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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]

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]

High precision and low complexity control algorithm plays an important role in the developing of the end-effector instrumentation of different robot manipulators. In order to reduce the kinetic energy and the high-speed drift phenomenon of the repetitive motion tracking task, the robot manipulator needs to calibrate its configuration. In this paper, we formulate the configuration calibration of the robot manipulator for the repetitive motion task as a future quadratic programming optimization problem constrained with equality constraints, which is also regarded as a fundamental problem in artificial intelligence and modern control engineering. Zhang neural network, which is a canonical method, can be adopted to deal with the continuous form of the future optimization problem, named as temporally dependent quadratic programming problem with equality constraints. In order to overcome the issue of temporally dependent inverse computing, a novel Zhang neural network model and its uncertain disturbance tolerant model, which are termed as filtered reciprocal-kind Zhang neural network model and uncertain disturbance tolerant filtered reciprocal-kind Zhang neural network model, respectively, are proposed by integrating the energy-type cost function and Zhang neural network design formula for solving the temporally dependent quadratic programming problem with equality constraints in this paper. Based on the Euler discrete formula and the models, the discrete filtered reciprocal-kind Zhang neural network and the discrete uncertain disturbance tolerant filtered reciprocal-kind Zhang neural network algorithms are proposed for solving the future quadratic programming problem with equality constraints and the robot manipulator configuration calibration problem of repetitive motion. The convergence properties of the reciprocal-kind Zhang neural network model and its corresponding uncertain disturbance tolerant model are obtained by Lyapunov stability theory of nonlinear system and its corresponding perturbed system, while the convergence property of the filtered reciprocal-kind Zhang neural network model is analyzed by the limit thinking. For the repetitive motion task, three experiments for solving the configuration calibration problem of PUMA560, Kinova Jaco2, and Franka Emika Panda robot manipulators are performed to illustrate the effectiveness, robustness and superiority of our proposed discrete filtered reciprocal-kind Zhang neural network algorithms. • A novel configuration calibration scheme of the robot manipulators is formulated. • An inverse-free Zhang neural network algorithm is proposed. • The proposed algorithm is robustness under uncertain disturbance environment. [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 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]

In this paper, the flexural wave propagation and its control of a novel piezoelectric composite pipe conveying fluid are investigated. Dual piezoelectric layers used as sensor and actuator are periodically arranged on the pipe, and a feedback amplifying circuit is applied from sensor to actuator, forming a self-powered phononic crystal (PC) control structure. The vibration reduction performance can be actively tuned by adjusting the feedback control gain instead of conventional changing the construction of pipe itself. The pipe is composed of functionally graded material (FGM), in which the material properties vary continuously along the radial direction, and a poroelastic medium is introduced. By using the Timoshenko beam theory and Hamilton's principle, a set of electromechanical coupling equations governing flexural vibration of the pipe is deduced. The band structure, band gap (BG) distribution and frequency response are presented by applying the spectral element technology. Comprehensive parametric studies are carried out. The results obtained validate the excellent vibration control effect of the proposed design, and further demonstrate the significant impacts of material, piezoelectric layers, feedback control and flowing fluid on the BG characteristics. This paper is expected to provide a technological reference for the vibration and elastic wave control of engineering composite pipe structures. [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 paper refers to the study of applications of complex SEE (Sadaq-EmadEmann) integral transform on various functions. In this paper, we have applied complex SEE transform on some special functions including the Mittag-Leffler function, Generalized function, piecewise continuous function, and integrals. Additionally, we apply the complex SEE integral transform to determine the transfer function of mechanical systems and control engineering. As well as, present and discuss the Beam problem by utilizing complex SEE transform. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to solve the challenging problem of automatic carrier landing with the presence of environmental disturbances. Therefore, a global fast terminal sliding mode control (GFTSMC) method is proposed for automatic carrier landing system (ACLS) to achieve safe carrier landing control. Design/methodology/approach: First, the framework of ACLS is established, which includes flight glide path model, guidance model, approach power compensation system and flight controller model. Subsequently, the carrier deck motion model and carrier air-wake model are presented to simulate the environmental disturbances. Then, the detailed design steps of GFTSMC are provided. The stability analysis of the controller is proved by Lyapunov theorems and LaSalle's invariance principle. Furthermore, the arrival time analysis is carried out, which proves the controller has fixed time convergence ability. Findings: The numerical simulations are conducted. The simulation results reveal that the proposed method can guarantee a finite convergence time and safe carrier landing under various conditions. And the superiority of the proposed method is further demonstrated by comparative simulations and Monte Carlo tests. Originality/value: The GFTSMC method proposed in this paper can achieve precise and safe carrier landing with environmental disturbances, which has important referential significance to the improvement of ACLS controller designs. [ABSTRACT FROM AUTHOR]

