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The proton exchange membrane fuel cell (PEMFC) stack is an excellent source of clean energy for electric vehicles with zero carbon footprint. The abrupt changes in power demand in automotive applications can adversely impact the oxygen excess ratio (OER) and stack voltage. Therefore, this study aims to design an intelligent cascade control framework to ensure the durable and efficient operation of PEMFC. A novel mixed locally recurrent fuzzy neural network proportional-integral-derivative (RFNN-PID) control architecture is proposed. The RFNN-PID and proportional-integral (PI) controllers are employed as the primary and secondary controllers in cascaded loops, respectively. Four other cascaded schemes with fuzzy PID and PI (FPID/PI), two-degree-of-freedom PID & two-degree-of-freedom PI (2DOF-PID/2DOF-PI), fractional order PID & fractional order PI (FOPID/FOPI), and PID/PI controllers are designed for comparison. The controller parameters are optimised using the mayfly algorithm (MA) to minimise the integral time absolute error (ITAE). The findings suggest the cascaded RFNN-PID/PI strategy yields the fastest voltage regulation and minimum ITAE (0.3018 s & 3.406), as compared to cascaded FPID/PI (0.4087 s & 4.273), 2DOF-PID/2DOF-PI (0.4213 s & 6.626), FOPID/FOPI (0.8135 s & 9.083) and PID/PI (1.066 s & 10.89). The proposed controller also exhibits robust performance in the presence of disturbance and noise. Hence, it is concluded that the adaptive RFNN-PID/PI controller efficiently controls the voltage and regulates OER even in adverse operating conditions. [Display omitted] • A novel cascaded control is developed for the regulation of PEMFC. • RFNN-PID and PI are used as primary and secondary controllers, respectively. • The Mayfly algorithm is utilised to estimate the parameters of the controllers. • Detailed analysis with varying load, noise and disturbance is exhibited. [ABSTRACT FROM AUTHOR]

A cascade control structure (CCS) is still the most commonly used control scheme in variable speed control (VSC) electrical drives with alternating current (AC) motors. Several tuning methods are used to select the coefficients of controllers applied in CCS. These approaches can be divided into analytical, empirical, and heuristic ones. Regardless of the tuning method used, there is still a question of whether the CCS is tuned optimally in terms of considered performance indicators to provide high-performance behavior of the electrical drive. Recently, artificial intelligence-based methods, e.g., swarm-based metaheuristic algorithms (SBMAs), have been extensively examined in this field, giving promising results. Moreover, the intensive development of artificial intelligence (AI) assistants based on large language models (LLMs) supporting decision-making processes is observed. Therefore, it is worth examining the ability of LLMs to tune the CCS in the VSC electrical drive. This paper investigates tuning methods for the cascade control structure equipped with PI-type current and angular velocity controllers for PMSM drive. Sets of CCS parameters from electrical engineers with different experiences are compared with reference solutions obtained by using the SBMA approach and LLMs. The novel LLM-based Tuning Assistant (TA) is developed and trained to improve the quality of responses. Obtained results are assessed regarding the drive performance, number of attempts, and time required to accomplish the considered task. A quantitative analysis of LLM-based solutions is also presented. The results indicate that AI-based tuning methods and the properly trained Tuning Assistant can significantly improve the performance of VSC electrical drives, while state-of-the-art LLMs do not guarantee high-performance drive operation. [ABSTRACT FROM AUTHOR]

This paper presents a novel Fuzzy Logic Controller (FLC) framework aimed at enhancing the performance and stability of Automatic Voltage Regulators (AVRs) in power systems. The proposed system combines fuzzy control theory with the Fractional Order Proportional Integral Derivative (FOPID) technique and employs cascading control theory to significantly improve reliability and robustness. The unique control architecture, termed Fuzzy Fractional Order Proportional Integral (PI) plus Fractional Order Proportional Derivative (PD) plus Integral (Fuzzy FOPI+FOPD+I), integrates advanced control methodologies to achieve superior performance. To optimize the controller parameters, the Teaching–Learning-Based Optimization (TLBO) algorithm is utilized in conjunction with the Integral Time Absolute Error (ITAE) objective function, ensuring precise tuning for optimal control behavior. The methodology is validated through comparative analyses with controllers reported in prior studies, highlighting substantial improvements in performance metrics. Key findings demonstrate significant reductions in peak overshoot, peak undershoot, and settling time, emphasizing the proposed controller's effectiveness. Additionally, the robustness of the controller is extensively evaluated under challenging scenarios, including parameter uncertainties and load disturbances. Results confirm its ability to maintain stability and performance across a wide range of conditions, outperforming existing methods. This study presents a notable contribution by introducing an innovative control structure that addresses critical challenges in AVR systems, paving the way for more resilient and efficient power system operations. [ABSTRACT FROM AUTHOR]

Gimbal systems serve as critical mechanisms for carrying payloads and accurately aligning them with specific lines of sight. Designing controllers for these gimbal systems necessitates robustness against external disturbances and variations in system parameters. Various control methods have been explored in existing literature to address this challenge. In the scope of this study, we investigate the performance of four distinct control strategies—Proportional-Integral (PI) control, Self-Tuning PI control, Integral Action LinearQuadratic regulator (IA-LQR), and Relay Sliding Mode Control based on the Input-Output Model (RSMCIO)—as speed controllers for a gimbal system. We assess their efficacy through both simulation-based experiments and real-world applications, offering a comprehensive analysis of their outcomes. Beyond speed control, we extend our investigation to include cascade position control, employing a ProportionalDerivative (PD) control structure in the outer loop. Our study focuses on evaluating the performance of these diverse control structures when subjected to disturbances and variations in model parameters. To the best of our knowledge, this research marks the first attempt to apply the RSMC-IO approach to gimbal systems, enhancing our understanding of control strategies in this context and offering valuable insights into their practical implications. [ABSTRACT FROM AUTHOR]

