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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]

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]

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]

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.

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]

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.

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]

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]

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]

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]

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Plate heat exchangers are realized by means of a heat transfer mechanism, in which heat is naturally transferred from the hot substance to the object with a lower temperature according to the laws of thermodynamics. Two liquids of different temperatures flow on the wall, heat transfer on the wall and convection of the liquid on the wall, thus promoting heat transfer between the two liquids. Under the same flow rate and power consumption conditions, its heat transfer coefficient is three times that of shell and tube heat exchangers, which is a key and efficient new equipment for effectively using effective resources and saving and developing new energy. However the heat supply plate heat exchanger has a tiny circulation surface and is easily obstructed. Regular maintenance and cleaning, troubleshooting, and plate replacement all necessitate frequent heat exchanger disassembly and installation. The requirements and challenges in dismantling and assembling the heat exchanger are very high, and manual disassembly is wasteful, making consistent force difficult to achieve. The current methods of disassembly and assembly are inefficient and incorrect. The intelligent mechanization of disassembly and assembly equipment is realized in this paper by driving, clamping, automatic control, distance measurement, sensing, and other systems. The problems of uneven force, low efficiency, and precision in plate heat exchanger disassembly and assembly are solved. Our power disassembly equipment for high efficiency heat transfer plate heat exchangers not only enhances disassembly efficiency and precision, but it also ensures the safe operation of the plate heat exchanger heating system, and the heat transfer efficiency and heat exchange efficiency are improved. Furthermore, it has a wide range of applications in the petroleum, chemical, and other industries. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel method to formally represent elements of control engineering knowledge in a suitable data structure. To this end, we first briefly review existing representation methods (RDF, OWL, Wikidata, ORKG). Based on this, we introduce our own approach: The Python-based imperative representation of knowledge (PyIRK) and its application to formulate the Ontology of Control Systems Engineering (OCSE). One of its main features is the possibility to represent the actual content of definitions and theorems as nodes and edges of a knowledge graph, which is demonstrated by selected theorems from Lyapunov's theory. While the approach is still experimental, the current result already allows the application of methods of automated quality assurance and a SPARQL-based semantic search mechanism. The feature set of the framework is demonstrated by various examples. The paper concludes with a discussion of the limitations and directions for further development. [ABSTRACT FROM AUTHOR]

This paper considers the comparative analysis of the physical and mathematical methods of the optimal operation of aviation objects' automatic control systems, which is an urgent scientific and technical task. The paper also represents the corresponding stability criteria, depending on the operating conditions, and the influence of external factors that allows ensuring the automatic control systems' reliable operation not only in normal circumstances, but also in the presence of probable disagreements. The scientific novelty of the research lies in developing new stability criteria by means of synthesising the influence of different factors and also the ability to ensure optimal functioning of the automatic control systems. Corresponding mathematical and computer models have been developed. The use of these models allows to determine the optimal stability criteria for control systems with parameters of a different physical nature and ensure reliable operation of electromechanical systems for general and special applications based on the current analysis. The research results are illustrated by corresponding mathematical models, engineering calculations and modelling of the optimal control limits depending on the influence of various factors. The simulation results coincide with the theoretical calculations, which indicates the consistency between the microprocessor-based and software of automatic control systems. [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]

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]

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]

In this paper, an optimized Genetic Algorithm (GA) based internal model controller-proportional integral derivative (IMC-PID) controller has been designed for the control variable to output variable transfer function of dc-dc boost converter to mitigate the effect of non-minimum phase (NMP) behavior due to the presence of a right-half plane zero (RHPZ). This RHPZ limits the dynamic performance of the converter and leads to internal instability. The IMC PID is a streamlined counterpart of the standard feedback controller and easily achieves optimal set point and load change performance with a single filter tuning parameter ?. Also, this paper addresses the influences of the model-based controller with model plant mismatch on the closed-loop control. The conventional IMC PID design is realized as an optimization problem with a resilient controller being determined through a genetic algorithm. Computed results suggested that GA-IMC PID coheres to the optimum designs with a fast convergence rate and outperforms conventional IMC PID controllers. [ABSTRACT FROM AUTHOR]