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]

This research paper proposes a new implementation of a long short-term memory network for active fault-tolerant control subjected to single and multiple undiagnosable sensor faults. There are two networks used: the first performs as a diagnosis for automated manufacturing systems and can identify faulty sensors, while the second acts as an inverse model of these systems and is used to determine the reconfigured control action to take when sensors are not functioning as expected. The Factory I/O simulator is interfaced with MATLAB to simulate and verify the proposed approach for automated material handling case study with faultless and multiple fault sensors. Four sensors of the case study out of six are tolerated. [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]

The development of digital techniques in control engineering leads to the creation of innovative algorithms for measuring specific parameters. In the field of electric power engineering these parameters may be amplitude, phase and frequency of voltage or current occurring in the analyzed electric grid. Thus, the algorithms mentioned, applied in relation to the quoted parameters, may provide precise and reliable measurement results in the electric grid as well as ensure better grid monitoring and security. Signal analysis regarding its identification due to the type of interference is very difficult because the multitude of information obtained is very large. In order to indicate the best method for determining errors in measuring synchronous parameters of the measured current or voltage waveforms, the authors propose in this paper a new form of one error for all testing functions, which is called an equivalent error. This error is determined for each error's value defined in the applicable standards for each of selected 15 methods. The use of the equivalent error algorithm is very helpful in identifying a group of methods whose operation is satisfactory in terms of measurement accuracy for various types of disturbances (both in the steady state and in the dynamic state) that may occur in the power grid. The results are analyzed for phasor measurement unit (PMU) devices of class P (protection) and M (measurement). [ABSTRACT FROM AUTHOR]

Differing from the response control in civil and engineering applications, the excitation in a closed-loop sensing system is unknown and the control is designed to balance and measure the unknown excitation in real time. In this paper, a novel optimal force-balance control for a closed-loop sensing system with time delay is proposed. By introducing the errors between the control force and the unknown input as new variables, the force-balance control problem is transformed into a response minimization one with a time delay. Then, the discretization method is applied, and the continuous time system with time delay is converted into an extended discrete system without time delay, from which the analytical expression of the optimal force-balance control force is obtained. To illustrate the effectiveness of the proposed control, the optimal control of a practical quartz flexible force-balance accelerometer (FBA) is solved as an application. Numerical results show that the proposed control can realize the accurate measurement of wide-band random acceleration signals with a time delay of up to 10 times of control period. Besides, the proposed control can also significantly inhibit the vibration response of the FBA while guaranteeing measurement accuracy, which will benefit the obtaining of a large dynamic measurement range as a sensing application. [ABSTRACT FROM AUTHOR]

In this paper, we present a re-established functional fractal circuit model of arterial blood flow that incorporates the shunt effect of the branch vessels. Under the background of hemodynamics, we abstracted a family of fractal operators and investigate the kernel function and properties thereof. Based on fractal operators, the intrinsic relation between Bessel function and Struve function was revealed, and some new special functions were found. The results provide mathematical tools for biomechanics and automatic control. [ABSTRACT FROM AUTHOR]

As digitalization is permeating all sectors of society toward the concept of "smart everything," and virtual technologies and data are gaining a dominant place in the engineering and control of intelligent systems, the Digital Twin (DT) concept has surfaced as one of the top technologies to adopt. This paper discusses the DT concept from the viewpoint of Modeling and Simulation (M&S) experts. It both provides literature review elements and adopts a commentary-driven approach. We first examine the DT from a historical perspective, tracing the historical development of M&S from its roots in computational experiments to its applications in various fields and the birth of DT-related and allied concepts. We then approach DTs as an evolution of M&S, acknowledging the overlap in these different concepts. We also look at the M&S workflow and its evolution toward a DT workflow from a software engineering perspective, highlighting significant changes. Finally, we look at new challenges and requirements DTs entail, potentially leading to a revolutionary shift in M&S practices. In this way, we hope to foster the discussion on DTs and provide the M&S expert with innovative perspectives. [ABSTRACT FROM AUTHOR]