The hydraulic secondary regulation drive system employs a hydraulic servo motor to achieve precise position tracking and zero throttling loss, but it faces challenges such as high inertia, low damping, and high system order, leading to suboptimal control accuracy. Traditional adaptive robust control methods struggle with the control challenges of such high-order systems. This paper introduces a cascaded control approach based on adaptive robust control to address these issues. A fifth-order model is developed to account for significant load inertia, dividing the system into inner and outer control loops. The outer loop applies adaptive robust control to handle uncertainties and load disturbances for accurate rotational position control, while the inner loop uses swashplate disturbance compensation robust control to manage torque disturbances and achieve precise displacement control. A cascaded Lyapunov function is designed to address the coupling effects between the errors of the inner and outer loop controllers, ensuring stability across both subsystems. Experimental results show that the proposed method's position tracking accuracy exceeds that of cascade dual-PID control methods by 50% to 80% and traditional adaptive robust control methods by 30% to 40% under sinusoidal frequency commands of 0.1 Hz and 0.25 Hz. • Construct a 5th order model of the secondary regulation system , considering the dynamic characteristics. • Propose an ASCRC method to address the parameter explosion in the design of control laws for high-order systems. • Use a single cascade Lyapunov equation to ensure that the stability of all controllers in series still meets the system requirements. [ABSTRACT FROM AUTHOR]

In mountainous regions, forested areas, and other zones prone to natural disasters, power equipment faces heightened risks of shutdown. Such disruptions significantly elevate the risk of secondary cascading failures within the power grid. Consequently, devising cascading failure mitigation strategies from an operational perspective is of paramount importance for containing the spread of cascading failures in the power system during disasters and minimizing the losses incurred from disaster incidents. Firstly, based on the severity of natural disaster accident risks, this paper establishes a risk index for power equipment for the first time, providing a new perspective for the refined analysis of the development model of cascading failures in power systems. Subsequently, a new collaborative mitigation strategy for system cascading failures is proposed at the operational control level. This strategy, in conjunction with proactive prevention and control measures, aims to promptly sever potential cascading failure paths upon the occurrence of a disaster, thereby ensuring that the area of power outage is minimized to the greatest extent possible. The effectiveness of the proposed strategy is verified through simulation cases. The results show that in the scenario set in this article, the risk of cascading failures under natural disasters is nearly five times higher than that without natural disasters. At the same time, the cascading failure control method proposed in this study can reduce the risk of cascading failure by about 80%. [ABSTRACT FROM AUTHOR]

Nested, or cascade speed and torque control has been widely used for DC motors over recent decades. Simultaneously, fractional-order control schemes have emerged, offering additional degrees of control. However, adopting fractional-order controllers, particularly in cascade schemes, does not inherently guarantee better performance. Poorly paired fractional exponents for inner and outer PI controllers can worsen the DC motor's behavior and controllability. Finding appropriate combinations of fractional exponents is therefore crucial to minimize experimental costs and achieve better dynamic response compared to integer-order cascade control. Additionally, mitigating adverse couplings between speed and current loops remains an underexplored area in fractional-order control design. This paper develops a computational model for fractional-order cascade control of DC motor speed (external) and current (internal) loops to derive appropriate combinations of internal and external fractional orders. Key metrics such as overshoot, rise time, and peak current values during speed and torque changes are analyzed, along with coupled variables like speed drop during torque steps and peak torque during speed steps. The proposed maps guide the selection of effective combinations, enabling readers to deduce robust or adaptive designs depending on specific performance needs. The methodology employs Oustaloup's recursive approximation to model fractional-order elements, with MATLAB–SIMULINK simulations validating the proposed criteria. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower 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.)

Fruit ripening is a highly-orchestrated process that requires the fine-tuning and precise control of gene expression, which is mainly governed by phytohormones, epigenetic modifiers, and transcription factors. How these intrinsic regulators coordinately modulate the ripening remains elusive. Here we report the identification and characterization of FvALKBH10B as an N6-methyladenosine (m6A) RNA demethylase necessary for the normal ripening of strawberry (Fragaria vesca) fruit. FvALKBH10B is induced by phytohormone abscisic acid (ABA), and ABA-Responsive Element Binding Factor 3 (FvABF3), a master regulator in ABA signaling, is responsible for this activation. FvALKBH10B mutation leads to a delay in fruit ripening and causes global m6A hypermethylation of 1859 genes. Further analyses show that FvALKBH10B positively modulates the mRNA stability of SEPALLATA3 (FvSEP3) encoding a transcription factor via m6A demethylation. In turn, FvSEP3 targets numerous ripening-related genes including those associated with biosynthesis of ABA and anthocyanin and regulates their expression. Our findings uncover an FvABF3-FvALKBH10B-FvSEP3 cascade in controlling fruit ripening in strawberry and provide insights into the complex regulatory networks involved in this process. Fruit ripening is a complex process controlled by various factors. Here, the authors show that plant hormone ABA activates m6A demethylase FvALKBH10B, which stabilizes mRNA of ripening regulator FvSEP3, thereby modulating strawberry fruit ripening. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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.)

