Keywords: Image processing, Industrial control, Fault detection and Diagnostics
Abstract: In this paper, we present an effective content-based image retrieval (CBIR) for surface defects of hot-rolled steel strips. This system allows the expert to separate serious defects from others automatically. The proposed CBIR system is based on extracting completed local binary patterns (CLBP) features from the discrete wavelet transform (DWT) coefficients. This DWCLBP descriptor extracts highly discriminative texture features at different scales and orientations. We select the optimal mother wavelet and wavelet decomposition levels by making extensive comparisons. The experimental results on NEU surface defects database demonstrate promising retrieval performance of the DWCLBP features.

Keywords: Image processing, Fault detection and Diagnostics
Abstract: The objective assessment of corneal endothelial pathology is frequently carried out using manual and semi-automated software tools. These software applications enable the quantification and analysis of corneal endothelial cells. However, this approach is subjective and not widely adopted by ophthalmologists. Developing methods for the automatic assessment of the size and structural organization of endothelial cells represents a significant challenge in the field of ophthalmology. Therefore, this article introduced a cell segmentation method using a convolutional neural network based on the U-Net architecture. More specifically, the network is trained to discriminate pixels at the borders between cells. The main contribution of this study lies in modifying the original U-Net by reducing the number of parameters in width and using average pooling, aiming to enhance the efficiency of corneal endothelial cell segmentation and analysis. The proposed method was evaluated on a dataset consisting of corneal endothelial cell images. The accuracy values are around 93,99% and the sensitivity has a high value (99,33%) compared to other architectures.

Keywords: Industrial control, Manufacturing systems, Control education
Abstract: The most important and complicated work metric, which is not usually directly connected to productivity, is the work efficiency of machinery operators. Strict adherence to technical and technological regulations, a conscientious attitude towards machinery, and energy efficiency are among the factors that influence work efficiency. This article suggests a method for assessing operator performance through the precise control of a moving object based on the method for assessing a person’s reaction time. The paper discusses the results of experiments carried out on a group of students. It has been demonstrated that this approach may be used to assess the efficiency of professional training of operators in terms of gaining practical skills. The authors examine the efficiency of testing using a virtual reality headset compared to a standard video display.

Keywords: Fractional order systems, Multivariable control, Linear and nonlinear systems
Abstract: In this manuscript, sufficient conditions for the asymptotic stability of positive two dimensional (2D) fractional order discrete systems modeled by the Roesser model are presented. It will be revealed that examining the asymptotic stability of the 2D fractional order positive systems can be reduced to testing the asymptotic stability of the equivalent positive 1D systems.

Keywords: Fractional order systems, Control applications, Mathematical systems theory
Abstract: One-Sided Lipschitz (OSL) fractional order modeling is a top choice for solving the stabilization issue of nonlinear systems. Despite numerous studies on the subject, there remains a gap in understanding when it comes to fractional calculus. By providing a stabilizing strategy for a certain type of OSL fractional order nonlinear systems, this study fills the gap. A numerical example demonstrating the correctness of the suggested approach and demonstrating its efficacy for the tested class.

Keywords: Estimations and identification, Fractional order systems, Observer design
Abstract: This paper considers a 6-dimensional fractional-order linear system equipped with a sensor network digraph containing 4 sensors. The objective is to develop a method for distributed state estimation. First, based on the assumption of strong connectivity， a compensation set is introduced to construct the transformation matrix. Then, the relationship between the transformed state at each node and the transformed observable states of the 4 nodes is established. In the light of this relationship, 4 centralized fractional-order observers with dimensions smaller than 6, are employed to estimate the 4 observable states, thereby realizing distributed estimation. In the end, a numerical example is presented to verify the availability of the proposed method.

Keywords: Fractional order systems, Estimations and identification, Linear and nonlinear systems
Abstract: In this paper, the pseudo-state and the disturbance of a class of fractional order linear systems are simultaneously estimated via an algebraic approach. To achieve this, an augmented fractional order system model is provided for the studied fractional order linear system. Then, the pseudo-state of the augmented fractional order system is estimated using the fractional order modulating functions method. Further, the pseudo-state and the disturbance of the original system are recovered based on the augmented fractional order system. Simulation example illustrates the efficiency of the proposed method under the condition of noisy output measurements.