The Inverted Pendulum On a Cart (IPOC) system poses a challenge in control engineering due to its inherent instability, nonlinearity, and underactuation. This addresses the fundamental issues arising from its underactuated nature and introduces an approach that combines Takagi-Sugeno (T-S) fuzzy control with an awareness of real-world constraints to create a control system ensuring both stability and practicality. By aligning theoretical insights with extended considerations, the Linear Matrix Inequality (LMI)-based control design is demonstrated in a comprehensive framework. Theorems are introduced and validated, leading to the derivation of LMI conditions. The simulation results are assessed with accompanying comments to demonstrate the effectiveness of the theorems. Through this integration of T-S fuzzy control with additional considerations, the paper aims to bridge the gap between theory and practical applications, advancing the field of control engineering. [ABSTRACT FROM AUTHOR]

The PID controller's well-established advantages have led to its widespread application in practically all industrial operations. The effectiveness of the controller has a major impact on the overall performance of the system, making tuning an essential part of the system's operation, which made this a hot topic for academics to dig into for some time. This paper provides an overview of both contemporary and old PID tuning methods. Techniques can be categorized into two major groups, namely: Traditional and optimization tuning methods are two examples of tuning techniques. A comparison between some of the different methods has as well as being made available. The primary objective of this paper is to give thorough for PID professional controllers. [ABSTRACT FROM AUTHOR]

Recovering the global accurate complex physics field from limited sensors is critical to the measurement and control of the engineering system. General reconstruction methods for recovering the field, especially the deep learning with more parameters and better representational ability, usually require large amounts of labeled data which is unaffordable in practice. To solve the problem, this paper proposes uncertainty guided ensemble self-training (UGE-ST), using plentiful unlabeled data to improve reconstruction performance and reduce the required labeled data. A novel self-training framework with the ensemble teacher and pre-training student designed to improve the accuracy of the pseudo-label and remedy the impact of noise is first proposed. On the other hand, uncertainty guided learning is proposed to encourage the model to focus on the highly confident regions of pseudo-labels and mitigate the effects of wrong pseudo-labeling in self-training, improving the performance of the reconstruction model. Experiments including the airfoil velocity and pressure field reconstruction and the electronic components' temperature field reconstruction indicate that our UGE-ST can save up to 90% of the data with the same accuracy as supervised learning. [ABSTRACT FROM AUTHOR]

Load forecasting is a research hotspot in academia; in the context of new power systems, the prediction and determination of load reserve capacity is also important. In order to adapt to new forms of power systems, a day-ahead automatic generation control (AGC) reserve capacity demand prediction method based on the Fourier transform and the attention mechanism combined with a bidirectional long and short-term memory neural network model (Attention-BiLSTM) optimized by an improved whale optimization algorithm (IWOA) is proposed. Firstly, based on the response time, Fourier transform is used to refine the distinction between various types of load reserve demand, and the power of the AGC reserve band is calculated using Parseval's theorem to obtain the reserve capacity demand sequence. The maximum mutual information coefficient method is used to explore the relevant influencing factors of the AGC reserve sequence concerning the data characteristics of the AGC reserve sequence. Then, the historical daily AGC reserve demand sequences with relevant features are input into the Attention-BiLSTM prediction model, and the improved whale algorithm is used to automatically find the optimal hyperparameters to obtain better prediction results. Finally, the arithmetic simulation results show that the model proposed in this paper has the best prediction performance with the upper (0.8810) and lower (0.6651) bounds of the coefficient of determination ( R 2 ) higher than the other models, and it has the smallest mean absolute percentage error ( M A P E ) and root mean square error ( R M S E ). [ABSTRACT FROM AUTHOR]

