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In automated manufacturing systems (AMSs), because of unpredictable failures, resources can lose functions such that the deadlock control methods, in existence, are invalidated. In this paper, a robust deadlock control approach is proposed for AMSs with multiple unreliable resources. The considered AMSs modelled by Petri nets (PNs) allow to acquire different types of resources at each processing stage. In order to visualise the fact that resource failures occur in AMSs, recovery subnets are designed for the modelling AMSs to depict the failures and recoveries of resources. Based on a siphon detection method performed by a set of integer linear programming formulations, a control specification is proposed. Control places (monitors) with their control variables are designed for the detected unmarked siphons at a marking to guarantee that they are always marked even if some unreliable resources break down. Iteratively, all unmarked siphons are detected and controlled. Therefore, a robust deadlock supervisor is synthesised to ensure the controlled system's liveness no matter there exist resource failures or not. The theoretical analyses and proof are given to verify the correctness of the proposed method. Finally, the comparative studies are presented to expound the proposed method's effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

The enhanced model reference adaptive control (EMRAC) algorithm is an effective full‐state adaptive solution to control plants affected by nonlinear unmodelled dynamics and persistent disturbances. The EMRAC strategy improves the tracking performance by equipping the MRAC algorithm with adaptive switching and adaptive integral control actions. However, the need for the plant state prevents the applicability of the EMRAC algorithm to engineering control problems where only the plant output is measurable. To cover this gap and extend the range of plants controllable by EMRAC solutions, this article presents an output‐based EMRAC algorithm leveraging the closed‐loop (CL) MRAC formulation. The robustness of the closed‐loop control system is analytically analysed, not only with respect to plant parameter uncertainties and square measurable disturbances, but also to ℒ∞$$ {\mathcal{L}}_{\infty } $$ unmodelled terms and disturbances. The ultimate boundedness of the closed‐loop control system is assessed with respect to ℒ∞$$ {\mathcal{L}}_{\infty } $$ unknown nonlinear terms and disturbances, by using Lyapunov theory for Filippov systems, as the adaptive switching control action makes the closed‐loop system discontinuous. To assess the effectiveness of the CL‐EMRAC strategy to impose reference trajectories despite the unmodelled plant dynamics and persistent bounded disturbances, the problem of vehicles' direct yaw moment control is used as an engineering case study. The closed‐loop tracking performance is also quantitatively evaluated through a set of key performance indicators and compared to those provided by four benchmark controllers, that is, two LQ‐based strategies and two MRAC‐based control solutions. The CL‐EMRAC and benchmark controllers are implemented and tested in a co‐simulation environment based on a high‐fidelity IPG CarMaker vehicle model. [ABSTRACT FROM AUTHOR]

The notion of stability margin (SM) plays an important role in control engineering. For multiple‐input multiple‐output (MIMO) systems, the classic SM is no longer applicable. The one‐loop‐at‐a‐time analysis method may lead to unreliable SMs. Although some robust SM analysis methods are popular in MIMO systems, they are model‐based or not easy‐to‐use in engineering sometimes. In this paper, ℒ2$$ {\mathcal{L}}_2 $$ gain margin and ℒ2$$ {\mathcal{L}}_2 $$ time‐delay margin are defined for linear MIMO systems, and a corresponding SM analysis method is proposed by utilizing a loop transformation and the small‐gain theorem. Most importantly, a data‐driven method for measuring the defined SMs is also presented. As a frequency‐domain method, this method can be used to experimentally obtain the SMs of MIMO systems on model‐free occasions. The proposed SM analysis method and measurement method are simple and practical. Two simulation studies and an experimental test are performed to illustrate the effectiveness and practicability of the proposed method. [ABSTRACT FROM AUTHOR]

Lightweight, high-strength, conductive carbon nanocomposites are widely used in axial moving systems, and the primary parametric resonance and primary resonance due to variable axial velocity and tension are quite disturbing when they work in complex electromagnetic environments. In this paper, a theoretical model for predicting Young's modulus and electrical conductivity of graphene nanocomposites is developed by combining equivalent medium theory, shear-leg theory, and Mori–Tanaka theory. The magnetoelastic vibration equations of axially moving graphene nanocomposite current-carrying beam with variable speed and axial force are then derived and solved analytically and numerically. The amplitude-frequency response equations are derived to describe the parametric resonance of the nanocomposite beam with different graphene volume concentrations. The coupled effect of graphene fillers, electric–magnetic field, and external citation on the system's primary parametric resonance are deeply investigated. The results showed that the concentration of graphene filler could significantly affect the amplitude response of the system by controlling Young's modulus and electrical conductivity of the nanocomposite. It can provide a theoretical basis for structure design and vibration control in engineering applications. [ABSTRACT FROM AUTHOR]

The precise measurements of the magnetic field are essential for particle accelerators, and the harmonic coil measurement system is especially suitable for the multipole field because of its unique advantages. The accurate placement of magnets is essential for accurate magnetic field measurements. The current positioning technique employed for harmonic coil measurement is inefficient due to its labor-intensive and time-consuming nature. The aim of this study is to automate the positioning of the quadrupole magnet. Therefore, a close-range photogrammetry system is utilized to monitor the position of the magnet due to its non-contact feature, and an electrically driven Stewart platform is utilized to manipulate the magnet. Meanwhile, a control system has been developed to regulate the automatic positioning. The system is capable of receiving measurements from the close-range photogrammetry system in order to ascertain the displacements of the magnet from its current position to the target. Subsequently, it can transmit commands to Stewart platform to regulate its movement. The experiments indicate that the efficiency of the quadrupole magnet positioning has increased significantly by at least 5 times, and the final positioning accuracy was verified by the laser tracker. The study also addresses the potential application of this technology in high radiation environments that are otherwise inaccessible. [ABSTRACT FROM AUTHOR]

