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In this work, the fabrication of Rochelle salt based piezoelectric structures is illustrated. Structures composed of paper and Rochelle salt are easily manufactured using simple processes. Both manufacturing and the material itself are environmental friendly. Additionally Rochelle salt is biocompatible. In the paradigm of a cleaner piezoelectric technology, the fabrication of active sensing or actuating devices is developed. Thus processing method, material and piezoelectric properties have been studied: (1) pure crystals are used as acoustic actuator, (2) properties of paper impregnated with Rochelle salt are detailed, (3) charge generation is demonstrated on the impregnated material. Actuating and sensing devices are reported in order to highlight the potential of this green piezoelectric material. [ABSTRACT FROM AUTHOR]

Abstract: Good cross-directional control of sheet variables in a paper machine depends on a number of factors. One such factor is the correct alignment of actuators with their corresponding responses. The alignment changes with time either locally or across the whole paper sheet due to a variety of reasons. In this paper, we provide an online mapping technique based on estimating the cross-correlation between actuator movement and the measurements. This procedure involves two steps–in the first step (called alignment monitoring) we determine if the current mapping is wrong at any CD position, and in the second step (called re-mapping), the alignment of actuators is corrected. The main advantage of this method is in its ability to re-align under closed loop conditions with minimal operational disruption. [Copyright &y& Elsevier]

Sting paper into compatible grades is a necessary step before recycling. Current methods of manually sorting are tedious, slow, andexpensive. High-speed automation of the sorting process will improve the cost efficiency and increase the amount of paperrecycled significantly. Correct identification of the sample in real-time before the sample reaches the actuation stations till remains a challenge because different types of paper and board samples are mixed in a waste stream, and have a lot of variation in terms of color, chemical composition, coating, and printing in black and white and color to different degrees. This primarily is because of a lack of satisfactory sensors and sensor fusion algorithms for sample identification in real-time. In this paper, we identify key parameters that must be measured, discuss a sensor system design, and describe integration of the output from sensors to interpret the type of sample using a fuzzy inference algorithm. Results show that the sensor system proposed is capable of identifying the samples at 90% accuracy compared to manual identification. The sensor system can be integrated onto a conveyor and a ctuation system for automated sorting. [ABSTRACT FROM AUTHOR]

A paper sliceform or lattice-style pop-up is a form of papercraft that uses two sets of parallel paper patches slotted together to make a foldable structure. The structure can be folded flat, as well as fully opened (popped-up) to make the two sets of patches orthogonal to each other. Automatic design of paper sliceforms is still not supported by existing computational models and remains a challenge. We propose novel geometric formulations of valid paper sliceform designs that consider the stability, flat-foldability and physical realizability of the designs. Based on a set of sufficient construction conditions, we also present an automatic algorithm for generating valid sliceform designs that closely depict the given 3D solid models. By approximating the input models using a set of generalized cylinders, our method significantly reduces the search space for stable and flat-foldable sliceforms. To ensure the physical realizability of the designs, the algorithm automatically generates slots or slits on the patches such that no two cycles embedded in two different patches are interlocking each other. This guarantees local pairwise assembility between patches, which is empirically shown to lead to global assembility. Our method has been demonstrated on a number of example models, and the output designs have been successfully made into real paper sliceforms. [ABSTRACT FROM PUBLISHER]

The September 2023 issue of the IETE Journal of Research features 60 articles covering a wide range of topics in electrical engineering. These include communications, electromagnetics, opto-electronics, computers and computing, control engineering, electronic circuits, devices and components, instrumentation and measurements, medical electronics, and power electronics. The articles discuss ongoing research and recent advancements in these fields, presenting innovative approaches and techniques. Some specific examples include securing sensitive data in communications, improving the performance of OFDM systems through deep learning, antenna design and bandwidth enhancement in electromagnetics, and the application of artificial intelligence in the legal field. The issue also covers topics such as image data security and medical applications of electronics. Each research paper in the issue focuses on a specific problem, proposes a solution or method, and provides results and comparisons to demonstrate its effectiveness. The authors of the papers are experts in their respective fields, with extensive experience and qualifications. [Extracted from the article]

Abstract: The automatic control of product moisture content in the paper industry is based upon online moisture measurement. Furthermore, the automatic control of other quality variables such as coat weight may also rely on the moisture measurement. The integrity of infrared radiation (IR) based online moisture measurement systems was studied by performing basic calibrations at the mills with references sealed between two glass plates. The calibrations were performed according to the EN ISO/IEC 17025 standard which is a requirement for calibration laboratories. The observed measurement errors were 2.9% moisture in the first time calibrations at the 95% confidence level. It is demonstrated that these errors can be reduced to under 0.5% moisture by applying traceable methods in the basic calibration, thus improving the integrity of online moisture measurements. Also a standardised algorithm, based on the experience from the performed calibrations, is proposed to ease the adjustment of different moisture measurement systems. [Copyright &y& Elsevier]

