M.G. Xibilia

M.G. Xibilia
Università degli Studi di Messina | UNIME · Dipartimento di Ingegneria

Dr., Eng., PhD

About

182
Publications
22,633
Reads
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3,309
Citations
Introduction
M.G. Xibilia currently works at the Dipartimento di Ingegneria, Università degli Studi di Messina as associate professor in Automatic Control Systems. Their current project is 'Soft sensors for industrial applications.'
Additional affiliations
May 2007 - October 2016
Università degli Studi di Messina
Position
  • associate professor of automatic control
May 1998 - present
Università degli Studi di Messina
Position
  • associate professor of automatic control

Publications

Publications (182)
Article
Full-text available
Commensurate Multiple Time-Delay Systems (CMTDSs) are of considerable interest for many applications, ranging from process control to decision-making systems. A stable CMTDS can become unstable when a small delay is introduced and vice-versa. The letter proposes an innovative controller design procedure for CMTDSs, able to transform the system into...
Conference Paper
Failure prognostics can improve industrial systems' availability and reliability by determining the occurrence of failure and estimating the system's remaining useful life (RUL) before deterioration. This paper presents a prognostic method based on data-driven and degradation model approaches to accurately predict the RUL of a scale replica s...
Article
This paper provides a comparative analysis of two common control configurations used to control the side-stream distillation used to separate benzene, toluene and xylene as suggested by Doukas and Lyben. Their under-actuated model has been considered as the model of distillation column and the internal model controller is designed considering a Sin...
Article
Full-text available
Soft Sensors (SSs) are inferential dynamical models employed in industries to perform prediction of process hard-to-measure variables based on their relation with easily accessible ones. They allow implementation of real-time control and monitoring of the plants and present other advantages in terms of costs and efforts. Given the complexity of ind...
Article
Full-text available
Rotating machines such as induction motors are crucial parts of most industrial systems. The prognostic health management of induction motor rotors plays an essential role in increasing electrical machine reliability and safety, especially in critical industrial sectors. This paper presents a new approach for rotating machine fault prognosis under...
Article
Full-text available
The knowledge of the electrochemical processes inside a Fuel Cell (FC) is useful for improving FC diagnostics, and Electrochemical Impedance Spectroscopy (EIS) is one of the most used techniques for electrochemical characterization. This paper aims to propose the identification of a Fractional-Order Transfer Function (FOTF) able to represent the FC...
Article
The implementation of soft sensors for industrial processes is expanding in applications for recent machine learning techniques. In this work, strategies based on reservoir computing are applied to developing dynamical models of target variables in a sulfur recovery unit (SRU) of a refinery plant in Italy. In particular, a specific type of recurren...
Article
Full-text available
The design and application of Soft Sensors (SSs) in the process industry is a growing research field, which needs to mediate problems of model accuracy with data availability and computational complexity. Black-box machine learning (ML) methods are often used as an efficient tool to implement SSs. Many efforts are, however, required to properly sel...
Article
Full-text available
Soft Sensors (SSs) are mathematical models that allow real-time estimation of hard-to-measure variables as a function of easy-to-measure ones in an industrial process, emulating the behavior of existing sensors when they are, for instance, taken off for maintenance. The Sulfur Recovery Unit (SRU) from a refinery is taken in exam. Recurrent Neural N...
Article
The chaotic analysis is often used to investigate electrochemical signals. The proposed work applies it to understand the behavior of hydrogen electrochemical devices, with particular attention to electrochemical hydrogen compressors (EHC). Measurements, carried out at the C.N.R - Istituto di Tecnologie Avanzate per l’Energia “Nicola Giordano” of M...
Article
Full-text available
The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved the state of the art in many applications, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Thing...
Article
Full-text available
Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of...
Article
Soft Sensors (SSs) are inferential models which are widely used in industry. They are generally built through data-driven approaches that exploit industry historical databases. Selection of input variables is one of the most critical issues in SSs design. This paper aims at highlighting difficulties arising from the implementation of data-driven in...
Article
Here is reported about the design of a Soft Sensor (SS) able to monitor hazardous gases in industrial plants. The SS is designed to estimate the gas concentrations by means of the measurements coming from an array of sensors, avoiding at the same time the humidity and temperature influence on array outputs. The SS has been designed with a data-driv...