Optimal control of multivariable systems is a complex dynamic process that minimizes the cost function to obtain the optimal control strategy. Unfortunately, for nonlinear systems, it is not possible to use the traditional linear quadratic regulator (LQR), which would be optimal over the entire range of parameter variation. The problem of nonlinear multivariable systems and their optimal control is very momentous. The solution presented in this paper is based on the application of Reinforcement Learning (RL) networks in controlling a five-degree-of-freedom overhead crane system. Additionally, unlike the classical approach, the algorithm is adapted to directly analyze tabular data of inputs and outputs of the controlled model instead of analyzing its state as feedback (model-free). Implementing the new control structure for the multivariable system improved control quality compared to the classical LQR controller with linearization at the operating point. In addition to quality, the resource indicators, which in the LQR controller are represented by the matrix R, have been significantly improved. The architecture of the neural control system is presented, ensuring that over the entire range of nonlinearity, the quality of control is preserved while reducing the cost of its resource intensity. Obtaining optimal control with reduced resources for its implementation induces a wide range of applications of such neural control in engineering systems. The effectiveness of the proposed control system has been demonstrated in simulation studies. The simulation results present the system's excellent control performance and adaptability over the entire range of object nonlinearity. The neural algorithm resulted in significantly shorter adjustment time and better control quality with significantly less system resource consumption and increased system dynamics. [ABSTRACT FROM AUTHOR]

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Advances in artificial intelligence (AI) have led to its application in many areas of everyday life. In the context of control engineering, reinforcement learning (RL) represents a particularly promising approach as it is centred around the idea of allowing an agent to freely interact with its environment to find an optimal strategy. One of the challenges professionals face when training and deploying RL agents is that the latter often have to run on dedicated embedded devices. This could be to integrate them into an existing toolchain or to satisfy certain performance criteria like real-time constraints. Conventional RL libraries, however, cannot be easily utilised in conjunction with that kind of hardware. In this paper, we present a framework named LExCI, the Learning and Experiencing Cycle Interface, which bridges this gap and provides end-users with a free and open-source tool for training agents on embedded systems using the open-source library RLlib. Its operability is demonstrated with two state-of-the-art RL-algorithms and a rapid control prototyping system. [ABSTRACT FROM AUTHOR]

In order to solve the problem of recognizing multiple product images, the author proposes the research of image recognition technology based on deep learning in automated control systems. Firstly, the FasterRCNN method is improved by proposing a non class specific FasterRCNN, which can be used for pre annotation of product images by training only on publicly available datasets. Due to the use of position correction networks, the pre annotation effect is more accurate than that of candidate region networks. Then, combining Grabcut with non class specific FasterRCNN, a sample enhancement method was proposed to synthesize a large number of training images containing multiple products and use them for model training. In addition, based on non class specific FasterRCNN, a re identification layer was proposed to improve detection accuracy. In the end, the recognition and positioning of multiple products achieved a recall rate of 93.8% and an accuracy of 96.3%. [ABSTRACT FROM AUTHOR]

With the rapid development and gradual popularization of Internet of Things technology, it is necessary to provide necessary Operation and Maintenance (O&M) services and data control for electromechanical engineering to maintain the normal function of the power system. This paper does the following research to carry out orderly and standardized management of related communication resources in power communication networks, conduct closed-loop and process-oriented management of communication O&M work, and ensure the safe, stable, and economical operation of power grids in electromechanical engineering. Firstly, the technology selection, algorithm implementation, solutions, and other related technologies that may be used in the platform design and implementation process are introduced and selected. Secondly, the research and call logic of the design and implementation of related algorithms for intelligent O&M are introduced. It includes the design and implementation of anomaly detection algorithms to monitor equipment health status and the design and construction of fault diagnosis algorithms for abnormal analysis. Finally, the simulation experiment of the proposed processing scheme is carried out on the Mininet simulation network to prove that the proposed scheme can provide a better anonymization effect when introducing low latency. The results show that the design of the gateway system realizes the module applications of the system, such as user, data storage, O&M, and fault management. Based on the technical selection, the algorithm is implemented and optimized, and the call logic of the algorithm is implemented in the O&M module. Simulation verifies that the anonymization algorithm can complete the mapping without introducing an additional delay of more than 3%. [ABSTRACT FROM AUTHOR]

Pediatric head computed tomography (CT) scans necessitate precise determination of radiation dose to optimize image quality while minimizing patient exposure. This study explores the influence of head size variation on radiation dose and image quality using phantom and patients set, aiming to investigate the efficacy of Automatic Exposure Control (AEC) in dose modulation. Image noise and radiation dose were assessed using with and without AEC, maintaining a constant tube current of 180 mA. The correlation between CT dose index volume (CTDIvol) and water-equivalent diameter (Dw) was examined across 134 image sets, revealing an exponential relationship indicative of AEC's contribution to elevated radiation exposure in larger heads. Furthermore, a slice-based analysis demonstrated a consistent variation in tube current along the slice location, effectively modulated by Dw. However, discrepancies in tube current were observed in the caudal region, suggesting the influence of factors beyond section size. Refinement of analysis improved curve fitting, highlighting the importance of section size in dose modulation. AEC proved essential in maintaining image quality consistency across slices, with inactive AEC resulting in lower image noise in cranial slices. These findings highlight the significance of AEC-based dose modulation in pediatric head CT to ensure optimal image quality while minimizing radiation exposure, emphasizing the need for comprehensive understanding and implementation of AEC systems from different manufacturers. [ABSTRACT FROM AUTHOR]