Abstract: The construction of electromechanical actuator has been achieved by using the conducting polypyrrole films deposition onto a gold-coated cellophane paper. This is probably the first report of this type of paper actuator. The conducting polypyrrole was electro-generated using either galvanostatic or potentiostatic conditions at 0.5mA/cm2 current density or 0.7V applied potential, respectively. The two types of actuators were constructed, namely: (1) Ppy/cellophane bi-layer; (2) Ppy/cellophane paper/Ppy tri-layer. These actuators showed a reversible and reproducible displacement in acetonitrile solution containing LiClO4 (1M). The maximum displacement of 9.1mm was recorded for tri-layer device and 3.5mm for bi-layer device in 1M LiClO4 acetonitrile solutions. The results obtained in acetonitrile solution containing 1M LiClO4 shows that the actuator requires very low excitation voltage of 0.2MVm−1. The mechanism for this paper actuation phenomenon is addressed in this paper. [Copyright &y& Elsevier]

Abstract: The studies reported here examined differences in user behaviour when presented with a low-fidelity paper prototype compared to fully operational product, and evaluated the effectiveness of different types of enhanced labelling of controls. In the first study with a paper prototype, 30 users of high-pressure washers were asked to choose the settings of the temperature control for different cleaning objects, comparing standard with information-enriched control labelling. In the second study, 34 users operated a real high-pressure washer with different forms of control labelling. The results of both studies provided evidence for some benefits of an information-enriched control labelling over traditional temperature-centred controls labelling. Furthermore, a comparative analysis of the data of the two studies suggested that low-fidelity paper prototypes may have to be used with caution. Therefore, designers need to be aware that the behavioural effects induced by different design modifications may be overestimated when using paper prototypes. The implications of the findings are discussed within the framework of an enlarged concept of fidelity. [Copyright &y& Elsevier]

Examines the cross directional control of coat weight on industrial bent blade coaters. Elimination of automatic control; Development of control strategy; Identification of the active suboptimal dual controller.

Abstract: Hyphenated techniques like Py-GC/MS (pyrolysis-gas chromatography/mass spectrometry) result often in complex chromatograms containing a high information density. Extracting meaningful information is difficult and time consuming. Especially with automatic sampling, data evaluation becomes a major bottleneck. An effective approach to automate the characterization of chromatograms is presented. The database approach consists basically of three steps: measuring reference substances to generate a database, measuring unknown or difficult samples and using the database for the identification of these samples. The compiled database contains a collection of mass spectra of pyrolysis products with data such as retention index and additional information from which reference substances the pyrolysis products may derive. The developed database approach has been tested on designed mixtures of compounds forming “white pitch”. “White pitch” is a typical type of deposit found in paper production processes deriving from chemicals used in coating processes. [Copyright &y& Elsevier]

Abstract: This paper investigates the performance of electro-active paper (EAPap) actuators with thickness variation. EAPap made with cellulose paper, is attractive for biomimetic actuators due to its characteristics in terms of lightweight, biodegradable, dry condition, large displacement output, low actuation voltage and low power consumption. EAPap actuators exhibit a bending deformation in the presence of electric field. However, the performance is sensitive to the thickness of the EAPap material because the thickness is associated with the bending stiffness that strongly affects the bending deformation and the force output of the actuator. Thus, the performance of EAPap actuators that have three different samples of 20, 30, and 40μm thicknesses is tested in terms of tip displacement, blocked force, electrical power consumption, and the efficiency. The sample preparation and the test methods are addressed. The resonance frequency and the bending stiffness are associated with the thickness of the EAPap actuator, and there is an optimum thickness for the best performance of the EAPap actuators. The mechanical output power and the efficiency at an optimal thickness are drastically improved comparing with the previous thickness case. [Copyright &y& Elsevier]

The paper considers a digital model of a wheeled agricultural tractor, as well as algorithms for automatic control of the engine and transmission. Simulation of the working conditions was performed in MATLAB and its applications, Simulink, Sim-scape. The tractor model is based on a systemic approach and includes such subsystems as the engine, transmission, undercarriage, hook load, and control actions from the operator, as well as functions of logic and optimisation for gear shifting. With the help of fundamental blocks of the Matlab package, models of tractor physical components are created. The fundamental blocks of the package serve to model the physical components of the tractor: engine, transmission control system, the transmission that includes friction clutches, gears, shafts ties with the necessary characteristics. Simulation of the working processes of a tractor unit is performed with optimisation of the laws of engine and transmission control according to the criterion of fuel efficiency and maximum power usage. The control system parameters were optimised in the transport mode, as well as in the maximum power mode in the traction range. As an illustration of the use of this analysis method, a solution to the problem of optimisation of an agricultural wheeled tractor operating modes is given. The results of this mathematical simulation are presented in this paper. Parameters of tractor operation control algorithm, which provide minimum fuel consumption in tractor operating cycles, are given. The research results showed the effectiveness of the proposed algorithms and the digital model. The presented digital model allows to debug the operating tractor control algorithms and offers an engineering practice for optimising automatic control of the agricultural tractor engine and transmission. [ABSTRACT FROM AUTHOR]