Chapter
Soft Sensors are mathematical models used to predict the behavior of real systems. They are usefully applied to estimate hard-to-measure quantities in the process industry. Many Soft Sensors are designed by using data-driven approaches and exploiting historical databases. Machine learning is widely used for this aim. Here, the potentialities of dee...
Article
Data selection is a critical issue in data-driven soft sensor design. The paper proposes a new method for data selection based on a feature extraction step, followed by data selection algorithms. The method has been applied to an industrial case study, i.e., the estimation of the quality of processed wastewater produced by a Sour Water Stripping pl...
Article
Full-text available
In this paper, classical and non-integer model order reduction methodologies are compared. Non integer order calculus has been used to generalize many classical control strategies. The property of compressing information in modelling systems, distributed in time and space, and the capability of describing long-term memory effects in dynamical syste...
Article
Full-text available
This paper proposes a model of the dynamics of credit contagion through non-performing loans on financial networks. Credit risk contagion is modeled in the context of the classical SIS (Susceptibles-Infected-Susceptibles) epidemic processes on networks but with a fundamental novelty. In fact, we assume the presence of two different classes of infec...
Chapter
The current trend of automation and data exchange in manufacturing technologies is commonly referred to as the fourth industrial revolution, and known as Industry 4.0. Its “pillars” are Cyber-Physical Systems (CPS), Cognitive Computing (CC), Internet of Things (IoT) and Cloud. In such a scenario, to know both technologies and processes supporting d...
Chapter
The prediction of failures in rotating machines is an important issue in industries to improve safety, to reduce the cost of maintenance and to prevent accidents. In this paper a predictive maintenance algorithm, based on the analysis of the orbits shape of the rotor shaft is proposed. It is based on an autonomous image pattern recognition algorith...
Article
Full-text available
: Internal model control (IMC) is an established technique in continuous time linear control, but it is less used for discrete-time systems. Most of the existing solutions do not cover all the situations and, in any case, they lead to complex procedures to design the controller. In this paper, a IMC technique able to control over-actuated systems i...
Cover Page
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Research Proposal
Full-text available
Article
This paper introduces a soft sensor (SS) for the estimation of the deflection of a polymeric mechanical actuator. The actuator is based on ionic polymer-metal composites (IPMCs). Applications of IPMCs have been proposed in fields such as robotics, surgery, and aerospace, to mention the most interesting ones. In such application fields, both the com...
Article
Full-text available
Smart Grids play a crucial role for always more efficient, flexible and reliable integration of technologies in the electricity marketplace. At the “edge” of Smart Grids, appliances and consumer devices consume electricity by Microgrids. End-users need easily and dynamically accessible electricity marketplace and heterogeneous renewable energy sour...
Article
In this brief, the thermal model identification of the limiter surface placed in nuclear fusion plants facilities is presented. Experimental data measured at the Frascati Tokamak Upgrade (FTU) have been considered in order to identify a nonlinear dynamical model of the temperature distribution over the cooled lithium limiter used in the FTU. Three...
Article
In this work, a data-driven model procedure aimed at identifying the dynamical behavior of the thermal distribution over the limiter surface placed in nuclear fusion plant facilities is provided. In particular, we focused on experimental data collected in the in Frascati Tokamak Upgrade (FTU) where a cooled liquid lithium limiter (CLL) with a capil...
Article
In this paper, positive-real systems under lossless positive-real transformations are investigated. Let G(s) be the transfer function matrix of a continuous-time positive-real system of order n and F(s) a lossless transfer function of order nF. We prove here that the lossless positive-real transformed system, i.e. G(F(s)), is also positive-real. Fu...
Chapter
Aim of the paper is to deeply investigate the role and the characteristics of fog in various paintings by famous artists of different art movements, in which the presence of fog significantly affects the visual experience. To do this a new nonlinear signal processing technique, able to remove fog from color pictures exploiting optical properties of...
Conference Paper
In this paper, the model identification of the temperature over the surface of the limiter adopted in the Frascati Tokamak Upgrade (FTU) is presented. Tokamaks are considered as the most interesting facilities to study self-sustained nuclear fusion reactions. Recently, a Liquid Lithium Limiter (LLL) has been introduced in the FTU with the aim of re...