Electrode roll forming involves rolling a battery electrode into a preset thickness using a hydraulic roll gap thickness automatic control system (hydraulic AGC for short). The pump-controlled AGC is a highly nonlinear servo system, which is a combination of mechanical, hydraulic and electronic control disciplines; thus, as a new technology, it still faces many challenges in the field of pole plate rolling. In this paper, electro-hydraulic servo pump-controlled AGC technology is replaced by electro-hydraulic servo valve-controlled AGC technology. With pump-controlled AGC high-precision thickness control as the research objective, the fuzzy control method is selected to deal with complex nonlinear systems based on pump-controlled AGC nonlinear stiffness characteristics and nonlinear transmission characteristics. A characteristic compensation control strategy is proposed. At the same time, considering the load fluctuation caused by the uneven thickness of the electrode plate under the intermittent coating rolling condition of a lithium battery, the fuzzy internal model (IMC) compensation control strategy was proposed to compensate the structural characteristics of the electrode plate rolling. Comparative experiments show that the position control accuracy of the pump-controlled AGC system can be improved significantly by using a fuzzy IMC compensation control strategy. The steady-state accuracy of the slope signal can reach ±0.7 μm, and the position-following accuracy of the sinusoidal signal can reach ±1.8 μm. In addition, this study will assist technological upgrades to lithium battery electrode roll forming and fixed-roll-gap rolling, laying a theoretical foundation for the promotion of pump control technology in the field of electrode rolling. [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]

Similar to many complex systems, the operation process of electric balanced forklifts has characteristics such as time-varying model parameters and nonlinearity. Establishing an accurate mathematical model becomes challenging, making it difficult to apply model-based control methods in engineering practice. Aiming at the longitudinal control system of electric forklifts containing external disturbances, this paper proposes an improved full-format dynamic linearization model-free adaptive PID control (iFFDL-MFA-PID) method. Firstly, the full-format dynamic linearization (FFDL) method is employed to transform the operating system of the electric balanced forklift into a virtual equivalent linear data model. Secondly, the nonlinear residual term and pseudo-gradient (PG) of the data model are estimated using the difference estimation algorithm and the optimal criterion function, respectively. Furthermore, in order to enhance the robustness of the system, the idea of intelligent PID (iPID) is introduced and the principle of equivalent feedback is utilized to derive the iFFDL-MFA-PID control scheme. The design process of this scheme only requires the use of the input and output data of the system, without relying on the mathematical model of the system. Finally, the iFFDL-MFA-PID method proposed in this paper is simulated and tested with the EFG-BC/320 counterbalanced forklift equipped in the Special Equipment Testing Center and compared with the model-free adaptive control method (FFDL-MFAC) and the PID control method. Simulation results show that the speed-tracking error of the electric forklift truck under the action of the iFFDL-MFA-PID algorithm is maintained within ±0.132 m/s throughout the process, achieving higher tracking accuracy and better robustness compared to the MFAC and PID methods. [ABSTRACT FROM AUTHOR]

Rotary inverted pendulum (RIP) is a classical model of control engineering. Paper deals with a PID-adaptive structure which is based on structure of neuron to train Kp, Ki, Kd through operation. In simulation, our adaptive controller is proven to work in larger range than classical PID controller. Through experimental model using STM32F4, we prove vibration of system under adaptive-PID is smaller than under classical PID structure. Then, combination of neuron network (NN) and PID control can be used as simple structure for single-input multi output (SIMO) systems which are similar to RIP. [ABSTRACT FROM AUTHOR]

The occurrence of late spring frosts due to climate change causes great damage to plantation production worldwide. The main objective of the paper is to provide a comprehensive overview of the problem and to outline effective protective measures against late spring frosts. The nature of frost depends on regional, altitudinal, and geographic differences, but they all share a common problem: they remove heat, resulting in the freezing of new plant growth and flowers. Tissue freezing is affected by critical temperatures and the frost type, intensity, and duration. Protection against late spring frosts can be broadly divided into three categories: active, passive, and chemical measures. In the field of agricultural engineering, various techniques have been thoroughly researched, and their effectiveness has been confirmed by research. These include various sprinkler systems, different heating devices, and large-diameter fans. Conclusive findings are being made on the performance of these systems in sub-zero temperatures and their cost-effectiveness. Climate change increases the importance of protecting permanent crops from late spring frosts and requires advances in agricultural technology to meet changing production demands and challenges. [ABSTRACT FROM AUTHOR]