In modern power systems, the integration of inverter‐based renewable energy sources has significantly reduced system inertia, leading to heightened frequency fluctuations and potential instability within multi‐area interconnected microgrids. To counter this, a virtual inertia and damping controller utilizing battery energy storage, leveraging the virtual synchronous generator concept is proposed in this paper. This controller supplements inertia by modulating active power flow, thus stabilizing frequency during high renewable energy source penetration periods. Additionally, to enhance load frequency control, a cascaded controller combining adaptive neuro‐fuzzy inference system‐assisted fractional‐order PID with a nonlinear FOPI controller is introduced. It should be noted that improper controller parameters can worsen frequency deviations and system stability. Hence, a whale optimization algorithm optimizes control parameters using the integral time absolute error based objective function. Simulation studies on a modified IEEE 10‐generator 39‐bus power system, considering various disturbances like stochastic load‐generation, nonlinear generation behaviours, and time delay, validate the effectiveness of the proposed controller. Comparative analysis demonstrates the superior resilience of the cascaded control approach in managing contingencies within low‐inertia power systems, with a remarkable performance improvement of 87.9811% compared to existing control methods. [ABSTRACT FROM AUTHOR]

Riverine contamination of metals and metalloids is a growing global concern. However, our understanding of how cascade reservoirs influence the fate of these pollutants remains limited. In this study, we focused on the Jinsha River, a typical large river polluted with metal(loid)s in Southwest China, to investigate the partitioning and transport of these substances from the upper natural reaches to the lower cascade reservoirs-regulated reaches during both flood and dry seasons. Results revealed that the rapid urbanization and industrial development following the construction of reservoirs led to significant copper (Cu), nickel (Ni), lead (Pb), chromium (Cr), and cadmium (Cd) pollution. Through various analytical techniques such as correlation analysis, principal component analysis, redundancy analysis, and structural equation modeling, we determined that reservoirs had a profound impact on solid-associated parameters, including particulate organic matter (POM), suspended solid concentration (SSC), and median particle diameter (D50). These parameters, in turn, affected the fate of metal(loid)s through processes like sorption-desorption and dissolution-precipitation. High POM concentrations and low SSC and D50 values resulted in the precipitation of most particulate metal(loid)s, thereby reducing their transport across reservoirs. As river water moved downstream across the reservoirs, the percentage of particulate metal(loid)s decreased by 6.1% for arsenic (As), 38.3% for Cu, 74.9% for Ni, 36.8% for Cr, 17.8% for Cd, and 41.9% for Pb, respectively. Furthermore, the cascade reservoirs had cumulative effects on the deposition of particulate metal(loid)s, particularly concerning Cr, Cd, and Pb in the final reservoirs. Human health risk assessments indicated that dissolved As and Pb posed potential non-carcinogenic threats to residents. Despite the fact that reservoirs captured most particulate metal(loid)s, the transport of dissolved As and Pb across the reservoirs still impacted the safety of downstream drinking water. Therefore, in cascade reservoir systems, the concern regarding dissolved metal(loid) pollution remains a priority for future reservoir management. [ABSTRACT FROM AUTHOR]

In order to realize high-quality control for turboshaft engine with variable rotor speed, a cascade control method based on the acceleration estimator of gas turbine speed (Ngdot) through Complementary filtering – incremental nonlinear dynamic inversion (CF-INDI)with Newton's prediction is proposed. Firstly, an adaptive torsional suppression method based on the Recursive Least Square (RLS) algorithm and combined with the control index of power turbine speed is proposed and designed to solve the torsional instability of control system in turboshaft engine with variable rotor speed. Then, an online Ngdot estimated method based on CF-INDI with Newton's prediction is developed, and the complementary filtering method is applied to compensate for the inaccuracy of the state variable model available at a single working point, and Newton prediction is used to alleviate the problem of lagging acceleration estimate, which is accessible to realize the cascade control for turboshaft engine based on Ngdot. The simulation results show that the RLS adaptive torsional filter can effectively suppress the low-order torsional components with frequencies of 1.2 Hz and 2.0 Hz mixing in power turbine speed, and the torsional suppression effect is remarkable. In addition, under different flight conditions, CF-INDI with Newton prediction is faster and more accurate than INDI Ngdot estimate, and smoother than central difference method, which proves the feasibility of INDI Ngdot estimator. Meanwhile, after the application of CF-INDI with Newton prediction Ngdot estimator in cascade control, the anti-interference capacity of power turbine speed is stronger, and the dynamic control effect is superior, which has satisfactory robustness performance. [ABSTRACT FROM AUTHOR]

In this paper, a control design methodology is proposed for the implementation of a three-phase interleaved buck converter as a battery charger. The control strategy consists of a multiple-loop controller in cascade configuration to implement the constant-current constant-voltage (CC-CV) protocol for the fast charging of an electric vehicle (EV) battery. To compensate for the inherent asymmetric distribution of the current between the phases, the first control loop (inner loop) is dedicated to implement the democratic current sharing technique, while the two outer loops constitute a seamless controller, which allows a soft transition from CC mode to CV mode when charging the battery. The controllers are designed using the root locus method and conventional rules for cascade controllers. The design methodology is validated and tested by numerical simulations of the switched model system implemented in PSIM© software. The obtained results put in evidence a robust performance in front of input voltage and load variations, failure conditions and other parametric uncertainties. A 1.5 kW experimental prototype is implemented to charge a battery of 48 V from a 100 V DC input voltage and to validate the theoretical predictions and the simulation results. The proposal opens the way for subsequent research in ultrafast charging of batteries.