Remote control engineering in industry usually requires cameras to assist target identification and detection, but the cameras working in nuclear environments face the threat of radiation-induced degradation. Both γ- and X-rays in nuclear environments will cause ionizing radiation damage, but the difference in degradation of camera’s performance induced by ionizing radiation damage with equivalent total ionizing dose (TID) of these two rays is unclear, which is crucial for the evaluation of camera performance in a nuclear radiation environment. In order to figure out the degradation of CMOS cameras by ionization radiation damage under different rays, this study conducted irradiation experiments on CMOS image sensors under X-ray with 10 keV and 60Co-γ ray with 1.25 MeV, respectively, and then tested and calculated the resolution of camera based on this CMOS image sensor. After comparing and analyzing the results, it was found that the dark current and full well capacity of the CIS, as well as the resolution of the camera, were more severely degraded after X-ray irradiation. Further analysis found that the interface dose enhancement effect of X-ray, as well as the generation of high-density oxide trapped charges in the gate oxide, aggravated the degradation of full well capacity on the CIS after X-ray irradiation, resulting in more severe degradation in the resolution of the CMOS camera. This study provides theoretical basis for the safety and reliability evaluation of cameras in strong nuclear radiation environments. [ABSTRACT FROM AUTHOR]

AbstractPetrol vapors as important occupational and environmental pollutants can cause oxidative stress and may play a role in the development of neurodegenerative diseases along with the risk factors involved. This research is designed as a preliminary study to evaluate the protective effects of apigenin (APG) on oxidative stress caused by petrol vapors inhalation in rats. A total of 24 male Wistar rats were randomly divided into four groups inside the inhalation chamber. Body weight changes and oxidative stress markers were investigated. The average body weight of the group exposed to petrol vapors was significantly lower compared to the other groups. The level of reactive oxygen species (ROS), content of oxidized-glutathione (GSSG), and Malondialdehyde were found to be higher in the petrol-inhaled group, while the content of reduced-glutathione (GSH) was lower compared to the other groups. APG administration did result in any significant improvement in these toxicities induced by petrol vapor. APG administration may ameliorate the petrol-induced oxidative stress. In chronic exposures, in addition to personal protection and engineering control, the use of compounds of natural origin may help in reducing the side effects (such as CNS) caused by exposure to petrol vapors. [ABSTRACT FROM AUTHOR]

A modified onboard neuro-fuzzy adaptive (NFA) helicopter turboshaft engine (HTE) automatic control system (ACS) is proposed, which is based on a circuit consisting of a research object, a regulator, an emulator, a compensator, and an observer unit. In this scheme, it is proposed to use the proposed AFNN six-layer hybrid neuro-fuzzy network (NFN) with Sugeno fuzzy inference and a Gaussian membership function for fuzzy variables, which makes it possible to reduce the HTE fuel consumption parameter transient process regulation time by 15.0 times compared with the use of a traditional system automatic control (clear control), 17.5 times compared with the use of a fuzzy ACS (fuzzy control), and 11.25 times compared with the use of a neuro-fuzzy reconfigured ACS based on an ANFIS five-layer hybrid NFN. By applying the Lyapunov method as a criterion, its system stability is proven at any time, with the exception of the initial time, since at the initial time the system is in an equilibrium state. The use of the six-layer ANFF NFN made it possible to reduce the I and II types of error in the HTE fuel consumption controlling task by 1.36...2.06 times compared with the five-layer ANFIS NFN. This work also proposes an AFNN six-layer hybrid NFN training algorithm, which, due to adaptive elements, allows one to change its parameters and settings in real time based on changing conditions or external influences and, as a result, achieve an accuracy of up to 99.98% in the HTE fuel consumption controlling task and reduce losses to 0.2%. [ABSTRACT FROM AUTHOR]

The work is devoted to the helicopter turboshaft engines' gas generator rotor R.P.M. neuro-fuzzy controller development, which improves control accuracy and increases the system's stability to external disturbances and adaptability to changing operating conditions. Methods have been developed, including improvements to the automatic control system structural diagram which made it possible to obtain the system transfer function in the bandpass filter transfer function form. The work also improved the fuzzy rules base and the neuron activation function mathematical model, which significantly accelerated the neuro-fuzzy controller training process. The transfer function frequency and time characteristics analysis showed that the system effectively controlled the engine and reduced vibration. Methods for ensuring a guaranteed stability margin and the synthesis of an adaptive filter were studied, which made it possible to achieve the system's high stability and reliability. The results showed that the developed controller provided high stability with amplitude and phase margins, effectively compensating for changes in external conditions. Experimental studies have demonstrated that the control quality improved by 2.31–2.42 times compared to previous neuro-fuzzy controllers and by 5.13–5.65 times compared to classic PID controllers. Control errors were reduced by 1.84–2.0 times and 5.28–5.97 times, respectively, confirming the developed neuro-fuzzy controller's high efficiency and adaptability. [ABSTRACT FROM AUTHOR]

Compensatory changes in brain connectivity keep motor symptoms mild in prodromal Parkinson's disease. Studying compensation in patients is hampered by the steady progression of the disease and a lack of individual baseline controls. Furthermore, combining fMRI with walking is intricate. We therefore used a seed-based metabolic connectivity analysis based on 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) uptake in a unilateral 6-OHDA rat model. At baseline and in the chronic phase 6–7 months after lesion, rats received an intraperitoneal injection of [18F]FDG and spent 50 min walking on a horizontal treadmill, followed by a brain PET-scan under anesthesia. High activity was found in the cerebellar anterior vermis in both conditions. At baseline, the anterior vermis showed hardly any stable connections to the rest of the brain. The (future) ipsilesional cerebellar hemisphere was not particularly active during walking but was extensively connected to many brain areas. After unilateral dopamine depletion, rats still walked normally without obvious impairments. The ipsilesional cerebellar hemisphere increased its activity, but narrowed its connections down to the vestibulocerebellum, probably aiding lateral stability. The anterior vermis established a network involving the motor cortex, hippocampus and thalamus. Adding those regions to the vermis network of (previously) automatic control of locomotion suggests that after unilateral dopamine depletion considerable conscious and cognitive effort has to be provided to achieve stable walking. [ABSTRACT FROM AUTHOR]