Recently, cellulose has been re-discovered as a smart material that can be used as sensor and actuator materials, which is termed electro-active paper (EAPap). This paper reports recent advances in paper actuators made with cellulose and hybrid materials such as multi-walled carbon nanotubes, conducting polymers and ionic liquids. Two distinct actuator principles in EAPap actuators are demonstrated: piezoelectric effect and ion migration effect in cellulose. Piezoelectricity of cellulose EAPap is quite comparable with other piezoelectric polymers. But, it is biodegradable, biocompatible, mechanically strong and thermally stable. To enhance ion migration effect in the cellulose, polypyrrole conducting polymer and ionic liquids were nanocoated on the cellulose film. This hybrid cellulose EAPap nanocomposite exhibits durable bending actuation in an ambient humidity and temperature condition. Fabrication, characteristics and performance of the cellulose EAPap and its hybrid EAPap materials are illustrated. Also, its possibility for remotely microwave-driven paper actuator is demonstrated. [ABSTRACT FROM AUTHOR]

The purpose of this study was to gain a better understanding of how and why flight progress strips are currently used in air traffic control towers in the United States. The 3 main staffing positions in the tower, flight-data/clearance delivery (FD/CD), ground control (GC), and local control (LC), were observed by subject-matter experts at 10 control towers. Frequency of occurrence, importance ratings, and type of paper used were recorded. In addition, perceived benefits of marks made on the paper were assessed using open item responses and a series of Likert-scale questions. The positions varied in the marks the controllers made and in their reasons for making the marks. FD/CD controllers tended to make marks because they reduced workload or aided communication. LC tended to make marks because they aided memory, organization, and situation awareness. GC proved to be an interesting hybrid of the FD/CD and LC. [ABSTRACT FROM AUTHOR]

This paper presents a receding horizon optimal control (RHOC) method with an economic objective function for balancing the cost of resources (resource use × cost) with income through yield (yield × product price). This paper considers the two elements that determine the income through yield. The first element is yield and associated fruit development. A new, computationally viable, approach to model the income through yield is proposed and its prediction accuracy with respect to the original model is evaluated. The new approach employs a model that predicts at each time step, the future income through yield based on the assimilates partitioned to the fruits at the current time step. Simulations suggest that the assumptions made to arrive at the model for the new approach, do not significantly affect the accuracy of the predictions. The second element considered in this paper is the product price and the uncertainty inherent in its forecasts. Historical product price data are used to generate artificial product price forecasts. An uncertainty analysis, in combination with the artificial product price forecasts, showed that the product price forecast error does not considerably affect the optimised control strategy. Season-wide simulations with RHOC suggest that the product price forecast error does not considerably affect the value of the economic objective function. • A computationally viable approach to model the income through yield is proposed. • The new approach to model income through yield allows for RHOC with a short horizon. • Historical product price data are used to create artificial product price forecasts. • Product price forecast errors do not considerably affect the control strategy. [ABSTRACT FROM AUTHOR]

This article focuses on the development of a computer-aided formulation of silica defoamers for the paper industry. It also provides information on the standard way of making paper as well as some problems encountered during the manufacturing process. The mentioned computer-aided formulation of silica defoamers is based on a nonlinear programming model. The nonlinear programming model is developed based on an empirical equation of the defoamer's performance as well as on a deterministic equation of ingredient cost. Paper manufacturers confirmed the validity of the predicted optimal formula in four out of five paper plant trials.

Discusses the basics of process control on pulp and paper production. Differences between the PID setpoint and the process variable; Role of correct loop tuning; Usability and function of multi-variable model predictive control technology.

Proportional - Integral - Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. However PID controller is poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This research comes up with a soft computing approach involving Genetic Algorithm, Evolutionary Programming, Particle Swarm Optimization, Bacterial Foraging Optimization and heuristic algorithm bacterial foraging combine with particle swarm optimization. The proposed soft computing is used to tune the PID parameters and its performance has been compared with the conventional method Ziegler Nichols. The results obtained reflect that use of soft computing based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. This research addresses comparison of tuning of the PID controller using soft computing techniques on moisture control system in paper machine (Machine Direction). [ABSTRACT FROM AUTHOR]

This paper describes a human interface design concept of automated driving systems. Control authority while using the automated systems will be back to the driver due to the operational limitation of the automated systems of Level 2 and 3. The human interface design of the automated systems in the transition process is essential for enhancing the driver's acceptance of the information provided or the automated controls. In this study, we propose the interface design of the “Request to Intervene (RtI)” that is determined based on the difference between a driver capability and a task demand (contributed by the task‐capability interface model). This concept suggests that when the driver capability exceeds the task demand before the transition mode, the transition will be successfully completed; however, the control authority cannot return to the driver smoothly and comfortably if the task demand is higher than the driver capability. In this paper, occlusion method is introduced as an estimation method of the task demand while driving. Evaluation indices for applying to a driver monitoring system is introduced, which measures the driver capability while the automated system is active. Driving simulator experiments were conducted to investigate the relationship between the driver capability and the task demand under manual drives. [ABSTRACT FROM AUTHOR]

Studies the role of automatic control theory that lead to system methodologies of identification for various types of applied problems. System methodologies developed for the practical use of the mathematical apparatus of the theory; Orientation of research activity to realization and detailed description of the rational structure of identification within the framework of various search systems; Provision of the subject of identification with informational support for transformation of the difficult-to-formalize conditions.