Article
In this paper new results on the open-loop balanced representation of continuous time linear time-invariant systems are reported. More particularly, the effect of lossless positive real transformations on open-loop balanced representations is investigated with specific attention to the problem of model order reduction. The properties of systems whe...
Article
In this paper the invariance of the characteristic values and of the L∞ norm of linear time-invariant (LTI) systems under lossless positive real transformations is proven. Given a LTI system with transfer function matrix G(s), the transformation s←F(s) with F(s) being an arbitrary lossless positive real function of order n F is considered, and the...
Article
The evolution of natural phenomena in real environments often involves complex nonlinear interactions. Modeling them implies the characterization of both a map of interactions and a dynamical process, but also of the peculiarity of the space in which the phenomena occur. The model presented in this paper encompasses all these aspects to formalize a...
Conference Paper
In this paper evolutionary computation algorithms are applied to select optimal parameters in model order reduction for linear systems. In particular a parameterized set of reduced order model is obtained by using a Parametric Generalised Singular Perturbation Approximation of a balanced realization. The optimization algorithm is then used to selec...
Conference Paper
After the fabrication of several devices showing memristive switching behavior, recently a growing interest to the realization of dynamical nonlinear circuits based on memristors has been manifested. Currently, many memristor circuits have been mostly conceived on the basis of theoretical memristor models. However, in order to analyze the dynamical...
Conference Paper
In this paper a new class of orthonormal functions which includes as particular case the Laguerre filters are introduced. These functions are defined as the product of a fixed transfer function of order n and of an all-pass filter of order n × h for any n and h. The orthogonality of these functions is proven in the general case. Moreover, the singu...
Article
Full-text available
Smart systems adapt to the surrounding environments in a number of ways. They are capable to scavenge energy from available sources, sense and elaborate external stimuli and adequately react. Electro Active Polymers are playing a main role in the realization of smart systems for applications if fields such as bio inspired and autonomous robotics, m...
Conference Paper
Ionic Polymer-Polymer Composites (IP2Cs) are electro-active polymers which can be used both as sensors and as actuators. In this paper IP2Cs, used as actuators, and with water as the solvent, are modeled. Starting from some previous results regarding modeling of Ionic Polymer Metal Composites (IPMCs) and of IP2Cs themselves, using ethylene glycol (...
Article
Full-text available
In this paper, two different nonlinear models for Artemia swarming are derived. In order to generate the data suitable for identification, a robot driving the Artemia population has been built. The obtained data have been then used to identify the parameters of a model based on Newton’s equations and a black-box NARX model implemented by neural net...
Article
Stable linear time-invariant systems can be made passive by a feedforward action. In this article, an analytical approach to obtain the matrix which allows to enforce passivity in the system is proposed. This matrix depends only on one parameter, namely α. The introduced method is based on the calculation of the characteristic polynomial of the Ham...
Article
Full-text available
In this paper a new approach based on Cellular Nonlinear Networks (CNNs) for modeling the diffusion of forest fires is presented. Based on a model relying on an hyperbolic reaction-diffusion equation, the proposed approach exploits the peculiarity of CNNs allowing the investigation of different types of forest fires, also considering specific morph...
Article
IPMC actuators suffer because of a large number of influencing factors that do not allow adequate open loop working conditions and they require the use of controlling strategies. IPMC controllers can be designed by using suitable device models. Here a non integer order transfer function is used to model IPMC actuators. In the present paper the IPMC...
Conference Paper
In this paper different strategies to model Ionic Polymer-Polymer Composite (IP2C), used as actuator, are compared. Starting from some previous results regarding the ionic polymer metal composites (IPMCs) modeling, a linear gray-box model has been determined for an IP2C actuator. Moreover linear and nonlinear black-box models have been identified f...
Article
A new nonlinear signal processing technique, able to remove fog from color images exploiting the optical properties of the fog effect, is introduced. It is based on the use of cellular nonlinear networks (CNNs), a paradigm for nonlinear parallel image processing. The technique is applied to the analysis of several paintings by famous artists of dif...