In recent years, quadcopter-type unmanned aerial vehicles have been preferred in many engineering applications. Because of its nonlinear dynamic model that makes it hard to create optimal control, quadcopter control is one of the main focuses of control engineering and has been studied by many researchers. A quadcopter has six degrees of freedom movement capability and multi-input multi-output structure in its dynamic model. The full nonlinear model of the quadcopter is derived using the results of the experimental studies in the literature. In this study, the control of the quadcopter is realized using the symbolic limited optimal discrete controller synthesis (S-DCS) method. The attitude, altitude, and horizontal movement control of the quadcopter are carried out. To validate the success of the SDCS controller, the control of the quadcopter is realized with fractional order proportional-integral-derivative (FOPID) controllers. The parameters of the FOPID controllers are calculated using Fire Hawk Optimizer, Flying Fox Optimization Algorithm, and Puma Optimizer, which are recently developed meta-heuristic (MH) algorithms. The performance of the S-DCS controller is compared with the performance of the optimal FOPID controllers. In the path planning part of this study, the optimal path planning performances of the SDCS method and the MH algorithms are tested and compared. The optimal solution of the traveling salesman problem (TSP) for a single quadcopter and min-max TSP with multiple depots for multi quadcopters are obtained. The methods and the cases that optimize the dynamic behavior and the path planning of the quadcopter are investigated and determined. [ABSTRACT FROM AUTHOR]

Considering Industry 4.0 directions, followed by recent Industry 5.0 principles, interest in integrating legacy systems in industrial manufacturing has emerged. Due to the continuous evolution of the Internet of Things (IoT) and the Industrial Internet of Things (IIoT), as well as the rapid extension of the scope and adoption of broader technologies, such integration has become feasible. Even though newly developed equipment provides easier interoperability, the replacement of legacy systems highly impacts cost and sustainability, which usually extends to the entire production process, the operators and the maintenance team, and sometimes even the robustness of the production process. Ensuring the interoperability of legacy systems is a problematic task, being dependent on technologies and development techniques and specific industrial domain particularities. This paper considers strategies to ensure the interoperability of legacy systems in a building-management system scenario where local structures are approached using both industrial protocols and web-based contexts. The solution is built following the Industry 5.0 pillars (sustainability, human focus, resilience) and conceives the entire data acquisition and supervisory solution to be flexible, open-source, resilient, and under the control of company engineers. The chosen environment for interfacing and supervision is Node-RED, enabling IoT and IIoT tools, together with a complete orientation toward digital transformation. This way, it is possible to construct a final result that enhances security while bridging outdated protocols and technologies, eliminating compatibility risks in the context of the evolutionary IIoT, ensuring critical process functions are possible, and aiding operators in complying with regulations governing building-management system (BMS) operations, thus solving the challenges that arise in the complex task of adopting the IoT backbone of digital transformation in relation to the integration of legacy equipment. The obtained solution is tested in an automotive industry building-management system, and the results demonstrate its performance, reliability, and high customizability in a context of openness and low cost. [ABSTRACT FROM AUTHOR]

Polarization relaxation loss caused by defects and interfaces has become a fascinating electromagnetic wave (EMW) loss mechanism. However, the logical relationship between impedance matching and various loss mechanisms requires further elucidation to facilitate more comprehensive and in‐depth research. Herein, phase engineering on molybdenum disulfide (MoS2) is proposed as the main controller of permittivity, offering a straightforward and highly effective method for regulating permittivity. Through the main control of phase engineering, a small gradient, monotonic change of the permittivity across a substantial area is achieved, leading to the gradual transition of the material system from strong loss but impedance mismatching to weak loss but EMW transparent phase. Thanks to the fundamental regulation of impedance characteristic and attenuation capacity by the dielectric gene engineering controlled by the phase engineering, combined with the ingenious coordination of sulfur vacancy‐induced polarization and interfacial polarization, t‐60 harvests an effective absorption band of 6.8 GHz and a minimum reflection loss of −59.8 dB. This study effectively expands the dielectric gene pool and improves the research logic for various loss mechanisms, offering valuable insights for the development of advanced EMW absorbing materials. [ABSTRACT FROM AUTHOR]

The reliability of thermal regulation systems is crucial for ensuring the stability of condensed-mode gas-phase fluidized bed reactors (FBRs) used in the production of linear low-density polyethylene (LLDPE). However, studies reporting on the practical industrial control engineering of such reactors relying on thermal equilibrium mechanisms are scarce. This study presents a thorough analysis of a hot thermoregulating water (TRW) valve-jamming incident and interprets the related phenomena and parameter changes. The effect of the catalyst activity and variations in the liquid-phase quantities on the TRW valve action are investigated in depth, and a general explanation is provided by analyzing typical distributed control system data trends and proven deductive reasoning. Results indicate that the polymerization stability is maintained by two thermal pathways. The first pathway is related to the latent (condensate)/sensible heat (gas) extraction and polymerization heat of the materials, and the second is associated with the TRW system, specifically the cold and hot TRW branches. These pathways exhibited synergistic bidirectional effects. Finally, a series of innovative measures are proposed for internal and external operations to fully prevent and respond to TRW valve malfunctions and maintain overall polymerization stability. This study enhances the dependability of linear low-density polyethylene production through advanced process optimization utilizing the Unipol prototype and offers perspectives on system engineering for polyethylene production processes. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) integrate diverse energy resources using advanced communication technologies and intelligent control strategies. This integration enhances the utilization and efficiency of distributed generation. This paper explores the incorporation of VPPs into load frequency control (LFC) systems. It includes an analysis of VPP-aggregated resources' frequency regulation characteristics and a VPP-inclusive LFC model. Additionally, a decentralized automatic generation control strategy is proposed to distribute power outputs effectively, enabling swift grid frequency adjustments. This study uses MATLAB simulations to demonstrate the benefits and efficacy of VPPs in LFC, underscoring their role in advancing grid management and stability. [ABSTRACT FROM AUTHOR]