In order to improve the autonomy and intelligence of group animation behavior, this paper proposes a particle swarm optimization algorithm for automatic control of group animation behavior. After the user inputs the group animation behavior construction target, the individual path is planned according to the fixed behavior rules, and the particle swarm optimization algorithm and the improved artificial fish swarm optimization algorithm are used to select the optimal action for the individual in the group animation according to the top-down control process. The experimental results show that after the PSO converges to the global optimal solution, the evolution times of the PSO converge to the global optimal solution again when the surrounding environment changes 10 times. The population diversity of particle swarm optimization algorithm is obviously better than those of the other two algorithms in the process of automatically controlling the movement of individuals to the circle and to the stand in the crowd animation. Compared with the original algorithm AFSA, the improved artificial fish swarm algorithm proposed in this paper is easier to obtain the global optimal value, and the optimization speed is also improved. In conclusion, the example analysis verifies that the algorithm can effectively realize the automatic control of group animation behavior and has high convergence speed and high autonomy. [ABSTRACT FROM AUTHOR]

This paper investigates different actuator sector model implementation alternatives and how they compare to actuator line results. The velocity sampling method, tip/smearing correction, and time step are considered. A good agreement is seen between the line and sector model in the rotor plane and the wake flow. Using the sector model, it was possible to reduce the computational time by 75 % compared to the actuator line model as it is possible to run the simulations with a larger time step without compromising the accuracy considerably. The results suggest that the proposed velocity sampling method produces the closest results to the line model with different tip speed ratios. Moreover, the vortex-based smearing correction applied to the sector model results in the lowest error values, among the considered methods, to correct the radial load distributions. Also, it is seen that reducing the time step compared to the one used for the actuator disc/sector does not provide an advantage considering the increased computational time. [ABSTRACT FROM AUTHOR]

Automatic control of robots with flexible links has been a pivotal subject in control engineering and robotics due to the challenges posed by vibrations during repetitive movements. These vibrations affect the system's performance and accuracy, potentially causing errors, wear, and failures. LQR control is a common technique for vibration control, but determining the optimal weight matrices [Q] and [R] is a complex and crucial task. This paper proposes a methodology based on genetic algorithms to define the [Q] and [R] matrices according to design requirements. MATLAB and Simulink, along with data provided by Quanser, will be used to model and evaluate the performance of the proposed approach. The process will include testing and iterative adjustments to optimize performance. The work aims to improve the control of robots with flexible links, offering a methodology that allows for the design of LQR control under the design requirements of controllers used in classical control through the use of genetic algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a novel numerical model for characterizing the seepage and dissolution coupling effect on the durability of anti-seepage walls of earth-rock dams is proposed. The model considers the influence of hydraulic gradient-driven seepage on the non-equilibrium decomposition of the calcium dissolution in concrete, as well as the effects of seepage dissolution on pore structure, permeability, and diffusivity. The reasonableness of the model is validated by experimental and literature data, which is then applied to analyze the deterioration and failure processes of a concrete cutoff wall of an earth-rock dam in Zhejiang Province, China. On this basis, the seepage dissolution durability control indices of anti-seepage walls are identified. The findings demonstrate that the suggested method accurately explains the calcium leaching process in concrete. Under the seepage and dissolution coupling effect, calcium in the wall continuously decomposes and precipitates, leading to varying degrees of increases in structural performance parameters, which weaken the seepage control performance of the walls and consequently result in an increase in seepage discharge and hydraulic gradient. By proposing the critical hydraulic gradient as a criterion, the service life of the wall is projected to be 42.8 years. Additionally, the upstream hydraulic head, the initial permeability coefficient, and the calcium hydroxide (CH) content are three crucial indices affecting the durability of walls, and these indices should be reasonably controlled during the engineering design, construction, and operational phases. [ABSTRACT FROM AUTHOR]