Mathematical models of energy systems have been mostly represented by either linear or nonlinear ordinary differential equations. This is consistent with lumped-parameter dynamic system modeling, where dynamics of system state variables can be fully described only in the time domain. However, when dynamic processes of energy systems display both temporal and spatial evolutions (as is the case of distributed-parameter systems), the use of partial differential equations is necessary. Distributed-parameter systems, being described by partial differential equations, are mathematically (and computationally) much more difficult for modeling, analysis, simulation, and control. Despite these difficulties in recent years, quite a significant number of papers that use partial differential equations to model and control energy processes and systems have appeared in journal and conference publications and in some books. As a matter of fact, distributed-parameter systems are a modern trend in the areas of control systems engineering and some energy systems. In this overview, we will limit our attention mostly to renewable energy systems, particularly to partial differential equation modeling, simulation, analysis, and control papers published on fuel cells, wind turbines, solar energy, batteries, and wave energy. In addition, we will indicate the state of some papers published on tidal energy systems that can be modelled, analyzed, simulated, and controlled using either lumped or distributed-parameter models. This paper will first of all provide a review of several important research topics and results obtained for several classes of renewable energy systems using partial differential equations. Due to a substantial number of papers published on these topics in the past decade, the time has come for an overview paper that will help researchers in these areas to develop a systematic approach to modeling, analysis, simulation, and control of energy processes and systems whose time–space evolutions are described by partial differential equations. The presented overview was written after the authors surveyed more than five hundred publications available in well-known databases such as IEEE, ASME, Wiley, Google, Scopus, and Web of Science. To the authors' best knowledge, no such overview on PDEs for energy systems is available in the scientific and engineering literature. Throughout the paper, the authors emphasize novelties, originalities, and new ideas, and identify open problems for future research. To achieve this goal, the authors reviewed more than five hundred journal articles and conference papers. [ABSTRACT FROM AUTHOR]

The following paper was selected for the 2018 IEEE Transactions on Control Systems Technology Outstanding Paper Award from papers that appeared in 2016–2017: “Multimode Q Control in Tapping-Mode AFM: Enabling Imaging on Higher Flexural Eigenmodes” by Michael G. Ruppert and S. O. Reza Moheimani Vol. 24, No. 4, pp. 1149–1159, July 2016. [ABSTRACT FROM AUTHOR]

This paper proposes a more efficient water monitoring and control system for water utilities to address the current water wastage problem, utilizing IoT and Android applications. The integrated system aims to enhance real-time data collection, analysis, and remote management, empowering water utilities to optimize resource usage and mitigate environmental impact. Conventional water tanks cannot monitor or control the water level in the tank, leading to a significant amount of wastage. Implementing smart water tank systems with automated monitoring and control features can not only prevent wastage but also enhance overall water management efficiency. Ultrasonic sensors are used to measure the water level, while other parameters such as pH, TDS, and turbidity of the water should be calculated. Additionally, these sensors play a crucial role in ensuring accurate and real-time monitoring of water quality in various applications, such as industrial processes, aquaculture, and environmental monitoring. The integration of ultrasonic technology for water level measurement enhances the overall efficiency and reliability of water management systems. The calculated values from the sensors can be processed by the microcontrollers and uploaded to the internet through the Wi-Fi module (ESP 8266). Some other technologies have certain drawbacks in one way or another. The removal of these shortcomings and the provision of an efficient and economical solution have been the main focus of this paper. Through extensive research and innovation, our team has strived to overcome these limitations, paving the way for a more robust and seamless technological landscape. [ABSTRACT FROM AUTHOR]

Automatic light control systems have garnered significant attention for their potential to enhance energy efficiency and user convenience across various settings. This paper provides a comprehensive overview of these systems, elucidating their principles, components, applications, and associated benefits. The primary objective of automatic light control systems is to intelligently regulate lighting levels based on environmental factors such as occupancy, ambient light, and time of day. Various sensors, including Passive Infrared (PIR), ultrasonic, and photoresistors, are commonly employed to detect changes in the surroundings and trigger appropriate lighting adjustments. Advanced control algorithms and communication protocols facilitate seamless integration with building automation systems, enabling centralized management and optimization of lighting across diverse zones. Moreover, the advent of smart lighting solutions leveraging Internet of Things (IoT) platforms enables remote monitoring and control, empowering users to personalize lighting preferences and further optimize energy consumption. The paper critically reviews the key features, benefits, and challenges associated with automatic light control systems, underscoring their pivotal role in promoting sustainability, comfort, and cost-effectiveness in both residential and commercial environments. Additionally, the paper discusses future research directions, highlighting opportunities for innovation in sensor technology, data analytics, and human-centric lighting design to propel the capabilities and adoption of these systems. [ABSTRACT FROM AUTHOR]