A four‐degree‐of‐freedom upper limb exoskeleton rehabilitation robot system with a gravity compensation device is constructed. The objective is to address the rehabilitation training needs of patients with upper limb motor dysfunction. A BP neural network adaptive control method based on particle swarm optimization is proposed. First, the degrees of freedom of the human body are analyzed, and a Lagrange method is employed to construct a dynamic model. Second, a particle swarm optimization back propagation neural network adaptive control algorithm based on particle swarm optimization is presented. Subsequently, the range of motion of the upper limbs is analyzed with reference to muscle anatomy and a three‐dimensional motion capture system. And the robot structure design is analyzed in detail. Finally, simulation experiments were conducted, and the results demonstrated that the proposed method exhibited high effectiveness and accuracy. [ABSTRACT FROM AUTHOR]

Objectives: On September 20, 2019, the Jungong ancient landslide in Lajia Town, Maqin County, Qinghai Province, China suffered a local failure, which led to the interruption of traffic and seriously threatened the safety of local resident's lives and properties. It is urgent to find out the deformation area and deformation law of the ancient landslide, and to provide the support for prevention and control engineering design, monitoring and early warning. Methods: First, using high-resolution satellite images, digital elevation model data and combined with field investigations, the ancient landslide were zoned based on landslide morphological characteristics and signs of deformations; further, Sentinel-1 radar satellite descending data from January 2017 to December 2020 were used to analyze the surface deformation characteristics and deformation patterns of the ancient landslide based on small baseline subset interferometric synthetic aperture radar technology (SBAS-InSAR). Results: Based on the morphological characteristics and deformation signs of the landslide, the ancient landslide was divided into four sub-areas. The SBAS-InSAR results show that the ancient landslide is in a continuous slow creeping state. The strong deformation area of the landslide is mainly located in the road excavation section. Human activities greatly disturb the stability of the ancient landslide. The deformation rate of the strong deformation area of the landslide has a good relationship with rainfall. Conclusions: Although the ancient landslide has been partially treated with anti-slide piles and other projects, the ancient landslide has multi-level sliding surfaces, and the depth of the existing anti-slide piles is not enough. Although the ancient landslide has played a certain role in anti-slide, it has not completely prevented the creep deformation of the land‐ slide. It is suggested that the subsequent treatment projects should use drilling and other exploration techniques to find out the depth of the multi-level sliding surfaces before designing, and installing onsite real-time monitoring and early warning equipment such as crack meters in the strongly deformed areas. Combined with the medium and long-term monitoring of radar satellite InSAR, a point-surface monitoring and early warning system could be realized [ABSTRACT FROM AUTHOR]

The ballast control of a floating dock mainly relies on manual operations, which can be time-consuming and requires skilled workers. This study proposes an automatic ballast control system for floating docks, which improves operational efficiency and safety during the vessel docking process. A numerical model is developed to simulate the dynamic process of the floating dock's operations, which includes a six degrees-of-freedom (6DOF) model, a hydrostatic force model, a hydrodynamic force model, and a hydraulic model. The hydrostatic force model is developed using the Archimedes law and a strip theory along the longitudinal direction. The hydrodynamic model is made based on the effects of added mass and dynamic damping. The hydraulic model is proposed to deal with the hydraulic calculation of the ballast water system. The present automatic ballast control is designed based on a modified proportional controller (P-controller) to control the valve opening angles when the pitch or roll angles are larger than the corresponding threshold values. Without using controllers, the roll angles of the dock can reach 8.9 deg and 13 deg during the ballasting and de-ballasting operations, respectively. The present modified P-controller with optimized control parameters can stabilize the dock during the de-ballasting operation and keep the maximum pitch and roll angles no larger than 0.016 deg and 0.0783 deg, respectively. During the ballasting operation with the same control parameters, the roll and pitch are below 0.0604 deg and 0.0145 deg, respectively. The present automatic control will be further implemented in the vessel docking cases and can significantly improve the stability of the dock. [ABSTRACT FROM AUTHOR]

Recent research on fractional-order control laws has introduced the fractional calculus concept into the field of control engineering. As described herein, we apply fractional-order linear quadratic regulator (LQR) control to a current-controlled attractive-force-type magnetic levitation system, which is a strongly nonlinear and unstable system, to investigate its control performance through experimentation. First, to design the controller, a current-controlled attractive-force-type magnetic levitation system expressed as an integer-order system is extended to a fractional-order system expressed using fractional-order derivatives. Then, target value tracking control of a levitated object is achieved by adding states, described by the integrals of the deviation between the output and the target value, to the extended system. Next, a fractional-order LQR controller is designed for the extended system. For state-feedback control, such as fractional-order servo LQR control, which requires the information of all states, a fractional-order state observer is configured to estimate fractional-order states. Simulation results demonstrate that fractional-order servo LQR control can achieve equilibrium point stabilization and enable target value tracking. Finally, to verify the fractional-order servo LQR control effectiveness, experiments using the designed fractional-order servo LQR control law are conducted with comparison to a conventional integer-order servo LQR control. [ABSTRACT FROM AUTHOR]