Keywords: Fractional order systems, Estimations and identification, Modeling and simulation
Abstract: The aim of this paper is to develop a fast and robust fractional differentiator for non-commensurate fractionalorder linear systems. To achieve this, the paper adopts a nonasymptotic algebraic perspective by applying the generalized modulating functions method. First, a proposition is given where fractional integration by parts formulas and the generalized modulating functions’ properties are used to eliminate the undesired terms and keep the needed ones of a generated equation from the system. Then, the differentiator is proposed by recursively apply this proposition. In fact, the so-called differentiator is a generalized one, which is also able to estimate the output itself and its integrals. The designed differentiator is given in the form of an algebraic integral formula, which has the advantage of noise resistance. Simulation results are provided to illustrate the effectiveness of this differentiator, and its robustness against corrupting noises.

Keywords: Fractional order systems, Linear and nonlinear systems
Abstract: In this paper, the infinite state representation is applied to model a fractional variant of the Lorenz chaotic

system. Thanks to a finite dimension approximation, the original fractional order system is converted into a large dimension set of integer order nonlinear differential equations whose initial conditions permit to test the sensitivity of the equivalent chaotic system. This sensitivity is quantified thanks to Lyapunov exponents which are computed with an experimental technique and the Gram-Schmidt algorithm.

Keywords: Control applications, Robotics
Abstract: This research paper explores the use of brain-computer interface (BCI) techniques for controlling arm movements through motor imagery (MI) signals. BCI technology enables communication and control between the brain and computers, utilizing brain activity to operate virtual entities without physical movement. Our study compares classification approaches, such as K-nearest neighbor (KNN) and support vector machine (SVM), to distinguish between left and right-hand MI based on EEG trials. Both classifiers achieve satisfactory accuracy in distinguishing MI-induced EEGs. The study highlights the application of MI-based BCI systems as an alternative communication and control channel for individuals with motor impairments. By employing Mel Frequency Cepstral Coefficients (MFCC) for feature extraction, known for their effectiveness in speech recognition and music retrieval, we contribute to the development of BCI-controlled robotic arm systems for rehabilitation. Our findings offer insights into effective motor imagery signal classification, promoting the development of BCI-based arm movement control during rehabilitation.

Keywords: Linear and nonlinear systems, Robotics, Robust control and Hinfty control
Abstract: This study introduces a robust control strategy to regulate the position of knee rehabilitation exoskeleton robot. A description of this particular robotic system and its nonlinear dynamic model are outlined first. The system faces challenges such as state constraints, external disruptions, and parameter uncertainties, all of which are meticulously addressed in the control design. Subsequently, we define the affine state-feedback controller and its design based on the LMI approach, aimed at ensuring the stabilization of the active exoskeleton robotic system at the knee joint level and hence its stability at the desired position. To achieve this, our proposed method utilizes a quadratic Lyapunov function and leverages mathematical tools such as the S-procedure Lemma, the Schur complement, the matrix inversion Lemma, and the Young inequality to derive finally two LMI conditions that guarantee the stability of the controlled knee exoskeleton system. Finally, the simulation studies validate the effectiveness of the proposed approach in the design of the LMI stability condition and hence the efficiency of the controller in the robust control of the knee exoskeleton robot.

Keywords: Estimations and identification, Fault detection and Diagnostics, Linear and nonlinear systems
Abstract: Abstract—Disorders of the heart and blood vessels are referred to as cardiovascular disease (CVD), which have been caused that can lead to a heart attack, chest torment (angina), or stroke. CVDs are the main reason for morbidity and mortality over the world. Cardiac catheterization is a tool for both diagnosis and therapeutic of CVDs. Machine learning can be used in the modeling of cardiac catheterization for binary classification. This work investigates the application of linear and non-linear support vector machines for classifying patients who need to be monitored. Using a dataset obtained from the Benghazi Heart Disease Center is of about 814 patients. We apply the principal component analysis (PCA) to display the dataset in a 3D space reflecting insight into the dataset. The aim of the research is to construct a binary classifier to predicate whether a patient is required to be followed by a doctor or not after a catheterization procedure. We find that the linear support vector machine identifies the crucial patients with an accuracy of 90.3%with slight effects on recall.

Keywords: Time-delay systems, Observer design, Estimations and identification
Abstract: This paper develops a functional reduced-order observer for a class of Linear Time-Invariant (LTI) systems with time-delay in the state. The proposed observer provides exponentially stable estimation errors. The unbiasedness conditions on the nominal part of the error dynamics of the reduced-order observer were given by employing an algebraic framework. Under such conditions, we propose the use of a partial pole placement of the error dynamical equations to handle sufficient conditions for the existence of the proposed observer. Specifically, we make use of the "multiplicity-induced-dominancy" property of the characteristic function corresponding to the system's error. The performance and the effectiveness of the developed observer is highlighted through two examples: first, the estimation of the HIV-1 infection dynamics, and second, the improvement of the environmental performance through the study of a diesel engine system.