Abstract In modern power systems, the integration of inverter‐based renewable energy sources has significantly reduced system inertia, leading to heightened frequency fluctuations and potential instability within multi‐area interconnected microgrids. To counter this, a virtual inertia and damping controller utilizing battery energy storage, leveraging the virtual synchronous generator concept is proposed in this paper. This controller supplements inertia by modulating active power flow, thus stabilizing frequency during high renewable energy source penetration periods. Additionally, to enhance load frequency control, a cascaded controller combining adaptive neuro‐fuzzy inference system‐assisted fractional‐order PID with a nonlinear FOPI controller is introduced. It should be noted that improper controller parameters can worsen frequency deviations and system stability. Hence, a whale optimization algorithm optimizes control parameters using the integral time absolute error based objective function. Simulation studies on a modified IEEE 10‐generator 39‐bus power system, considering various disturbances like stochastic load‐generation, nonlinear generation behaviours, and time delay, validate the effectiveness of the proposed controller. Comparative analysis demonstrates the superior resilience of the cascaded control approach in managing contingencies within low‐inertia power systems, with a remarkable performance improvement of 87.9811% compared to existing control methods.

Excited states are the key species in photocatalysis, while the critical parameters that govern their applications are (i) excitation energy, (ii) accessibility, and (iii) lifetime. However, in molecular transition metal-based photosensitizers, there is a design tension between the creation of long-lived excited (triplet), e.g., metal-to-ligand charge transfer (3MLCT) states and the population of such states. Long-lived triplet states have low spin–orbit coupling (SOC) and hence their population is low. Thus, a long-lived triplet state can be populated but inefficiently. If the SOC is increased, the triplet state population efficiency is improved—coming at the cost of decreasing the lifetime. A promising strategy to isolate the triplet excited state away from the metal after intersystem crossing (ISC) involves the combination of transition metal complex and an organic donor/acceptor group. Here, we elucidate the excited state branching processes in a series of Ru(II)-terpyridyl push–pull triads by quantum chemical simulations. Scalar-relativistic time-dependent density theory simulations reveal that efficient ISC takes place along 1/3MLCT gateway states. Subsequently, competitive electron transfer (ET) pathways involving the organic chromophore, i.e., 10-methylphenothiazinyl and the terpyridyl ligands are available. The kinetics of the underlying ET processes were investigated within the semiclassical Marcus picture and along efficient internal reaction coordinates that connect the respective photoredox intermediates. The key parameter that governs the population transfer away from the metal toward the organic chromophore either by means of ligand-to-ligand (3LLCT; weakly coupled) or intra-ligand charge transfer (3ILCT; strongly coupled) states was determined to be the magnitude of the involved electronic coupling. [ABSTRACT FROM AUTHOR]

Abstract Cascade control structures with inner current and outer speed loop, usually utilizing PI controllers, are widely used for electrical drives to meet high‐quality requirements. The present paper introduces design guidelines via pole placement for achieving control gains both in continuous and discrete time preserving the original cascade control structure with the initially applied controllers. This paper also presents an additional prefilter design to eliminate the undesirable effect of the reference integrals. The paper presents closed‐form expressions for the control gains as the function of desired damping ratios, the natural angular frequency of the control loop, and machine parameters to achieve the desired system dynamics. The proposed design methodology is demonstrated on brushed DC and permanent magnet synchronous machines.

This article provides a model-based design method for heading control based autonomous trajectory tracking of a KVLCC2 ship. Kinematics, dynamics, and hydrodynamic force subsystems are used to represent the ship's motion equations. By contrasting the outcomes with experimental data received from the maneuvering modelling group, the accuracy of the model is confirmed. Heading angle of the ship is controlled by a linear cascade controller, and the settings of the controller are modified by using two separate heuristic optimization techniques: particle swarm optimization and genetic algorithm. The comparison of the findings demonstrates that the particle swarm optimization approach is computationally more effective than the genetic algorithm. Performance in the presence of disturbance has been investigated using the controller parameters discovered using particle swarm optimization. A suitable guidance algorithm is incorporated into the architecture of a trajectory tracking system to establish the necessary heading angle for travel between waypoints. We use a real-time simulator to visualize the ship motion on a graphical environment.

Cascade control structures with inner current and outer speed loop, usually utilizing PI controllers, are widely used for electrical drives to meet high‐quality requirements. The present paper introduces design guidelines via pole placement for achieving control gains both in continuous and discrete time preserving the original cascade control structure with the initially applied controllers. This paper also presents an additional prefilter design to eliminate the undesirable effect of the reference integrals. The paper presents closed‐form expressions for the control gains as the function of desired damping ratios, the natural angular frequency of the control loop, and machine parameters to achieve the desired system dynamics. The proposed design methodology is demonstrated on brushed DC and permanent magnet synchronous machines. [ABSTRACT FROM AUTHOR]