Molecular communication (MC) is a concept in communication engineering, where diffusive molecules are used to transmit information between nano or micro-scale chemical reaction systems. Engineering MC to control the reaction systems in cells is expected for many applications such as targeted drug delivery and biocomputing. Toward control of the reaction systems as desired via MC, it is important to transmit signals without distortion by MC since the reaction systems are often triggered depending on the concentration of signaling molecules arriving at the cells. In this paper, we propose a method to analyze signal distortion caused by diffusion-based MC channels using frequency response of channels. The proposed method provides indices that quantitatively evaluate the magnitude of distortion and shows parameter conditions of MC channels that suppress signal distortion. Using the proposed method, we demonstrate the design procedure of specific MC channels that satisfy given specifications. Finally, the roles of MC channels in nature are discussed from the perspective of signal distortion. [ABSTRACT FROM AUTHOR]

The nonlinear system control is a classical problem in control engineering. In this paper, rather than try to get accurate nonlinear dynamics, the nonlinear and uncertain dynamics are viewed as a signal. It can be estimated by an extended state observer, and compensated by a control law. Accordingly, the nonlinear uncertain system is linearized. Based on the linearized system and the key point of the U-model control, a controller can be designed to obtain predetermined closed-loop system dynamics. To get a more satisfactory performance, a compensation signal of the total disturbance estimation (CSTDE) is designed. Based on the CSTDE, a compensation of the total disturbance estimation based extended state observer (CTDESO) and a fast-response active disturbance rejection control (FRADRC) are proposed. Convergence of the CTDESO and the closed-loop stability of the FRADRC are analyzed. Four nonlinear systems are considered to testify the proposed approaches. Numerical results show that, no matter disturbances exist or not, the proposed CTDESO can linearize a nonlinear system better, and the predetermined closed-loop responses can also be achieved more satisfactorily by the FRADRC. [ABSTRACT FROM AUTHOR]

Low frequency noise control is difficult due to the large wavelength. Acoustic metamaterials (AMs) bring a new sight for low frequency noise control because they can control low frequency wave with subwavelength structures. Since plate type structures are widely used in engineering, the plate type AM structures with different types of resonators are studied by both experiments and numeric simulations. The measured sound transmission loss (STL) curves of the samples show that there are several peak points appearing in the low frequency range. It is found from the numerical simulations that sound wave cannot transmit the plate at these points. The certain locally resonant modes of the resonators lead to good sound insulation properties of the plate type structures. By combing different types of resonators together, enhancement of STL in wide frequency ranges can be achieved. The results in this paper provide good guidance for noise control in engineering applications. [ABSTRACT FROM AUTHOR]

Gas lift is one of the most common artificial lift methods used to enhance oil well production. Oscillations in production flow rate, known as casing heading instability, are a common issue in gas lift systems. Designing an automatic control system is a recommended solution to prevent casing heading and improve the performance of a gas lift system. One of the major challenges in designing such a control system is the uncertainty of the system parameters and state variables. In this paper, the analytical gas lift model presented in previous studies was modified to account for the real gas flow in the annulus. Then, a parameter estimator and a state observer were designed using a square root Kalman filter to estimate the uncertain parameter and state variables. The simulation results have shown that the improved model is more reliable. The designed Linear Quadratic Gaussian (LQG) control, along with the estimator and observer, can stabilize the gas lift system under uncertain conditions. The main contribution of this work is the development of an integrated system for controlling and estimating the gas lift system. This system ensures reliable performance even in the presence of changes in wellbore and reservoir conditions. [ABSTRACT FROM AUTHOR]

A major occupational health risk in the agricultural industry is Hand Arm Vibration Syndrome (HAVS), which is brought on by exposure to vibration from handled machinery. This review thoroughly covers the historical background and prevalence of HAVS in agriculture, highlighting the harm it does to the health and productivity of workers. The goal is to solve the research deficit in this area by concentrating on vibration isolation and dampening approaches. The paper comprehensively examines measurement methods, such as accelerometer-based approaches, strain gauge and force plate methods, wireless sensor networks, for evaluating vibrations related to HAVS. These methods are compared in order to clarify their advantages and disadvantages. Furthermore, engineering controls, isolation mounts, dampers, and smart technologies are included in the categories of shock and vibration reduction solutions based on their efficiency and application. Also covered are human factors that affect vibration reduction. The difficulties in putting reduction strategies into practice are underlined. These difficulties include economic considerations, technological limitations, and user approval. In order to draw useful conclusions, case studies demonstrating effective vibration reduction methods in agricultural contexts are provided. Future directions for reducing HAVS in agriculture include interdisciplinary research opportunities, developing technologies for vibration reduction, and a global approach. This review concludes by highlighting the importance of tackling HAVS, providing insights into real-world applications, and suggesting future research initiatives. [ABSTRACT FROM AUTHOR]