Keywords: Estimations and identification, Power systems, Observer design
Abstract: Equivalent circuit models for fuel cell stacks as well as for the series connection of battery cells are characterized by multiple series-connected RC sub-networks. In practical applications, for example, when aiming at the aging detection and monitoring of the individual cells in a fuel cell stack, it is desired to estimate the individual state variables of each of these series-connected cells. The same holds true for battery management systems that are dedicated to the state of charge (resp., voltage) equalization in a series connection of multiple battery cells. However, the pure knowledge of the current through this series connection as well as the sum over all terminal voltages is insufficient to make the overall system model fully observable. To efficiently observe the state variables in each of the series-connected subsystems, we aim at avoiding the measurement of the voltages of each individual fuel (resp., battery) cell. Instead, this paper presents a systematic sensor switching strategy which allows for estimating the individual state variables of all series-connected subsystems in an Unscented Kalman Filter framework. Simulation results are presented to compare the achievable estimation accuracy with a scenario in which all cell (resp., terminal) voltages were measured simultaneously.

Keywords: Linear and nonlinear systems, Mathematical systems theory, Observer design
Abstract: This paper presents a method to analyze the local observability of nonlinear systems with known inputs. For this purpose, an algorithm is presented that performs rank checking of the observability matrix using Lie derivatives. To overcome the limitations associated with inserting initial conditions and symbolically computing the derivatives, Interval arithmetic and Taylor series expansion with automatic differentiation are used. This allows observability to be analyzed over an entire domain. The algorithm provides the intervals for which observability cannot be proven by the rank criterion. This can be helpful when designing real-world applications. Two numerical systems are given as examples, with the first one having a constant input signal and the second one having an analytical input.

Keywords: Mechatronics
Abstract: Ensuring data confidentiality is crucial for all institutions. Providing a secure and fast system is needed to enhance confidentiality. Information security measures should also be identified and implemented to ensure the confidentiality of information security IS data. In this regard, whether the information is confidential during all stages of information capture, processing, storage, and transmission in IS is questionable, and challenging will face enhanced confidentiality. Many techniques have been proposed to protect data confidentiality. One of the best ways to protect data confidentiality is encryption. It is among the most powerful cryptography techniques elliptic curve cryptography (ECC) is available. Elliptic curve cryptography (ECC) is actively researched, and performance for EC-El Gamal is effective and uncomplicated. Public-key cryptography uses the ECC encryption system for asymmetric key encryption. Two parties can communicate simply by generating a public and private key securely. A more secure way to store and retrieve database information that is both convenient and efficient has been created. In this study, some constraints have been executed, preventing any unauthorized system from knowing the usual items used in encryption. Significantly, it will increase the security of information between two parts of communication if we keep some constraints unannounced in public; that is a certain way to save information from any attacks in advance.

Keywords: Modeling and simulation, Optimization, Renewable Energy
Abstract: In this paper, a new absorber film based on SnS thin-layer with gold nanoparticles (Au-NPs) and back grooves texture is investigated. Numerical models based on FDTD method are developed to assess the optical performance of SnS absorber layer. A comparative study between the use of MNPs and back-grooves in SnS thin-film is carried out by estimating the key optical parameters associated with both structures. Particle Swarm Optimization (PSO)-based metaheuristic approach is implemented to boost up the optical performance of SnS thin-film over a broadband spectral range. It is found that the SnS absorber layer with optimized spatial distribution of gold NPs offers the best total absorbance efficiency of 75% as compared to that of SnS thin-films with and without grooves texture (62% and 68%, respectively). This is mainly attributed to plasmonic and the enhanced light scattering effects promoted by the optimized MNPs. Therefore, this interesting optical behavior can open new perspectives for the design of alternative photovoltaic devices based on SnS thin-film

Keywords: Real time systems, Power systems, Fault detection and Diagnostics
Abstract: Non-destructive testing (NDT) using ultrasound (US) is crucial for inspecting nuclear power plant components, including the reactor pressure vessel. Current implementations result in a high cable count system with complex extended routing, which necessitates the development of highly integrated solutions. A novel high-voltage (HV) pulser application-specific integrated circuit (ASIC) was designed, manufactured, and tested as a critical component in a modular multi-element NDT system and is discussed in this paper. A pulser channel occupied 0.0975 mm2 and exhibited 276 µW power consumption from 1.8 V and 5.5 V supplies. The circuit was electrically characterized using a variety of loads and measured in a pulse-echo test with a commercial two-element ultrasound transducer. The results validated the proposed architecture with a 5 MHz transducer, and pulse generation up to 29 MHz was demonstrated with various capacitive loads. The presented design can serve as a means of achieving a tightly integrated system for better reliability and reduced-cost NDT tests.