When launching a heavy-duty vehicle, torque and position control during automatic clutch engagement is critical, and the driver's intention to launch and changes in the vehicle's launching resistance make clutch control more complex. This paper analyses the automatic engagement process of automated mechanical transmission (AMT) clutches and proposes an optimal control of the clutch torque for launching heavy-duty vehicles. Firstly, a fuzzy neural network (FNN)-based vehicle launching states recognition (LSR) system is designed for distinguishing the driver's launching intention and the vehicle's launching equivalent moment of resistance. Secondly, jerk, friction work, and launching reserve power are taken as the performance indexes for clutch torque optimization, the weight coefficients of each performance index are adjusted according to the LSR results, and the optimal clutch torque is solved by using the minimum value principle based on the shooting method. Finally, simulations and tests are conducted to validate the strategy of optimizing clutch torque, and the impact of torque optimization on the position change during the engagement process is analyzed. The results indicate that under different driver's intentions, vehicle masses, and road gradient conditions, the jerk, friction work, and slipping time of heavy vehicles during the launching process are improved by applying the optimization strategy. [ABSTRACT FROM AUTHOR]

Contemporary vehicle fleets include a variety of both manually and automated operated vehicles. A significant shift involves the increasing use of electric powertrains. However, the current electric charging infrastructure predominantly relies on manual processes. There is an opportunity to automate the charging process for these cars, with the intent to enhance convenience, aid people with accessibility needs, to support MW charging where EV cables are heavy, and finally to enable autonomous driving. The charging standards are common but the mechanisms to access the charging ports are not i.e., lids and protectives. This could be a challenge in the automation process given the complexity of the manipulation task at hand. With the increasing variety of electric vehicle models, standardizing charging mechanisms becomes imperative to streamline the charging process and enable broader adoption. In summary, this paper presents a holistic approach to addressing the evolving needs of electric vehicle charging infrastructure, emphasizing the importance of automation in enabling efficient, accessible, and future-ready charging solutions. [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]

This paper presents development and analysis of different control strategies for smart automated system. The dynamic role of an electrical motor and sensor interfacing with wireless module becomes an essential element in a smart agriculture system to monitor various environmental parameters. The various key parameters such as temperature, humidity, air pressure, soil health and solar radiation are widely used to analyze the growth of plants and soil health based on different climate conditions. However, the smart development of an automatic system to measure these vital parameters provides a feasible approach and helps the farmers to monitor their crops productivity. In this paper, a smart sensor based intelligent and automatic control strategies such as fuzzy logic controller and PID (Proportional Integral Derivative) controller is developed to collect the real time environmental parameters and to adapt any environmental conditions by updating their membership functions automatically with the help of sensor outputs. This paper targets to bring the usage of sensor-based intelligent and automatic control methods in the field of an agriculture system which includes automatic solar panel tracking and control, environmental vital parameters measurement, monitoring and implementation of intelligent control methods. The different experiments have been carried out with the support of graphical and microcontroller programming environment. Experimental results provide that the proposed system effectively measure the environmental parameters and provide an accurate transmission of data for continuous monitoring. The advantage of the proposed system is simple, easy to implement and maintain the dynamic environment for plants with respect to any climate conditions. [ABSTRACT FROM AUTHOR]

Real‐time automated drone‐based crack detection can be used for efficient building damage assessment. This paper proposes an automated real‐time crack detection method based on a drone. Using a lightweight classification algorithm, a lightweight segmentation algorithm, a high‐precision segmentation algorithm, and a crack width measurement algorithm, the cracks are classified, roughly segmented, finely segmented, and the maximum width is extracted. A crack information‐assisted drone flight automatic control algorithm for automatic crack detection guides the drone toward the crack position. The effectiveness of the crack detection algorithm and the crack information‐assisted drone flight automatic control algorithm was tested on two different datasets, a two‐story building, and a 16‐m‐high shaking table test building. The results show that crack detection can be finished in real‐time during the flight. Using the proposed method can significantly improve the MIoU of crack edge detection and the accuracy of maximum crack width measurement under the non‐ideal shooting conditions of the actual inspection situation by automatically approaching the vicinity of the crack. [ABSTRACT FROM AUTHOR]