A damaged stator vane can disrupt the circumferential symmetry of the design flow for turbine assemblies, which can lead to a low-engine-order (LEO) forced response of rotor blades. To help engineers be able to better address sudden vane damage failures, this paper conducts a mechanism analysis of the LEO forced response of rotor blades induced by a single damaged vane using an in-house computational fluid dynamic code (Hybrid Grid Aeroelasticity Environment). Firstly, it is found that the damaged vane introduces a family of LEO aerodynamic excitations with high amplitudes by full-annulus unsteady aeroelastic simulations of a single-stage turbine. In particular, the LEO forced response of the rotor blades excited by 3EO is 2.01 times higher than the resonance response excited by vane passing frequency, and the LEO resonance risk of the rotor blades is greatly increased. Then, by analyzing the flow characteristics of the wake and potential field of the stator row with a damaged vane, the localized high transient pressure in the notch cavity and the radial redistribution of the secondary vortex at the stator exit are the main sources of the low-order harmonic components in the flow field. Importantly, the interaction mechanisms in two regions with high LEO excitation amplitude on the rotor blade surface are revealed separately. Finally, an evaluation and comparison of a single damaged vane in terms of aerodynamic performance and LEO forced response was carried out. The results of this paper provide a good theoretical basis for engineers to effectively control the resonance response of rotor blades caused by a damaged stator vane in turbine design. [ABSTRACT FROM AUTHOR]

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 paper examines the specificity of the modern intelligent control systems. The Big Data technology and Data Science algorithms open up great potential in train traffic management based on hazard prevention. An example is given of high reliability and acceptable accuracy of hazardous railway infrastructure failure prediction using methods based on artificial intelligence. A great deal of attention is given to economical methods of ensuring the required levels of functional safety of train control systems. For that purpose, the efficiency of the digital twin-based method was evaluated. It is shown that, under certain conditions, this method allows significantly reducing the cost of a control system while achieving an acceptably high level of functional safety. The method of virtual second channels is based on the same principle of using information redundancy rather than hardware redundancy. The paper presents and analyses the method of virtual second channels in respect to an axle counter-based train control system. It is established that it is possible to ensure a safety integrity level of an entire control system with a virtual second channel at least as high as SIL3. The above methods ensure, on the one hand, a reduction of the amount of equipment and significantly lower cost of the systems and, on the other hand, requires the creation of additional software and substantiation of the acceptability of the achieved level of functional safety. This matter is within the competence of the developer of the control system. [ABSTRACT FROM AUTHOR]

Automation of berthing maneuvers in shipping is a pressing issue as the berthing maneuver is one of the most stressful tasks seafarers undertake. Berthing control problems are often tackled by tracking a predefined trajectory or path. Maintaining a tracking error of zero under an uncertain environment is impossible; the tracking controller is nonetheless required to bring vessels close to desired berths. The tracking controller must prioritize the avoidance of tracking errors that may cause collisions with obstacles. This paper proposes a training method based on reinforcement learning for a trajectory tracking controller that reduces the probability of collisions with static obstacles. Via numerical simulations, we show that the proposed method reduces the probability of collisions during berthing maneuvers. Furthermore, this paper shows the tracking performance in a model experiment. [ABSTRACT FROM AUTHOR]

One of the main tenets of Gricean pragmatics is the distinction between what is said and what is implicated; that is, between truth-conditional and non-truth-conditional meaning. The main contribution of post-Gricean pragmatics was a new definition of what is said as a pragmatic and truth-conditional meaning (Carston, 2002; Recanati, 2010; Moeschler, 2018a). However, implicated meaning (mainly conversational implicature) is still defined as non-truth-conditional because it is cancellable without contradiction. The main consequence is that a speaker can deny having intended her implicature, which results in the hearer having no guarantee of the truthfulness of his inference. This paper explores the relationship between truth and pragmatic implicated meaning and posits that the assessment of a truth value of an inference is a crucial step in the comprehension process. To demonstrate this hypothesis, the paper develops a relevance-based approach to inference, which is coupled with Kahneman's dual cognitive system. I argue that the triggering of an inference is an intuitive and automatic process controlled by System 1, whereas its assessment as a true or false assumption is controlled by System 2. In other words, System 2 is responsible for what is defined in relevance theory as epistemic vigilance. • Explaining the dissociation of the inferential process from the assignment of a truth value to the inferred conclusion. • Assigning the inferential task to Kahneman's System 1, and the task of determining truth value to his System 2. • Fake news is assigned the truth value 'true' because it is compatible with the common ground. • The detection of fake news requires the intervention of System 2, which compares the proposition with the common ground. • Debunking fake news is only possible if an alternative common ground is accessible to the audience. [ABSTRACT FROM AUTHOR]