Conference Paper
Full-text available
In this paper, a wireless underwater mobile robot system is designed in order to study the behavior of Artemia group. A new idea has been presented for underwater mobile robot system which is consists of two parts, first is the underwater mechanical robot and the second is ZigBee wireless based mobile robot which controls and moves the first part....
Article
In this paper the approximation capabilities of different structures of complex feedforward neural networks, reported in the literature, have been theoretically analyzed. In particular a new density theorem for Complex Multilayer Perceptrons with complex valued non-analytic sigmoidal activation functions has been proven. Such a result makes Multila...
Article
In this communication the relationship between emerging patterns generated by using CNN Universal Machine and patterns appearing in visual art masterpieces is discussed. The template based programming tools are outlined and a gallery of impressive examples is presented. The paper remarks the impressive role of Cellular Nonlinear Networks in coverin...
Article
In this paper, a new strategy to cope with the identification of nonlinear models of industrial processes, when a limited number of experimental data is available, is proposed. The approach is intended to improve the generalization capabilities of the model and it is based on the integration of bootstrap resampling, noise injection and neural model...
Article
Full-text available
Artemia larvae may show swarming organization under the presence of a light spot, while being insensitive to several other external stimuli. In this paper, the dynamics of the Artemia population in response to this kind of stimuli has been exploited to design a robot moving inside the water and able to lead the direction of the group. The robot the...
Conference Paper
Full-text available
In this work, the collective behavior of Artemia Salina is studied both experimentally and theoretically. Several experiments have been designed to investigate the Artemia motion under different environment conditions. From the results of such experiments, a strategy to control the direction of motion of an Artemia population, by exploiting their s...
Article
The paper deals with the design of a data driven soft sensor, able to estimate propylene percentage in the bottom flow of a Propylene Splitter showing seasonal variations. Experimental data have been collected in a refinery in Sicily. The soft sensor is intended to replace the online analyzer during maintenance, in order to guarantee the desired pl...
Article
This paper analyzes a number of strategies that are devoted to improving the generalization capabilities of neural-network-based soft sensors when only small data sets are available. The aim of this paper is to search for a strategy that is able to cope with the problem of scarcity of experimental data, which often arises in industrial applications...
Conference Paper
A new strategy to realize an FPGA implementation of a soft sensor for an industrial process is proposed. In order to cope with the problem of small data sets in the identification of a non linear model the proposed approach is based on the integration of bootstrap re-sampling, noise injection and stacked neural networks (NNs), using the Principal C...
Conference Paper
Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal
Article
A new strategy to improve generalization capabiliy of data-driven soft sensor for industrial processes is proposed in the paper. The method is useful when a limited data set is available. The proposed approach is based on the integration of bootstrap resampling, noise injection and stacked neural networks. In the paper it has been applied to develo...
Article
In this paper a number of approaches to design a soft sensor for an industrial plant in case of small data set are compared. In particular different strategies to aggregate suboptimal models obtained by bootstrapped neural networks and noise injection are considered. An industrial case of study, consisting in the estimation of the T95% of a Thermal...
Article
In the paper a soft sensor design strategy for an industrial process, via neural NMA model, is described. A general design strategy, based on the automatic selection of regressors of a NMA model is proposed. It is based on the minimization of the cost function of a Gath Geva clustering algorithm. The obtained soft sensor will be implemented in a re...
Article
In this communication the relationship between emerging patterns generated by using a CNN universal machine and patterns appearing in visual art masterpieces is discussed. The template based programming tools are outlined and a gallery of impressive examples is presented. The paper remarks the impressive role of cellular nonlinear networks in cover...
Conference Paper
In the paper the Soft Sensor design strategy for an industrial process, via neural NMA model, is described. In details, the hydrogen sulphide (H2S percentage) in the tail stream of a Sulfur Recovery Unit (SRU) of a refinery located in Sicily, Italy, is estimated by a Soft Sensor, that was designed to replace the online analyzer during maintenance o...
Conference Paper
In this paper we compare a number of strategies to cope with the problem of small data sets in the identification of a nonlinear process. Four methods are analyzed: expansion of the training set by adding zero-mean fixed-variance Gaussian noise, expansion of the training set by adding zero-mean gaussian noise variance variable according with signal...