To ensure optimal use of images while preserving privacy, it is necessary to partition the shared image into public and private areas, with public areas being openly accessible and private areas being shared in a controlled and privacy-preserving manner. Current works only facilitate image-level sharing and use common cryptographic algorithms. To ensure efficient, controlled, and privacy-preserving image sharing at the area level, this paper proposes an image partition security-sharing mechanism based on blockchain and chaotic encryption, which mainly includes a fine-grained access control method based on Attribute-Based Access Control (ABAC) and an image-specific chaotic encryption scheme. The proposed fine-grained access control method employs smart contracts based on the ABAC model to achieve automatic access control for private areas. It employs a Cuckoo filter-based transaction retrieval technique to enhance the efficiency of smart contracts in retrieving security attributes and policies on the blockchain. The proposed chaotic encryption scheme generates keys based on the private areas' security attributes, largely reducing the number of keys required. It also provides efficient encryption with vector operation acceleration. The security analysis and performance evaluation were conducted comprehensively. The results show that the proposed mechanism has lower time overhead than current works as the number of images increases. [ABSTRACT FROM AUTHOR]

In order to scientifically and rationally evaluate the susceptibility to landslide hazards in Tekes County, Yili State. This paper takes Tekes County in Xinjiang as an example, on the basis of a comprehensive analysis of the regional geological environment conditions and the distribution pattern and formation conditions of geological disasters, using the data of geological disaster points (landslide center points), and through the correlation matrix calculation of the evaluation factors, the nine evaluation factors with larger absolute values of correlation coefficients were determined to construct the evaluation system of the susceptibility to landslide geological hazards in Tekesi County. Combining the information quantity method and the entropy value method, using the weights determined by the entropy value method, the information quantity method is used to calculate the information quantity value of each factor within the factor, calculate the susceptibility index of landslide geological disasters within the territory of Tekes County, and then carry out the landslide susceptibility evaluation. The susceptibility of landslide disasters was evaluated by ArcGIS. The results show that the landslide disaster susceptibility level in Tekes County can be divided into four levels: high susceptibility, medium susceptibility, low susceptibility, and not susceptible, with areas of 491.3276 km2, 1181.5171 km2, 1674.7609 km2 and 5295.2976 km2 accounting for 5.68%, 13.67%, 19.38% and 61.27% of the total area of Tex County, respectively. The AUC number obtained by the success curve method (ROC) is 0.8736, reflecting the evaluation accuracy of 87.36%, indicating that the model method used in this paper is effective. The results are expected to provide practical data support for landslide disaster control in Tekes County and provide a reference for geological disaster monitoring, early warning and engineering prevention and control deployment in Yili Valley. [ABSTRACT FROM AUTHOR]

Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as "Porpoising". This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems. [ABSTRACT FROM AUTHOR]

Autonomous berthing technology is a crucial engineering control problem within the ship intelligence system, encompassing a series of complex operations and technologies. Firstly, this paper analyses the research on autonomous berthing technology from a bibliometric point of view in order to obtain an overview of its past and present development and to outline the importance of this technology. Secondly, a literature review is conducted on each of the four aspects of autonomous berthing technology, namely sensing technology, berthing type, control method, and evaluation method, which can help to quickly understand the main aspects of this technology. Thirdly, the ship-assisting technologies needed to achieve autonomous berthing are discussed and analysed from six aspects: dynamic collision avoidance, path planning, path tracking, heading control, tug assistance, and shore-based systems. Finally, the challenges faced by the ship autonomous berthing technology on the way of development are summarised, and future development is projected. This paper aims to provide a more comprehensive perspective for analysing and researching ship autonomous berthing technology. [ABSTRACT FROM AUTHOR]

In this paper, we first propose a novel fully-decoupled, linear and second-order time accurate scheme to solve the phase-field model of non-Newtonian two-phase flows; the developed scheme is based on a stabilized Scalar Auxiliary Variable (SAV) approach. We strictly prove the unconditional energy stability of the scheme and conduct a numerical simulation to show the accuracy and stability of the proposed scheme. Moreover, we can observe that the parameter r in non-Newtonian fluids can affect spatial patterns during phase transitions, which directly enables us to design and perform optimal control experiments in engineering processes. [ABSTRACT FROM AUTHOR]