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]

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]

Many practical dynamic models always suffer from complex nonlinearities, parameter uncertainties and random noises. Such kind of models are always characterized by uncertain stochastic nonlinear systems. Besides, many factors will lead to dead‐zone actuator, which further adds more challenges to control engineering. This paper studies stabilization issue of stochastic systems with polynomial nonlinear conditions, unknown parameters and dead‐zone actuator. An adaptive control approach is proposed by exploring homogeneous domination control and using dynamic‐gain‐based adaptive design strategy. It shows that all the signals are bounded almost surely and the system states converge to the origin almost surely. The presented method is successfully applied to the mass spring mechanical system. [ABSTRACT FROM AUTHOR]

The continuous downward movement exhibited by the Lashagou landslide group in recent years poses a significant threat to the safety of both vehicles and pedestrians traversing the highway G310. By integrating geomorphological interpretation using multi-temporal optical images, interferometric synthetic aperture radar (InSAR) measurements, and continuous global navigation satellite system (GNSS) observations, this paper traced the formation period of the Lashagou landslide group, and explored its kinematic behavior under external drivers such as rainfall and snowmelt. The results indicate that the formation period can be specifically categorized into three periods: before, during, and after the construction of highway G310. The construction of highway G310 is the direct cause and prerequisite for the formation of the Lashagou landslide group, whereas summer precipitation and spring snowmelt are the external driving factors contributing to its continuous downward movement. Additionally, both the long-term seasonal downslope movement and transient acceleration events are strongly controlled by rainfall, and there is a time lag of approximately 1–2 days between the transient acceleration and heavy rainfall events. This study highlights the benefits of leveraging multi-source remote sensing data to investigate slow-moving landslides, which is advantageous for the implementation of effective control and engineering intervention to mitigate potential landslide disasters. [ABSTRACT FROM AUTHOR]

This study employs the diffusion process to construct Markov chains for analyzing the common two-inertia systems used in industry. Two-inertia systems are prevalent in commonly used equipment, where the load is influenced by the coupling of external force and the drive shaft, leading to variations in the associated output states. Traditionally, the control of such systems is often guided by empirical rules. This paper examines the equilibrium distribution and convergence rate of the two-inertia system and develops a predictive model for its long-term operation. We explore the qualitative behavior of the load end at discrete time intervals. Our findings are applicable not only in control engineering, but also provide insights for small-scale models incorporating dual-system variables. [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]

Purpose: This paper aims to propose the automatic carrier landing system with the fault-tolerant ability for carrier-based aircraft in the presence of deck motion, external airwake disturbance and actuator fault, which consists of the reference trajectory generation module and flight control module. Design/methodology/approach: The longitudinal and lateral basic controllers are designed based on the optimal preview control (OPC), which can ensure favorable tracking performance and anti-disturbance ability of system. Furthermore, based on the OPC, the robust fault-tolerant preview control scheme is proposed to attenuate the impact of actuator fault on system, which ensures the safe landing of carrier-based aircraft in case of actuator failure. Findings: Both the Lyapunov method and simulations prove that the tracking errors can converge to zero and system states can be asymptotically stable both in normal and fault operations. Originality/value: The fault-tolerant control strategy is introduced into preview control to deal with actuator fault, which combines feedforward control based on future previewable information and feedback control based on current information to improve the system performance. [ABSTRACT FROM AUTHOR]

Tuning a PID controller is a crucial task in control engineering to achieve optimal performance of the system. However, manual tuning of PID parameters can be inaccurate and difficult without extensive experience. One approach to tuning the PID controller is by utilizing heuristic algorithms. These algorithms are based on natural phenomena and can efficiently search for the optimal set of PID parameters. Therefore, utilizing met heuristic algorithms for tuning PID controllers can significantly improve the system's performance and reduce costs associated with manual tuning. In this paper, a new method for tuning parameters of the PID controller of DC motors using a hybrid adaptive PID_GTO predictive model based on the artificial gorilla troop optimizer algorithm (GTO) is proposed. The empirical results are compared based on four types of error indicator functions: integral time squared error (ITSE), integral time absolute error (ITAE), integral absolute error (IAE), and integral squared error (ISE), as well as with other previously published techniques in the literature, such as the Ziegler-Nichols and PSO Optimizer algorithms. The empirical results show that this method outperforms other techniques in improving steady-state error, stability, overshoot, rising time, and settling time of the DC motor. [ABSTRACT FROM AUTHOR]