Keywords: Real time systems, Signal processing, Mechatronics
Abstract: The World Health Organization reports that cardiovascular diseases account for 32% of global deaths, with coronary heart diseases and strokes being significant contributors. Addressing this, our work introduces a new approach using piezoelectric sensors to detect blood clots in vessels, integrating hydrodynamics and blood viscoelasticity theories. This method tracks blood flow changes, helping to identify clot formation or plaque accumulation by analyzing changes in vessel radius and blood velocity. This innovative, non-invasive technique offers a promising tool for blood coagulation monitoring, potentially benefiting global health by aiding in early detection and assessment of cardiovascular risks.

Keywords: Renewable Energy, Power systems, Modeling and simulation
Abstract: Various environmental factors affect the reliability and efficiency of PV systems. Such as geographical factors such as longitude, latitude, and solar energy intensity, in addition to other environmental conditions such as temperature, wind, humidity, pollution, snow, rain, as well as dust. It significantly affects the performance and efficiency of photovoltaic systems. This paper aimed to study and conduct experiments to understand the characteristics of dust and it’s on the electrical output of a grid-connected PV system established in September 2012 at the Libyan Center for Solar Energy Research and Studies (LCSERS) in Tripoli, Libya. Tripoli experiences hot and dusty weather conditions for most of the year, making dust a crucial factor affecting PV utilization. The findings revealed that dust accumulation on the surface of photovoltaic solar modules led to a decrease in both the short circuit current (ISC) and the overall output power, compared to clean modules. The study observed an average degradation rate of 6.1% for efficiencies 9.21% for the fill factor (FF) in indoor experiments, and 11.4% for efficiencies and 7.24% for FF in outdoor experiments. The findings solar panel of the PV-grid-connected system was taken after being exposed to weather conditions in the spring and summer of 2023. Furthermore, the research compared indoor and outdoor experimental results and established a reliable linear relationship. This relationship was found to be applicable for predicting the impact of dust on PV systems in Tripoli City, particularly in coastal areas with similar weather conditions. This study emphasizes the importance of taking into account the factor of dust accumulation on photovoltaic panels when sizing systems, in order to improve performance and avoid breakdow

Keywords: Linear and nonlinear systems, Robust control and Hinfty control, Stochastic control
Abstract: Anisotropy-based analysis problem for linear discrete time invariant systems is studied under the assumption of fixed-point arithmetic of digital controller. A covariance-type constraint is introduced in addition to constraint on mean anisotropy to limit the stochastic variations input disturbance. The relation between the anisotropic norm and the variance of round-off errors is outlined.

Keywords: Bond graphs
Abstract: The emergence of hybrid multi-source platforms presents a promising solution to address the escalating demand for electricity while aligning with sustainable practices. Given the reliance on renewable energy resources, ensuring the reliability of such systems is paramount. This paper proposes a methodology employing bond graph modeling for the design of fault detection and isolation algorithms. The approach utilizes Analytical Redundancy Equations (ARRs) as residual signal generators, embodying the energy conversion principles dictated by the bond graph representation of the system. To generate accurate ARRs, the model must exhibit derivative causality to obviate the need for explicit consideration of unknown initial conditions. This framework enables the detection of diverse fault types and mitigates false alarms through miss detection prevention. The proposed approach is validated using the 20sim software, a well-established platform for bond graph modeling. This methodology offers notable advantages, including expeditious graphical modeling and straightforward implementation of ARRs.

Keywords: Fractional order systems, Robust control and Hinfty control, Multivariable control
Abstract: This paper considers the problem of H∞ control for continuous 2D singular systems described by the Roesser model. A state feedback controller is investigated using linear matrix inequalities (LMIs), such that the closed-loop system is regular, stable, impulse free and guarantee a specified H∞ performance. . A numerical example is presented to show the effectiveness of the proposed method.