The article briefly describes the importance of furrowing depth stability for seed germination and growth under precision seeding conditions. By analyzing the application status of furrowing depth control technology of the planter globally, the research method, technical characteristics, and development of furrowing depth stability control technology are reviewed from three key aspects, namely, profiling adjustment device, furrowing depth detection technology, and automatic control system. In this paper, (1) two types of profiling adjustments, active and passive, are described based on the difference in the downforce adjustment method; (2) three furrowing depth detection methods are described based on different sensors; (3) and three ways of regulating the furrowing depth system are summarized based on the different ways of evaluating the stability of furrowing depth. In addition, the characteristics and application requirements of global furrow depth control technology are summarized. It is proposed that the future planter should be developed in the direction of automatic navigation, automatic monitoring and evaluation of seeding quality, variable seeding, high-speed seeding, and other intelligent precision seeding techniques. The summary and outlook of this paper aim to promote the overall development of furrowing depth control technology. [ABSTRACT FROM AUTHOR]

This paper analyzes the typical technical problems arising from dumping and tamping collision interferences in the working faces of conventional mechanized solid backfilling mining (SBM). Additionally, the technical and consecutive characteristics of the solid intelligent backfilling (SIB) method, the execution device, and the corresponding process categories of the SIB process are analyzed. A design for an SIB process flow is presented. Critical algorithms, including automatic recognition and optimization planning based on the cost function and laying the algorithm foundation, are proposed to develop a backfilling process control system. A joint simulation test system is built on a MATLAB/Simulink simulation toolkit (MSST) to simulate and test the optimized algorithms. The results show that the optimized algorithm can realize the automatic optimization planning and automatic interference-recognition adjustment of the backfilling process under actual engineering conditions. In conclusion, this paper analyzes typical technical problems in the conventional backfilling process, designs the SIB process flow, and develops key algorithms to achieve the automatic control of the backfilling process. [ABSTRACT FROM AUTHOR]

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In this paper, we prove some common fixed point theorems in S-metric spaces for a pair of weakly compatible self-mappings using control function and give some consequences of the established result. We also furnish some examples to demonstrate the validity of the results. The results presented in this paper generalize, extend and enrich several results in the existing literature. [ABSTRACT FROM AUTHOR]

We built an automatic chamber system to measure greehouse gas (GHG) exchange in forested peatland ecosystems. We aimed to build a system robust enough which would work throughout the year and could measure through a changing snowpackin addition to producing annual GHG fluxes by integrating the measurements without the need of using models. The system worked rather well throughout the year, but it was not service free. Gap filling of data was still necessary. We observed problems in carbon dioxide (CO2) flux estimation during calm summer nights, when a CO2 concentration gradient from soil/moss system to atmosphere builds up. Chambers greatly overestimated the nighttime respiration. This was due to the disturbance caused by the chamber to the soil-moss CO2 gradient and consequent initial pulse of CO2 to the chamber headspace. We tested different flux calculation and measurement methods to solve this problem. The estimated flux was strongly dependent on (1) the type of the fit (linear and polynomial), (2) the starting point of the fit after closing the chamber, (3) the length of the fit, (4) the speed of the fan mixing the air inside the chamber, and (5) atmospheric turbulence (friction velocity, u*). The best fitting method (the most robust, least random variation) was linear fitting with the period of 120-240 s after chamber closure. Furthermore, the fan should be adjusted to spin at minimum speed to avoid the pulse-effect, but it should be kept on to ensure mixing. If nighttime problems cannot be solved, emissions can be estimated using daytime data from opaque chambers. [ABSTRACT FROM AUTHOR]