Heat pump-based renewable energy and waste heat recycling have become a mainstay of sustainable heating. Still, configuring an effective control system for these purposes remains a worthwhile research topic. In this study, a Smith-predictor-based fractional-order PID cascade control system was fitted into an actual clean heating renovation project and an advanced fireworks algorithm was used to tune the structural parameters of the controllers adaptively. Specifically, three improvements in the fireworks algorithm, including the Cauchy mutation strategy, the adaptive explosion radius, and the elite random selection strategy, contributed to the effectiveness of the tuning process. Simulation and field investigation results demonstrated that the fitted control system counters the adverse effects of time lag, reduces overshoot, and shortens the settling time. Further, benefiting from a delicate balance between heating demand and supply, the heating system with upgraded management increases the average exergetic efficiency by 11.4% and decreases the complaint rate by 76.5%. It is worth noting that the advanced fireworks algorithm mitigates the adverse effect of capacity lag and simultaneously accelerates the optimizing and converging processes, exhibiting its comprehensive competitiveness among this study's three intelligent optimization algorithms. Meanwhile, the forecast and regulation of the return water temperature of the heating system are independent of each other. In the future, an investigation into the implications of such independence on the control strategy and overall efficiency of the heating system, as well as how an integral predictive control structure might address this limitation, will be worthwhile. [ABSTRACT FROM AUTHOR]

Hypertension is a multifactorial disease with stage-specific gene expression changes occurring in multiple organs over time. The temporal sequence and the extent of gene regulatory network changes occurring across organs during the development of hypertension remain unresolved. In this study, female spontaneously hypertensive (SHR) and normotensive Wistar Kyoto (WKY) rats were used to analyze expression patterns of 96 genes spanning inflammatory, metabolic, sympathetic, fibrotic, and renin-angiotensin (RAS) pathways in five organs, at five time points from the onset to established hypertension. We analyzed this multi-dimensional dataset containing ~15,000 data points and developed a data-driven dynamic network model that accounts for gene regulatory influences within and across visceral organs and multiple brainstem autonomic control regions. We integrated the data from female SHR and WKY with published multiorgan gene expression data from male SHR and WKY. In female SHR, catecholaminergic processes in the adrenal gland showed the earliest gene expression changes prior to inflammation-related gene expression changes in the kidney and liver. Hypertension pathogenesis in male SHR instead manifested early as catecholaminergic gene expression changes in brainstem and kidney, followed by an upregulation of inflammation-related genes in liver. RAS-related gene expression from the kidney-liver-lung axis was downregulated and intra-adrenal RAS was upregulated in female SHR, whereas the opposite pattern of gene regulation was observed in male SHR. We identified disease-specific and sex-specific differences in regulatory interactions within and across organs. The inferred multi-organ network model suggests a diminished influence of central autonomic neural circuits over multi-organ gene expression changes in female SHR. Our results point to the gene regulatory influence of the adrenal gland on spleen in female SHR, as compared to brainstem influence on kidney in male SHR. Our integrated molecular profiling and network modeling identified a stage-specific, sex-dependent, multi-organ cascade of gene regulation during the development of hypertension. [ABSTRACT FROM AUTHOR]

Insectivorous predators, including birds and bats, play crucial roles in trophic cascades. However, previous research on these cascades has often relied on permanent predator exclosures, which prevent the isolation of specific effects of birds and bats, given their different activity patterns throughout the day. Moreover, limited knowledge exists regarding the variations in individual effects of these predators under different biotic and abiotic conditions, such as changes in elevation. To address these uncertainties, our study aimed to investigate the distinct effects of bats and birds on arthropod densities in foliage and herbivory damage in lowland and highland rainforests of Papua New Guinea (PNG). Predator exclosures were established for one month to exclude diurnal or nocturnal predators across 120 saplings (ca. 2.5–4 m tall) selected from two lowland and two highland forests (i.e., 30 saplings per study site) along the Mt. Wilhelm transect in PNG. Arthropods were collected and measured, and herbivory damage was analyzed at the end of the experiment. Birds significantly reduced arthropod densities by 30%, particularly in arthropods longer than 10 mm, regardless of elevation. Additionally, both birds and bats appeared to mitigate herbivory damage in highland forests, with protected saplings displaying up to 189% more herbivory. Our results support previous studies that have demonstrated the ability of insectivorous predators to reduce leaf damage through the control of arthropods. Furthermore, our approach highlights the importance and necessity of further research on the role of seasons and elevations in trophic cascades. [ABSTRACT FROM AUTHOR]

This paper proposes a novel cascade impedance control architecture designed for the upper limb exoskeleton rehabilitation robot. The proposed architecture comprises two parts: First, the impedance reference trajectory is shaped from the desired trajectory utilizing the desired impedance model and feedback contact torques. The second part of the proposed controller is an adaptive backstepping control, responsible for tracking the generated impedance reference trajectory. Notably, the proposed adaptive backstepping impedance controller is nonmodel-based control approach, eliminating the need for the robot's model. Furthermore, a genetic algorithm is employed as an offline tuning method for the inner position loop controller, namely the adaptive backstepping controller. This approach outperforms the conventional impedance controller without relying on the model of the robot, making it more robust against model uncertainties and unknown parameters. Furthermore, to mitigate undesired compliance resulting from the permanent attachment between the robot and the patient's limb, we introduce an adaptive gain. This gain dynamically adjusts the priority between compliance and tracking, ensuring that the robot complies only when necessary. [ABSTRACT FROM AUTHOR]

This article investigates the issue of H ∞ security output feedback control for a nonlinear networked cascade control system with deception attacks. First, to further reduce the amount of communication data, reasonably schedule network resources, and alleviate the impact of multi-channel deception attacks, an attack-dependent adaptive event-triggered mechanism is introduced into the primary network channel, and its adaptive triggered threshold can be adjusted according to the random attack probability. Secondly, the output dynamic quantization of the secondary network channel is considered. Then, a novel security cascade output feedback controller design framework based on the Takagi–Sugeno (T-S) fuzzy networked cascade control system under deception attacks is established. In addition, by introducing the Lyapunov–Krasovskii stability theory, the design conditions of the controller are given. Finally, the effectiveness and superiority of the proposed design strategies are verified by two simulation examples of power plant boiler–turbine system and power plant boiler power generation control system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xi'an Jiaotong University is the property of Editorial Office of Journal of Xi'an Jiaotong University 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 Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications 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.)