While life-sustaining, hemodialysis is a non-physiological treatment modality that exerts stress on the patient, primarily due to fluid shifts during ultrafiltration. Automated feedback control systems, integrated with sensors that continuously monitor bio-signals such as blood volume, can adjust hemodialysis treatment parameters, e.g., ultrafiltration rate, in real-time. These systems hold promise to mitigate hemodynamic stress, prevent intradialytic hypotension, and improve the removal of water and electrolytes in chronic hemodialysis patients. However, robust evidence supporting their clinical application remains limited. Based on an extensive literature research, we assess feedback-controlled ultrafiltration systems that have emerged over the past three decades in comparison to conventional hemodialysis treatment. We identified 28 clinical studies. Closed loop ultrafiltration control demonstrated effectiveness in 23 of them. No adverse effects of closed loop ultrafiltration control were reported across all trials. Closed loop ultrafiltration control represents an important advancement towards more physiological hemodialysis. Its development is driven by innovations in real-time bio-signals monitoring, advancement in control theory, and artificial intelligence. We expect these innovations will lead to the prevalent adoption of ultrafiltration control in the future, provided its clinical value is substantiated in adequately randomized controlled trials. [ABSTRACT FROM AUTHOR]

In multi‐agent systems (MASs), not only do agents engage in cooperative relationships, but they also compete with one another. The topic of collaborative group in MASs has garnered significant attention. Due to the possibility of explicit interaction among agents, the complete sharing of known information among nodes presents a risk of privacy leakage. Therefore, this article explores the problem of asymmetric bipartite consensus control for MASs with strong‐privacy‐preserving. A novel state decomposition privacy‐preserving algorithm is proposed to achieve asymmetric bipartite consensus of MASs. This algorithm can ensure that the initial and final states of each agent will not be compromised, via a preservation coefficient designed in proposed algorithm. By employing algebraic graph theory and automatic control theory, a thorough analysis of the algorithmic performance is conducted. It is demonstrated that our algorithm can preserve the privacy of all agents in MASs while achieving asymmetric bipartite consensus, i.e. the consensus values are different in sign and modulus. Finally, the effectiveness of the main results is validated through simulation examples. [ABSTRACT FROM AUTHOR]

The elastic wave bandgap (BG) properties of locally resonant phononic crystal (LRPC) make it has great potential in the research and development of damping composite material and the application of vibration control engineering. However, the number of BG of the traditional LRPC is only one, the BG frequency range is too concentrated, and the multi-frequency BGs is not opened, so the application in practical engineering is limited. In response to the above issues, this paper designs a concentric ring cement-based locally resonant phononic crystal (CRCBLRPC) composite material, and studies and analyzes its BG characteristics. Firstly, the improved plane wave expansion method (IPWEM) and finite element method (FEM) are used to calculate the band structure of the CRCBLRPC. Secondly, the transfer function and BG mechanism of CRCBLRPC are calculated using FEM. Then, the factors affecting the BG of CRCBLRPC are analyzed. Finally, an equivalent model of spring-mass system is proposed to theoretically estimate the BG range of CRCBLRPC. The results show that the CRCBLRPC opens multi-frequency and low frequency BGs within the 200 Hz frequency band, and the number of BGs is more than that of the traditional LRPC. Within the BG frequency range, the CRCBLRPC has a good inhibition effect on vibration. Among them, the density of the scatterer and the elastic modulus of the coating layer are the main factors affecting the BG of the CRCBLRPC. The established spring-mass system equivalent model can accurately calculate the BG range of the CRCBLRPC. The research content and related conclusions of this paper provide new perspectives and insights for the study and design of LRPC composite materials with multi-frequency and low frequency BGs, and can also provide new ideas and methods for solving low frequency vibration in practical engineering. [ABSTRACT FROM AUTHOR]

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]

This paper intends to model an AGC regulator for a restructured environment using Bare Bone Particle Swarm Optimization (BBPSO). The gain-controlled Proportional–Integral (PI) Controller is designed here to enhance the performance of the BBPSO algorithm along with Gaussian distribution. The practical difficulty in handling the area control error to zero is the sudden variations in load. In practice, the tremendous contribution of deregulation in the power sector causes volatility in frequency and tie-line power deviations. To ensure the robustness of the proposed controller, three different cases of power system transactions have been considered. The performance has been validated by comparing it with Real Coded Genetic Algorithm-tuned PI controller (RCGA-PI) and Differential Evolutionary Algorithm-tuned PI controller (DE-PI) for the five area Thermal-Thermal generation test system. Moreover, the dynamic performance of an extensive range of demands and disturbances of all areas like settling time and overshoot against parametric precariousness has been done on the proposed test system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Geomechanics is the property of Journal of Geomechanics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Xinjiang region is prone to frequent and complex wind and sand disasters, which present a significant challenge to the sustainable development of local areas. This research uses multi-source data to analyze the spatial distribution of the aeolian environment in Xinjiang, establishes a four-level zoning scheme, and proposes recommendations for ecological management and engineering and control. Results indicate that (1) Xinjiang's aeolian environment and its types exhibit spatial heterogeneity. The aeolian environment types display a high concentration in the eastern region and a low concentration in the western region. Furthermore, the aeolian environment types are concentrated in the basin region. Moreover, the aeolian environment types exhibit a meridional distribution pattern. (2) A four-level zoning system for aeolian environments in Xinjiang was developed, comprising two first-level zones, seven s-level subzones, 22 third-level wind zones, and 31 fourth-level subdivisions. (3) A structural model for a highway sand control system is proposed for aeolian environment types of subdivisions, including fixing-based, combined blocking and fixing, wind-blocking and sand-transferring, and combined blocking and fixing–transferring. The aeolian environment regionalization program proposed in this study can be a scientific reference for relevant departments in formulating and implementing sand prevention and control planning. [ABSTRACT FROM AUTHOR]