With the continuous improvement of the reinforcement learning (RL) algorithm, the algorithm has achieved excellent performance in an increasing number of automatic control tasks. However, there are still some challenges when applying the algorithm to realistic automatic assembly. The most significant challenge is that the stability of these model-free RL methods cannot be effectively guaranteed. Stability is the most critical characteristic of a control system, and stability is closely related to reliability and safety. To ensure the stability of the system, we reconstruct the RL algorithm based on the Lyapunov stability theory of the stochastic system proposed in this paper. An actor-critic learning framework based on Lyapunov stability (LSAC) is proposed for automatic assembly. In addition, this paper proposes a median Q-value theory to alleviate the Q-value estimation deviation that restricts the performance of the RL algorithm. To allow RL agents to better complete the automatic assembly task, this paper designs an adaptive impedance control algorithm. This impedance algorithm executes the actions output by the LSAC framework. Finally, a realistic experiment on automatic assembly is carried out to verify the robustness and superiority of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper comprehensively reviews effective control applications using shape memory alloy (SMA) actuators. Among many applications, this paper focuses on the vibration and stiffness control of flexible structures and shape control in the aerospace engineering field. In the vibration control of flexible structures, three different methods are introduced and discussed, including their merits and demerits. In addition, several control strategies, such as neuro-fuzzy controller, are investigated in terms of the implementation associated with the microchip. In the control process, the inherent hysteretic behavior of SMA is also reviewed as a feedforward loop or actuating force compensator. At the second part, applications on the morphing wing in the field of aerospace engineering are reviewed, and salient characteristics are discussed. In this review, the morphing wing, which is closely related to aircraft stability, is mainly investigated considering control logics and geometrical parameters. For easily understanding morphing control using SMA, a table which summarizes the main contribution of each research is presented. It is expected, since this review article provides numerous approaches for vibration and morphing control conducted over the last decade, it will be very helpful to the same research community to create novel ideas to achieve more advanced and effective results in vibration and morphing control using SMA actuators. [ABSTRACT FROM AUTHOR]

Critical (software) systems are all around us. These systems are typically characterised by stringent dependability requirements and demand elevated levels of robustness and fault tolerance. To assure that they function as intended and provide a number of quality guarantees, formal methods and automated verification techniques and tools have been in use in the engineering of such critical systems for many years now. In this introduction to the special issue FMICS-AVoCS on “Formal Methods and Automated Verification of Critical Systems”, we outline a number of recent achievements concerning the use of formal methods and automated verification techniques and tools for the specification and analysis of critical systems from a variety of application domains. These achievements are represented by six selected papers: five were selected from the joint 21st International Workshop on Formal Methods for Industrial Critical Systems and 16th International Workshop on Automated Verification of Critical Systems (FMICS-AVoCS 2016), while one of them was selected after an open call for papers. [ABSTRACT FROM AUTHOR]

In this paper, the initiation of the fracture of a segment caused by the pressure of the jack and other factors during shield construction is discussed. Based on the Rots model in the finite element software Diana 10.4, the fracture width is solved. Combined with in situ measurements, the mechanisms of concrete fracturing of a segment under external loads, such as the jack thrust deflection angle and uneven jack thrust caused by the changes in the segment due to the upward buoyancy and shield attitude, are studied; additionally, the occurrence conditions and engineering control measures for segment fracture are summarized. The results show that when the attitudes of the shield and segment are identical, the total thrust of the shield is recommended not to exceed 21,000 kN, and is strictly limited to 24,000 kN. When the attitude inclination angle between the shield machine and the segment is less than 1°, the impact on the segment quality is small. When the inclination angle reaches 2°, the total thrust of the shield is recommended not to exceed 16,000 kN, and is strictly limited to 18,000 kN. When the inclination reaches 3°, a fracture is easily produced. When the total thrust is 19,000 kN, it is recommended that the loading increase or decrease in the left and right four grippers should not exceed 20%, and they are prohibited to exceed 30%. The fracture width increases exponentially with the increase in misalignment between adjacent segment rings. These research results provide a theoretical basis for jack pressure control during shield construction. [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 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]