In this study, a comparative analysis of three different control methods for precise, real-time control of a complex dynamic double-tank liquid level process system was performed. Since the system in question has a time-delayed structure, feedforward proportional integral (FF-PI) control and cascaded nonlinear feedforward proportional integral delayed (CNPIR) controllers were tested on the process system. While the FF-PI controller improved the response time of the system, it showed limitations in handling external disturbances and nonlinearities. On the other hand, the CNPIR controller showed better improvements in control accuracy and lower overshoot compared to the FF-PI controller. Since the process system has a nonlinear model and is affected by external disturbances, these two controllers were inadequate in this study when compared to the fractional order adaptive proportional integral derivative sliding mode controller (FO-APIDSMC). The FO-APIDSMC controller provided fairly good performance in both tracking accuracy and disturbance rejection control for non-chattering, fast finite-time convergence, increased robustness, and uncertain dynamic processes. Experimental results reveal that the FO-APIDSMC controller achieves superior minimized tracking error and outperforms the FF-PI and CNPIR controllers by effectively handling uncertainties and external disturbances. [ABSTRACT FROM AUTHOR]

Leukotriene B4 (LTB4) is an inflammatory lipid produced in response to pathogens that is critical for initiating the inflammatory cascade needed to control infection. However, during plague, Yersinia pestis inhibits the timely synthesis of LTB4 and subsequent inflammation. Using bacterial mutants, we previously determined that Y. pestis inhibits LTB4 synthesis via the action of the Yop effector proteins that are directly secreted into host cells through a type 3 secretion system (T3SS). Here, we show that the T3SS is the primary pathogen associated molecular pattern (PAMP) required for production of LTB4 in response to both Yersinia and Salmonella. However, we also unexpectantly discovered that T3SS-mediated LTB4 synthesis by neutrophils and macrophages require the activation of two distinctly different host signaling pathways. We identified that phagocytosis and the NLRP3/CASP1 inflammasome significantly impact LTB4 synthesis by macrophages but not neutrophils. Instead, the SKAP2/PLC signaling pathway is required for T3SS-mediated LTB4 production by neutrophils. Finally, while recognition of the T3SS is required for LTB4 production, we also discovered that a second unrelated PAMP-mediated signal activates the MAP kinase pathway needed for synthesis. Together, these data demonstrate significant differences in the host factors and signaling pathways required by macrophages and neutrophils to quickly produce LTB4 in response to bacteria. Moreover, while macrophages and neutrophils might rely on different signaling pathways for T3SS-dependent LTB4 synthesis, Y. pestis has evolved virulence mechanisms to counteract this response by either leukocyte to inhibit LTB4 synthesis and colonize the host. Author summary: The production of inflammatory lipid mediators by the host is essential for timely inflammation in response to invasion by bacterial pathogens. Therefore, defining how immune cells recognize pathogens and rapidly produce these lipids is essential for us to understand how our immune system effectively controls infection. In this study, we discovered that the host signaling pathways required for leukotriene B4 (LTB4) synthesis differ between neutrophils and macrophages, highlighting important differences in how immune cells respond to infection. Together, these data represent a significant improvement in our understanding of how neutrophils and macrophages rapidly react to bacteria and provide new insights into how Yersinia pestis manipulates leukocytes to evade immune recognition to cause disease. [ABSTRACT FROM AUTHOR]

ABSTRACT The objective of this submission is to provide flexible reactive power regulation of a photovoltaic (PV)‐driven grid‐connected inverter. Here, inverter is realized as a synchronverter by employing frequency regulation using well‐established swing equation. However, reactive power regulation is accomplished by employing combined AC–DC voltage control in addition to traditional synchronverter control for ensuring smooth tracking of reactive power. Thus, the PV‐driven voltage source converter (VSC) will be injecting available active power as per the prevailing irradiation, temperature, and operator defined reactive power by employing proposed control. The performance of suggested control is evaluated and compared against existing control by considering realistic operational scenarios through a case study. [ABSTRACT FROM AUTHOR]

The intestine is populated by a complex and dynamic assortment of microbes, collectively called gut microbiota, that interact with the host and contribute to its metabolism and physiology. Diet is considered a key regulator of intestinal microbiota, as ingested nutrients interact with and shape the resident microbiota composition. Furthermore, recent studies underscore the interplay of dietary and microbiota‐derived nutrients, which directly impinge on intestinal stem cells regulating their turnover to ensure a healthy gut barrier. Although advanced sequencing methodologies have allowed the characterization of the human gut microbiome, mechanistic studies assessing diet–microbiota–host interactions depend on the use of genetically tractable models, such as Drosophila melanogaster. In this review, we first discuss the similarities between the human and fly intestines and then we focus on the effects of diet and microbiota on nutrient‐sensing signaling cascades controlling intestinal stem cell self‐renewal and differentiation, as well as disease. Finally, we underline the use of the Drosophila model in assessing the role of microbiota in gut‐related pathologies and in understanding the mechanisms that mediate different whole‐body manifestations of gut dysfunction. [ABSTRACT FROM AUTHOR]