Typical wind tunnel testing involves a series of configuration changes (to the angles of control surfaces) to simulate the lift and resistance characteristics of control surfaces in different flight conditions. It is very time-consuming and labor-intensive to manually change the angles of control surfaces, especially in the large continuous reflux wind tunnel. Thus, there is a demand for a morphing system design within the wind tunnel model that can deflect the control surfaces remotely and automatically. The basic design flow and characteristics of different actuator techniques for the morphing systems were summarized in this paper, including electromechanical actuator, pneumatic actuator, shape memory material actuator and piezoelectric actuator. In the case study, the accuracy of the control surface angle and aerodynamic performance of the ultrasonic-driven automatic control surface system reached the level of traditional fixed control surface systems, while its efficiency was much higher than that of the traditional fixed control surface systems. [ABSTRACT FROM AUTHOR]

This paper investigates a carrier landing controller for unmanned aerial vehicles (UAVs), and a nonlinear model predictive control (NMPC) approach is proposed considering a precise motion control required under dynamic landing platform and environment disturbances. The NMPC controller adopts constraint aware particle filtering (CAPF) to predict deck positions for disturbance compensation and to solve the nonlinear optimization problem, based on a model establishment of carrier motion and wind field. CAPF leverages Monte Carlo sampling to optimally estimate control variables for improved optimization, while utilizing constraint barrier functions to keep particles within a feasible domain. The controller considers constraints such as fuel optimization, control saturation, and flight safety to achieve trajectory control. The advanced control method enhances the solution, estimating optimal control sequences of UAV and forecasting deck positions within a moving visual field, with effective trajectory tracing and higher control accuracy than traditional methods, while significantly reducing single-step computation time. The simulation is carried out using UAV "Silver Fox", considering several scenarios of different wind scales compared with traditional CAPF–NMPC and the nlmpc method. The results show that the proposed NMPC approach can effectively reduce control chattering, with a landing error in rough marine environments of around 0.08 m, and demonstrate improvements in trajectory tracking capability, constraint performance and computational efficiency. [ABSTRACT FROM AUTHOR]

Purpose: To develop an inline automatic quality control to achieve consistent diagnostic image quality with subject‐specific scan time, and to demonstrate this method for 2D phase‐contrast flow MRI to reach a predetermined SNR. Methods: We designed a closed‐loop feedback framework between image reconstruction and data acquisition to intermittently check SNR (every 20 s) and automatically stop the acquisition when a target SNR is achieved. A free‐breathing 2D pseudo‐golden‐angle spiral phase‐contrast sequence was modified to listen for image‐quality messages from the reconstructions. Ten healthy volunteers and 1 patient were imaged at 0.55 T. Target SNR was selected based on retrospective analysis of cardiac output error, and performance of the automatic SNR‐driven "stop" was assessed inline. Results: SNR calculation and automated segmentation was feasible within 20 s with inline deployment. The SNR‐driven acquisition time was 2 min 39 s ± 67 s (aorta) and 3 min ± 80 s (main pulmonary artery) with a min/max acquisition time of 1 min 43 s/4 min 52 s (aorta) and 1 min 43 s/5 min 50 s (main pulmonary artery) across 6 healthy volunteers, while ensuring a diagnostic measurement with relative absolute error in quantitative flow measurement lower than 2.1% (aorta) and 6.3% (main pulmonary artery). Conclusion: The inline quality control enables subject‐specific optimized scan times while ensuring consistent diagnostic image quality. The distribution of automated stopping times across the population revealed the value of a subject‐specific scan time. [ABSTRACT FROM AUTHOR]

Copyright of Petroleum Geology & Oilfield Development in Daqing is the property of Editorial Department of Petroleum Geology & Oilfield Development in Daqing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During the operation of combine harvesters, the cutting platform height is typically controlled using manual valve hydraulic systems, which can result in issues such as delays in adjustment and high labor intensity, affecting both the quality and efficiency of the operation. There is an urgent need to enhance the automation level. Conventional methods frequently employ single-point measurements and lack extensive area coverage, which means their results do not fully represent the terrain's variations in the area and are prone to local anomalies. Given the inherently undulating terrain of farmland during harvesting, a control strategy that does not adjust for minor undulations but only for significant ones proves to be more rational. To this end, a sine wave superposition model was established to simulate three-dimensional ground elevation changes, and an area array LiDAR was used to collect 8 × 8 data for the header height. The effects of mounds and stubble on the measurement results were analyzed, and a dynamic process simulation model for the solenoid valve core was developed to analyze the on/off delay characteristics of a three-position four-way electromagnetic directional valve. Moreover, a physical model of the hydraulic system was constructed based on the Simscape module in Simulink, and the Bang Bang switch predictive control system based on position threshold was introduced to achieve early switching of the electromagnetic directional valve circuit. In addition, an automatic control system for cutting platform height was designed based on an STM32 microcontroller. The control system was tested on the hydraulic automatic control test rig developed by Shanxi Agricultural University. The simulation and experimental results demonstrated that the control system and strategy were robust to output disturbances, effectively enhancing the intelligence and environmental adaptability of agricultural machinery operations. [ABSTRACT FROM AUTHOR]