Software Defined Networking (SDN) is a paradigm shift in the network industry with decoupling of control and data plane. This helps network engineers to control and manage their network from centralized controller and troubleshoot the network at much better pace. With the benefits that SDN provides, it also has some vulnerable to attacks like Distributed Denial of Service (DDoS) that can disrupt the availability of the network. Most of the recent research work in DDoS detection and mitigation is done over Traditional network environments and packet limit strategy is used for mitigation by researchers with very less focus on redirection of illegitimate traffic which can result in less downtime and helpful in network analysis. The major contribution of this paper is detection and mitigation of DDoS in Software Defined Networks. We have created our own DDoS dataset with over 1.7 million entries. For Detection, we have used two different methods: (1) Snort (IDS) and (2) Machine Learning. In Machine Learning, we have used eight different Machine Learning algorithms that also include Ensemble Classifier and a Hybrid method of SVM-RF. We were able to get 99.1% accuracy which is a substantial growth as compared to recent works. For Mitigation, we have again used two methods: (1) Drop illegitimate traffic and (2) Redirect Illegitimate traffic. Results showed that hybrid SVM-RF algorithm works better as compared to individual Machine Learning algorithms and also as mitigation depends on Detection accuracy, so, the better the detection, the better the mitigation. In this paper detection and mitigation of DDoS has been performed over a SDN network. In which We have created our own dataset with over 1.7 million entries. For detection we have used two method: Snort (IDS), and Machine Learning and for Mitigation, Drop illegitimate traffic, and Redirect Illegitimate traffic. [ABSTRACT FROM AUTHOR]

The mystery of soaring birds, such as albatrosses and eagles, has intrigued biologists, physicists, aeronautical/control engineers, and applied mathematicians for centuries. These fascinating avian organisms are able to fly for long durations while expending little to no energy, utilizing wind to gain lift. This flight technique/maneuver is called dynamic soaring (DS). For biologists and physicists, the DS phenomenon is nothing but a wonder of the very elegant ability of these birds to interact with nature and use its physical ether in an optimal way for better survival and energy efficiency. For the engineering community, the DS phenomenon is a source of inspiration and an unequivocal opportunity for biomimicking. Mathematical characterization of the DS phenomenon in the literature has been limited to optimal control configurations that utilized developments in numerical optimization algorithms along with control methods to identify the optimal DS trajectory taken (or to be taken) by the bird/mimicking system. Unfortunately, all of these methods are highly complex and non-real-time. Hence, the mathematical characterization of the DS problem, we believe, appears to be at odds with the phenomenon/birds-behavior. In this paper, we provide a novel twolayered mathematical approach to characterize, model, mimic, and control DS in a simple real-time implementation, which we believe more effectively decodes the biological behavior of soaring birds. First, we present a differential geometric control formulation and analysis of the DS problem, which allow us to introduce a control system that is simple yet controllable. Second, we establish a link between the DS philosophy and a class of dynamical control systems known as extremum seeking systems. This linkage provides the control input that makes DS a real-time reality. We believe our framework accurately describes the biological behavior of soaring birds and opens the door for geometric control theory and extremum seeking systems to be utilized in biological systems and natural phenomena. Simulation results are provided along with comparisons to powerful optimal control solvers, illustrating the advantages of the introduced method. [ABSTRACT FROM AUTHOR]

This paper presents an active fault-tolerant flight control system (FCS) design for the dual-system/hybrid VTOL UAV configuration that maximally exploits its inherent over-actuation abilities to provide higher levels of fault-tolerance and reliability compared to that of the other VTOL UAVs configurations up to this point. The significance of this study is to convert the main drawback of having the vertical rotors as dead weights during the cruise to a key advantage where all the UAV's controls are kept active during all the flight phases raising the UAV's fault-tolerance and maneuverability abilities. The FCS proposed elaborates on a new architecture for the hierarchical automatic control loops using the dynamic inversion control to design the trajectory tracking virtual commands and employing optimal dynamic control allocation to optimally resolve the controls redundancy. Regarding fault-tolerance, the presented FCS handles simultaneous failures and jamming of all the control surfaces during flight where the control commands to the healthy controls (vertical rotors) were automatically adapted such that the trimming and trajectory tracking were successfully maintained till the mission end. Additionally, this paper addresses for the first time the employment of the controls redundancy to enhance the VTOL UAV's maneuverability in fault-free cases, where we present a study of reducing the minimum turn radius of the UAV when the vertical rotors are employed with the control surfaces during the maneuver. A reduction of 38% in the coordinated steady-level minimum turn radius turn at 35 m/sec flight speed was achieved. [ABSTRACT FROM AUTHOR]

Human activities overwhelm our environment with CO2 and other global warming issues. The current electricity landscape necessitates a superior, continuous power supply and addressing such environmental concerns. These issues can be resolved by incorporating renewable energy sources (RESs) into the utility grid. Thus, this paper presents an optimized hybrid fuzzy logic self-tuning PID controller to control the automatic generation control (AGC) of various renewable sources. This controller regulates the frequency deviations of the power system and governs the change in the tie-line load of a multi-area hybrid energy system composed of wind, biomass, and photovoltaic energy sources. MATLAB Simulink software was applied to design and test the system. The PID controller has been tuned using four algorithms, namely, genetic algorithm (GA), pattern search (PS), simulated annealing (SA), and particle swarm optimization (PSO), and we compared the results with the proposed novel optimized PID controller (GA-fuzzy logic self-tuning technique) to validate it. The results show the superiority of the proposed hybrid GA-fuzzy logic self-tuning algorithm over the other algorithms in bringing the power system back to its regular operation. The paper also proposes an operation strategy to lower the utilization of biomass energy in the presence of other renewable energy sources. [ABSTRACT FROM AUTHOR]