Under the impact of global climate change and human activities, the occurrence of compound disasters such as cascading landslides and flash floods caused by heavy rainfall is increasing. In response to these compound disaster events, it is important to simultaneously transport emergency resources from multiple emergency rescue points to the disaster sites to promptly control the cascading development of disasters and reduce the areas affected by the disasters and associated adverse impacts. This study proposes a dynamic game model for emergency resources dispatch to comprehensively consider the evolution of the compound disaster states and the timely dispatch of emergency resources from the rescue points to the disaster site. The dynamic game model is exemplarily applied to the emergency resource dispatch for a rainstorm-induced compound disaster that occurs in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Starting with the analysis of the characteristics of emergency resource management and the attributes of a cascading of heavy rainstorms, landslides, and flash floods, the game model simulates the dynamic game process between the "disaster state" and the "emergency resource manager" in the rescue operations. A two-stage dynamic game model can support decision-making with the objectives of minimal time cost and sufficient resource dispatch for the disaster sites. Game results show that the united emergency resource dispatch in the three GBA metropolitan areas can efficiently respond to compound disasters that occur within the GBA metropolitan area. The dynamic game model could be extended for compound disaster emergency responses with more complicated compound effects and resource constraints. [ABSTRACT FROM AUTHOR]

The development and validation of lateral control strategies for railway running gears with independently rotating driven wheels (IRDWs) are an active research area due to their potential to enhance straight-track centering, curve steering performance, and reduce noise and wheel–rail wear. This paper focuses on the practical application of theoretical models to a 1:5 scaled test rig developed by the German Aerospace Center (DLR), addressing the challenges posed by unmodeled phenomena such as hysteresis, varying damping and parameter identification. The theoretical model from prior work is adapted based on empirical measurements from the test rig, incorporating the varying open-loop stability of the front and rear wheel carriers, hysteresis effects, and other dynamic properties typically neglected in literature. A transparent procedure for identifying dynamic parameters is developed, validated through closed- and open-loop measurements. The refined model informs the design and tuning of a cascaded PI and PD controller, enhancing system stabilization by compensating for hysteresis and damping variations. The proposed approach demonstrates improved robustness and performance in controlling the lateral displacement of IRDWs, contributing to the advancement of safety-critical railway technologies. [ABSTRACT FROM AUTHOR]

In this paper, we devoted to investigate a hyperelliptic estimate of the ultimate bound and positively invariant set for the new system via the Lyapunov function method. Furthermore, we obtained the global exponential attractive set Cλ,k$$ {C}_{\lambda, k} $$, which is an exponential decay rate. The rate of the trajectories of the system going from the exterior to the interior of the set Cλ,k$$ {C}_{\lambda, k} $$. Numerical simulations are presented to show the effectiveness and the feasibility. The theoretical results obtained will find wide applications in cascade control and chaos synchronization. [ABSTRACT FROM AUTHOR]

The paper proposes a chain fault prevention and control method that takes into account safety and network loss to address chain fault accidents and the economic operation of the grid. The method is based on the Elman neural network to identify the key nodes that can reduce network loss and improve the safety margin. Secondly, a two-layer optimization model is established, in which the inner model is used to solve the safety level of the grid for interlocking faults characterized by the distance between nodes injecting power, and the outer model integrates the maximum safety distance and the minimum network loss of the grid for interlocking faults. Finally, the basic particle swarm algorithm is used to solve the two-layer optimization model based on the IEEE-39 node system. The results of the arithmetic example show that the method can improve the security level of the grid in a targeted way so that the security margin is increased from 0.004 to 20.0992 and, at the same time reduce the network loss, so that the network loss is reduced from 0.5166 to 0.4865, which effectively compresses the scope of control and reduces the difficulty of preventive control. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications 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 Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department 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.)

Aimed at the stability problem of quadrotor Unmanned Aerial Vehicle (UAV) flight attitudes under random airflow disturbance conditions, a robust H-infinity-based dual cascade Model Predictive Control (MPC) attitude control method is proposed. Model Predictive Control itself has the capability to minimize the deviation between the prediction error and the control target by optimizing the control algorithm. The robust H-infinity controller can maintain stability in the face of system model uncertainty and external disturbances. The controller designed in this paper divides the attitude control loop into the following two parts: the angle loop and the angular velocity loop. The angle loop, serving as the main control loop of the attitude control, employs the robust H-infinity controller to process the angle of the quadrotor UAV and then transmits the processed value to the MPC controller. This approach reduces the computational load of the MPC controller. Simultaneously, by optimizing the algorithm, MPC minimizes the prediction error and the deviation from the control target. Simulation experiments confirm that the proposed algorithm improves the stability of the UAV attitude under random airflow disturbance conditions, while also achieving accurate tracking of the UAV's position. [ABSTRACT FROM AUTHOR]

This work elucidates the control of integrating a nonminimum phase system via a series cascade scheme with fractional‐order P.I. (Proportional–Integral) plus D (Derivative) controller. The traditional Internal Model Control (IMC) is adopted for inner loop controller design. The feedback D controller is synthesized with the outer loop process model, showing the proposed work's universality. The outer loop controller is suggested in the IMC framework after the accountability of fractional‐filter and inverse response compensator. This combination is revealed to enhance performance without compromising robustness. The Riemann sheet principle is explored to compute the stability of the suggested controller. The sensitivity analysis has asserted the robustness. More importantly, the optimal value of controller settings is achieved via the Teaching Learning Based Optimization (TLBO) algorithm. This TLBO algorithm uses an objective function that minimizes Integral Square Error. Two illustrative problems are utilized to examine the recommended control structure's virtue. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny 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.)