An analysis of cost management within railway construction projects has been conducted using the Analytic Hierarchy Process (AHP) and a regression analysis to evaluate and rank key financial and operational factors affecting project costs. This research assesses the impact of various metrics, such as Safety Inspections, Emergency Preparedness, and Equipment Maintenance, along with financial indicators such as Actual Cost and Variance, on cost control strategies by building a hierarchical model and implementing AHP. The results indicate a clear preference for Financial Metrics, with a priority vector of 0.667, over Operational Metrics, which have a priority vector of 0.334. Among the Financial Metrics, Actual Cost, with a priority vector of 0.565, is identified as the most influential, underscoring the importance of direct cost management. Among the Operational Metrics, Emergency Preparedness is the most important, with a priority vector of 0.540, emphasizing the importance of effective risk management. A regression analysis confirms these priorities, with significant correlations presented between these metrics and variances in costs. According to this study, changes in Emergency Preparedness and Equipment Maintenance can predict cost fluctuations, aligning with the findings of the AHP study. The AHP evaluations are demonstrated to be reliable, with consistency ratios significantly below the 0.1 benchmark (0.043 for Financial Metrics and 0.008 for Operational Metrics), indicating a high degree of consistency in judgment. The statistical validation enhances the framework's effectiveness in steering strategic decisions regarding cost management. This paper discusses the implications of these results to reduce financial risks and improve project outcomes. [ABSTRACT FROM AUTHOR]

Wind power is currently the most mature representative of sustainable energy generation technology, which has been developed and utilized on a large scale worldwide. The random and fluctuating nature of wind power output poses a threat to the secure and stable operation of the system. Consequently, the transmission of wind power has garnered considerable attention as a crucial factor in mitigating the challenges associated with wind power integration. In this paper, an artificial-intelligence-aided frequency coordination control strategy applicable to wind power transmission systems based on hybrid DC transmission technology is proposed. The line commutated converter (LCC) station at the sending end implements the strategy of auxiliary frequency control (AFC) and automatic generation control (AGC) to cooperate with each other in order to assist the system frequency regulation. The AFC controller is designed based on the variable forgetting factor recursive least squares (VFF-RLS) algorithm for system identification. First, the VFF-RLS algorithm is used to identify the open-loop transfer function of the system. Then, the AFC controller is designed based on the root locus method to achieve precise control of the system frequency. The DC line power modulation quantity is introduced in the AGC to automatically track the active power fluctuation and frequency deviation of the system. The AGC utilizes the classical proportional-integral (PI) control. By selecting the integrated time absolute error (ITAE) performance index to construct the reward function, and using a deep Q-network (DQN) for controller parameter optimization, it achieves improved regulation performance for the AGC. The voltage source converter (VSC) station at the receiving end implements an adaptive DC voltage droop control (ADC)strategy. Finally, the effectiveness and robustness of the proposed frequency control strategy are verified through simulation experiments. [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]

In this study, a C-series linear accelerator was configured to enable rapid and reliable conversion between the production of conventional electron beams and an ultrahigh-dose-rate (UHDR) electron beamline to the treatment room isocenter for FLASH radiation therapy. Efforts to tune the beam resulted in a consistent, stable UHDR beamline. The linear accelerator was configured to allow for efficient switching between conventional and modified electron output modes within 2 minutes. Additions to the air system allow for retraction of the x-ray target from the beamline when the 10 MV photon mode is selected. With the carousel set to an empty port, this grants access to the higher current pristine electron beam normally used to produce clinical photon fields. Monitoring signals related to the automatic frequency control system allows for tuning of the waveguide while the machine is in a hold state so a stable beam is produced from the initial pulse. A pulse counting system implemented on an field-programmable gate array-based controller platform controls the delivery to a desired number of pulses. Beam profiles were measured with Gafchromic film. Pulse-by-pulse dosimetry was measured using a custom electrometer designed around the EDGE diode. This method reliably produces a stable UHDR electron beam. Open-field measurements of the 16-cm full-width, half-maximum gaussian beam saw average dose rates of 432 Gy/s at treatment isocenter. Pulse overshoots were limited and ramp up was eliminated. Over the last year, there have been no recorded incidents that resulted in machine downtime due to the UHDR conversions. Stable 10 MeV UHDR beams were generated to produce an average dose rate of 432 Gy/s at the treatment room isocenter. With a reliable pulse-counting beam control system, consistent doses can be delivered for FLASH experiments with the ability to accommodate a wide range of field sizes, source-to-surface distances, and other experimental apparatus that may be relevant for future clinical translation. [ABSTRACT FROM AUTHOR]

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

This study presents an integrated analog front-end (AFE) tailored for photoplethysmography (PPG) sensing. The AFE module introduces a novel transimpedance amplifier (TIA) that incorporates capacitive feedback techniques alongside common drain feedback (CDF) TIA. The unique TIA topology achieves both high gain and high sensitivity while maintaining low power consumption. The resultant PPG sensor module demonstrates impressive specifications, including an input noise current of 4.81 pA/sqrt Hz, a transimpedance gain of 18.43 MΩ, and a power consumption of 68 µW. Furthermore, the sensory system integrates an LED driver featuring automatic light control (ALC), which dynamically adjusts the LED power based on the strength of the received signal. Employing 0.35 µm CMOS technology, the AFE implementation occupies a compact footprint of 1.98 mm × 2.475 mm. [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]

We propose the theoretical design and experimental authentication of an ultrathin sound absorber consisting of a perforated plate and a back cavity with zigzag channels for realizing high-efficiency and broadband absorption of low-frequency sound. The dependence of the absorption performance on the structural parameters is analyzed, which suggests the possibility of decreasing the peak frequency of resonance noise absorption with equal compactness of device. Based on this, we propose a hybrid design composed of multiple structures with different parameters to effectively expand the working bandwidth, and propose to further optimize the low-frequency absorption performance by adjusting the inclined partitions in the zigzag channel. The experimental results show that nearly 100% sound absorption is obtained at the resonance frequency (< 500 Hz) with an absorber 30 times thinner than the wavelength. We envision our designed sound absorber with deep-subwavelength size, broadband functionality, and easy fabrication to find wide applications in noise control engineering. [ABSTRACT FROM AUTHOR]

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