This document is a review of advanced digital technologies in modeling and control of technological processes. It highlights the importance of international collaboration in scientific research and the sharing of knowledge and resources. The special issue includes studies in various fields such as mining, mineral processing, vision and image processing systems. The papers cover topics such as power quality data collection, energy generation estimation, predictive models for fault detection, virtual soft sensors, autonomous transportation control systems, machine learning for the oil and gas industry, optical inspection systems, image encryption, critical velocity prediction, computational fluid dynamics, and steel defect recognition. The contributions provide valuable insights and potential solutions for improving efficiency and sustainability in different industries. [Extracted from the article]

The presence of decentralized production in modern electrical systems precludes traditional automatic generation control (AGC) strategies. Renewable energy production is highly dependent on the environment; for example, photovoltaic (PV) system, but its power generation is very unstable, which makes power grids containing PV systems face greater challenges. In this paper, we propose a PV-grid control method based on self-gain system compensation to reduce the negative effects of large fluctuations and uncertainties in solar energy production. First, the performance characteristics of solar modules are discussed and a multi-region model with a system with high penetration of solar systems is built. The AGC power is then displayed with different power variations according to different maximum power point tracking methods to analyze the uncertainty and variation of the PV output power and its effects on the AGC. We have also developed and implemented a compensation unit to eliminate the negative effects of PV power on AGC. Finally, the proposed method was demonstrated using the load from the example step as a disturbance variable to obtain a dynamic model of a dual-zone switched grid AGC with two PV systems based on a DMPC-distributed model. As a result of the simulation, the proposed method in this paper can guarantee the excellent properties of the dynamic behavior of the AGC system with large variations and high uncertainty of the PV system, and the validity of the proposed method have also been confirmed. [ABSTRACT FROM AUTHOR]

Presents the recipients of the IEEE Transactions on Control Systems Technology Outstanding Paper Award. [ABSTRACT FROM AUTHOR]

There are two technical challenges in predicting slope deformation. The first one is the random displacement, which could not be decomposed and predicted by numerically resolving the observed accumulated displacement and time series of a landslide. The second one is the dynamic evolution of a landslide, which could not be feasibly simulated simply by traditional prediction models. In this paper, a dynamic model of displacement prediction is introduced for composite landslides based on a combination of empirical mode decomposition with soft screening stop criteria (SSSC-EMD) and deep bidirectional long short-term memory (DBi-LSTM) neural network. In the proposed model, the time series analysis and SSSC-EMD are used to decompose the observed accumulated displacements of a slope into three components, viz. trend displacement, periodic displacement, and random displacement. Then, by analyzing the evolution pattern of a landslide and its key factors triggering landslides, appropriate influencing factors are selected for each displacement component, and DBi-LSTM neural network to carry out multi-data-driven dynamic prediction for each displacement component. An accumulated displacement prediction has been obtained by a summation of each component. For accuracy verification and engineering practicability of the model, field observations from two known landslides in China, the Xintan landslide and the Bazimen landslide were collected for comparison and evaluation. The case study verified that the model proposed in this paper can better characterize the "stepwise" deformation characteristics of a slope. As compared with long short-term memory (LSTM) neural network, support vector machine (SVM), and autoregressive integrated moving average (ARIMA) model, DBi-LSTM neural network has higher accuracy in predicting the periodic displacement of slope deformation, with the mean absolute percentage error reduced by 3.063%, 14.913%, and 13.960% respectively, and the root mean square error reduced by 1.951 mm, 8.954 mm and 7.790 mm respectively. Conclusively, this model not only has high prediction accuracy but also is more stable, which can provide new insight for practical landslide prevention and control engineering. [ABSTRACT FROM AUTHOR]

Abstract  Cellulose-chitosan laminated films were made for Electro-Active Paper (EAPap) actuators and the effect of chitosan and different types of free ions namely, Cl−, NO3− and CF3COO− were investigated on the actuation behavior. The fabrication process of the films was explained and the actuation performance was tested in terms of bending displacement of the actuators. It was observed that, chitosan content and type of free ions influence the tip displacement of the actuators. Cl− was found the best free ion among others, and detail observations are explained. By laminating chitosan layer on the cellulose films, the humidity sensitiveness of cellulose EAPap actuators was reduced. [ABSTRACT FROM AUTHOR]

Focuses on the challenges in the detection, diagnosis and visualization of controller performance data in the refining, petrochemical, pulp and paper and the mineral processing industries. Factors that affect monitoring and diagnosing control problems; Techniques for extracting information relevant to controller performance monitoring; Implementation of an advanced control strategy.

