step size selection scheme, an ADMM type algorithm is proposed to solve the equations underlying the proposed model. The results of numerical implementation demonstrate the feasibility and effectiveness of the proposed model and algorithm.

Parole chiave

  • MRI reconstruction
  • LLT model
  • LOT model
  • coupling model
  • ADMM
  • split Bregman
  • wavelet transform
Accesso libero

Curve Skeleton Extraction Via K–Nearest–Neighbors Based Contraction

Pubblicato online: 03 Apr 2020
Pagine: 123 - 132

Astratto

Abstract

We propose a skeletonization algorithm that is based on an iterative points contraction. We make an observation that the local center that is obtained via optimizing the sum of the distance to k nearest neighbors possesses good properties of robustness to noise and incomplete data. Based on such an observation, we devise a skeletonization algorithm that mainly consists of two stages: points contraction and skeleton nodes connection. Extensive experiments show that our method can work on raw scans of real-world objects and exhibits better robustness than the previous results in terms of extracting topology-preserving curve skeletons.

Parole chiave

  • curve skeleton
  • points contraction
  • point cloud
  • nearest neighbors
Accesso libero

A Quaternion Clustering Framework

Pubblicato online: 03 Apr 2020
Pagine: 133 - 147

Astratto

Abstract

Data clustering is one of the most popular methods of data mining and cluster analysis. The goal of clustering algorithms is to partition a data set into a specific number of clusters for compressing or summarizing original values. There are a variety of clustering algorithms available in the related literature. However, the research on the clustering of data parametrized by unit quaternions, which are commonly used to represent 3D rotations, is limited. In this paper we present a quaternion clustering methodology including an algorithm proposal for quaternion based k-means along with quaternion clustering quality measures provided by an enhancement of known indices and an automated procedure of optimal cluster number selection. The validity of the proposed framework has been tested in experiments performed on generated and real data, including human gait sequences recorded using a motion capture technique.

Parole chiave

  • data clustering
  • quaternions data processing
  • human gait data processing
Accesso libero

An Algorithm for Quaternion–Based 3D Rotation

Pubblicato online: 03 Apr 2020
Pagine: 149 - 160

Astratto

Abstract

In this work a new algorithm for quaternion-based spatial rotation is presented which reduces the number of underlying real multiplications. The performing of a quaternion-based rotation using a rotation matrix takes 15 ordinary multiplications, 6 trivial multiplications by 2 (left-shifts), 21 additions, and 4 squarings of real numbers, while the proposed algorithm can compute the same result in only 14 real multiplications (or multipliers—in a hardware implementation case), 43 additions, 4 right-shifts (multiplications by 1/4), and 3 left-shifts (multiplications by 2).

Parole chiave

  • quaternions
  • space rotation
  • design of algorithms
Accesso libero

Heuristic Search of Exact Biclusters in Binary Data

Pubblicato online: 03 Apr 2020
Pagine: 161 - 171

Astratto

Abstract

The biclustering of two-dimensional homogeneous data consists in finding a subset of rows and a subset of columns whose intersection provides a set of cells whose values fulfil a specified condition. Usually it is defined as equality or comparability. One of the presented approaches is based on the model of Boolean reasoning, in which finding biclusters in binary or discrete data comes down to the problem of finding prime implicants of some Boolean function. Due to the high computational complexity of this task, the application of some heuristics should be considered. In the paper, a modification of the well-known Johnson strategy for prime implicant approximation induction is presented, which is necessary for the biclustering problem. The new method is applied to artificial and biomedical datasets.

Parole chiave

  • biclustering
  • Boolean reasoning
  • prime implicant approximation
  • biomedical data analysis
  • Johnson heuristic
Accesso libero

A Genetic Algorithm for the Maximum 2–Packing Set Problem

Pubblicato online: 03 Apr 2020
Pagine: 173 - 184

Astratto

Abstract

Given an undirected connected graph G = (V, E), a subset of vertices S is a maximum 2-packing set if the number of edges in the shortest path between any pair of vertices in S is at least 3 and S has the maximum cardinality. In this paper, we present a genetic algorithm for the maximum 2-packing set problem on arbitrary graphs, which is an NP-hard problem. To the best of our knowledge, this work is a pioneering effort to tackle this problem for arbitrary graphs. For comparison, we extended and outperformed a well-known genetic algorithm originally designed for the maximum independent set problem. We also compared our genetic algorithm with a polynomial-time one for the maximum 2-packing set problem on cactus graphs. Empirical results show that our genetic algorithm is capable of finding 2-packing sets with a cardinality relatively close (or equal) to that of the maximum 2-packing sets. Moreover, the cardinality of the 2-packing sets found by our genetic algorithm increases linearly with the number of vertices and with a larger population and a larger number of generations. Furthermore, we provide a theoretical proof demonstrating that our genetic algorithm increases the fitness for each candidate solution when certain conditions are met.

Parole chiave

  • maximum 2-packing set
  • genetic algorithms
  • graph algorithms
Accesso libero

A Decomposition Approach to Type 2 Interval Arithmetic

Pubblicato online: 03 Apr 2020
Pagine: 185 - 201

Astratto

Abstract

The classic interval has precise borders A=[a_,a¯]A = \left[ {\underline{a},\bar a} \right]. Therefore, it can be called a type 1 interval. Because of great practical importance of such interval data, several versions of type 1 interval arithmetic have been created. However, sometimes precise borders a_\underline{a} and ā of intervals cannot be determined in practice. If the borders are uncertain, then we have to do with type 2 intervals. A type 2 interval can be denoted as AT2=[[a_L,a_R],[a¯L,a¯R]]{A_{T2}} = \left[ {\left[ {{\underline{a}_L},{\underline{a}_R}} \right],\left[ {{{\bar a}_L},{{\bar a}_R}} \right]} \right]. The paper presents multidimensional decomposition RDM type 2 interval arithmetic (D-RDM-T2-I arithmetic), where RDM means relative-distance measure. The decomposition approach considerably simplifies calculations and is transparent for users. Apart from this arithmetic, examples of its applications are also presented. To the authors’ best knowledge, no papers on this arithmetic exist. D-RDM-T2-I arithmetic is necessary to create type 2 fuzzy arithmetic based on horizontal μ-cuts, which the authors aim to do.

Parole chiave

  • multi-dimensional RDM interval arithmetic
  • type 2 interval arithmetic
  • RDM type 2 interval arithmetic
  • decomposition type 2 interval arithmetic
  • interval arithmetic

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