This section is based on selected papers from the 6th and 7th ERCIM workshops on Formal Methods in Industrial Critical Systems. These papers either extend the state of the art in model checking and automatic test generation or they address the methodology for applying tools based on formal methods. Also, some important experiences are reported from industrial cases in which formal methods have been applied. [ABSTRACT FROM AUTHOR]

This paper deals with a simulation assessment of the impact of the introduction of ETCS L2 and L3 on the capacity of railway lines. The simulation itself is carried out in the OpenTrack simulation software, especially in the tool headway calculator. For this research, an infrastructure model has been built, which represents a typical layout of lines and stations in the Czech Republic. By successive modifications of the model, the significance of the impact of the implementation of ATP systems on the capacity of lines can be simulated. In the paper, the influence of the implementation of different application levels of ATP systems on the capacity of railway lines is evaluated. [ABSTRACT FROM AUTHOR]

During the operation of automatic navigation rice transplanter, the accuracy of path tracking is influenced by whether the transplanter can enter the stable state of linear path tracking quickly, thus affecting the operation quality and efficiency. To reduce the time to enter the path tracking stable state and improve the tracking accuracy and stability for the rice transplanter, path tracking control method based on variable universe fuzzy control (VUFC) and improved beetle antenna search (BAS) is proposed in this paper. VUFC is applied to achieve adaptive adjustment of the fuzzy universe by dynamically adjusting the quantization and scaling factors according to the variations of errors by the contraction–expansion factor. To solve the problem of setting the contraction–expansion factor in VUFC and real-time performance, an offline parameter optimization method is presented to calculate the optimal contraction–expansion factor by an iterative optimization algorithm in a path tracking simulation model, where the iterative optimization algorithm is the BAS algorithm improved by the isolated niching technique and adaptive step size strategy in this paper. To verify the effectiveness of the proposed path tracking control method, simulation and field linear path tracking experiments were carried out. Experimental results indicate that the proposed method reduces the time of entering the stable state of linear path tracking and improves the accuracy and stability of path tracking compared with the pure pursuit control method. [ABSTRACT FROM AUTHOR]

Efficient control of tunnel boring machine (TBM) tunneling along the designed tunnel axis in an unknown variable geological environment is a difficult and significant task. At present, the TBM attitude during tunneling is mostly manually controlled based on the deviation between the tunneling axis and the designed tunnel axis and their experiences. The tunneling axis from manual control is often the snakelike motion around the designed tunnel axis, even exceeding the deviation limit, for which this paper analyzed three reasons, the unknown geological environment, the hysteresis of TBM position response, and the unsolved overall optimization of tunneling axis. For these reasons, this paper proposed a real-time optimal control framework of TBM attitude based on reinforcement learning, which contains the geological information predictive model, TBM attitude and position (TBMAP) predictive model, and optimal attitude control policy (OACP). This framework can predict the current geological information in real-time and provide the corresponding real-time optimal attitude control that simultaneously considers the hysteresis of TBM position response and the overall optimization of the tunneling axis. This attitude control framework can be directly deployed to TBM without increasing costs and excessive modifications to the equipment. To verify the effectiveness of this attitude control framework, the Xinjiang Yiner Water Supply Phase II Project, using the TBM method, was adopted as a case study. The results revealed that the accuracy of geological environment recognition reached 94%, and OACP can significantly reduce the accumulated deviation of the tunneling axis from the designed tunnel axis by over 80% compared with the manual control and easily provide real-time decision support for attitude control in actual engineering. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to test the performance of the designed automatic control system based on the Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) algorithms during landing of the helicopter on the ship deck. This paper is a further development of the series based on Topczewski et al. (2020). Design/methodology/approach: The system consists of two automatic control algorithms based on LQR and the LQG. It is integrated with the ship motion prediction system based on autoregressive algorithm with parameters calculated using Burg's method. It is assumed that the source of necessary navigation data is integrated Inertial Navigation System with Global Positioning System. Landing of the helicopter on the ship deck is performed in automatic way, based on the preselected procedure. Performance of the control system is analyzed when all necessary navigation data is available for the system and in case when one of the parameters is unavailable during performing the procedure. Findings: In this paper, description of the designed control system developed for performing the approach and landing of the helicopter using selected procedure is presented. Helicopter dynamic model is validated using the manufacturer data and by test pilots, overview is presented. Necessary information about ship motion model is also included. Tests showing mission performance while using LQR and LQG algorithms applied to the control system are presented and analyzed, taking into account both situations when full navigation data is available/unavailable for the control system. Practical implications: Results of the system performance analyses can be used for selection of the proper control methodology for prospective helicopters autopilots. Furthermore, the system can be used to analyze the mission safety when information about one of the navigation parameters is identified by the navigation system as unavailable or incorrect and therefore unavailable during landing on the ship deck. Originality/value: In this paper, control system dedicated for the automatic landing of the helicopter on the ship deck, based on two different control algorithms is presented. Influence of lack of information about one of the navigation parameters on the mission performance is analyzed. [ABSTRACT FROM AUTHOR]