In order to address the limitation of fixed-ratio transmission (FRT), which compromises the attainment of both optimal main rotor speed and optimal power turbine speed, an optimal speed control method based on hybrid variable speed (HVS) is proposed. Firstly, based on the integrated performance calculation model of helicopter/turboshaft engine system, the distribution factors of variable speed are applied, and the integrated optimization method of optimal speed is proposed based on the minimum engine fuel flow. Subsequently, an online estimation technique employing a high-order filter is devised and engineered to achieve superior cascaded control of turboshaft engines. Finally, a novel real-time optimal speed control method based on hybrid variable speed is proposed. The simulation results under different operation conditions demonstrate that regardless of whether it is FRT or HVS, the optimal main rotor speed increases with forward velocity. In the case of HVS, turboshaft engine degradations have a significant impact on the optimal power turbine speed rather than optimal main rotor speed. Adopting an estimation method based on high-order filtering for gas turbine rotational acceleration proves more advantageous in mitigating high-frequency oscillation and continuous saltation of estimated values. Moreover, in comparison with the optimal speed control method of FRT, HVS-based approach enables simultaneous attainment of the optimal main rotor speed and power turbine speed, thereby enhancing the overall efficiency of the integrated helicopter/turboshaft engine system and significantly decreasing engine fuel consumption by over 2%. Consequently, there has been a remarkable enhancement in the overall performance of the integrated helicopter/turboshaft engine system. [ABSTRACT FROM AUTHOR]

Dynamic beam scanning with a dynamically tunable beam number, beam direction, and beam polarization remains a challenge in the terahertz gap, which is urgently needed for terahertz radar, next-generation wireless communication, and imaging applications. Different from programmable metasurfaces with element-level phase control, the beam direction is dynamically controlled by two cascaded all-dielectric metasurfaces during in-plane rotation. For a pair of circularly polarized beams with opposite handedness, the scanning field of view (FOV) can be the same or different according to the independent phase modulation in both layers and for both polarization states. Switchable single-beam and dual-beam scanning is achieved by controlling the incident polarization, which covers the ±60° FOV at 0.291 THz with an angular step of 1° and an average gain of 16.2 dBi. The output beam is quasi-circular polarized with an average ellipticity of 0.83. Single beam scanning along a Fibonacci spiral trajectory and dual beam scanning along symmetric and asymmetric trajectories are experimentally validated. Different beam scanning processes are recorded using a terahertz camera, which show good agreement with the theoretical prediction. The wide field-of-view continuous beam scanning with a switchable number of beams and a flexible FOV may have a significant impact on the development of terahertz radar and terahertz intelligent antennas. [ABSTRACT FROM AUTHOR]

SCADA systems play an important role in tracking the behaviour of critical process variables and connecting geographically dispersed subsystems at the industrial plant level. This article presents a PLC and SCADA-based control framework to automate and supervise the temperature control processes in the heat exchanger plant. The OMRON (NX1P2-9024DT1) PLC is interfaced with the Wonderware InTouch SCADA system to gather data, create a simulated temperature control prototype and carry out the necessary control operations within the heat exchanger plant. The PLC controls the entire process and programming of PLC is done using Sysmac studio automation software using the ladder programming language. The proposed system controls the temperature of the heat exchanger system through PID and Fractional Order PID (P I λ D μ ) controllers with Integral Anti-windup technique. Various control strategies like Cascade Control, Feedforward Control and Smith Predictor for time delayed process are discussed for controlling the temperature of the process. The performance of both PID and fractional order PID controllers is optimized using adaptive heuristic optimization techniques like Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). In control system design and analysis, the calculated performance indices are used as quantitative measures for evaluating the performance of a system. The combined form of temperature controller with Cascade control, Feedforward control and dead-time compensator is modelled and examined for simulation using MATLAB. Simulation and real-time experimentation analysis of the developed controllers are executed with metaheuristic optimization techniques based on different performance indices like ISE, IAE and ITAE. [ABSTRACT FROM AUTHOR]

The multi-reservoir flood control operation (MRFCO) problem is characterized by high dimensions and multiple constraints. These features pose significant challenges to algorithms aiming to solve the MRFCO problem, requiring them not only to handle high-dimensional variables effectively but also to manage constraints efficiently. The Horned Lizard Optimization Algorithm (HLOA) performs excellently in handling high-dimensional problems and effectively integrates with penalty functions to manage constraints. However, it still exhibits poor convergence when dealing with certain benchmark functions. Therefore, this paper proposes the Enhanced Horned Lizard Optimization Algorithm (EHLOA), which incorporates Circle initialization and two strategies for avoiding local optima, thereby enhancing HLOA's convergence performance. Firstly, EHLOA was tested on benchmark functions, where it demonstrated strong robustness and scalability. Then, EHLOA was applied to the MRFCO problem at the upper section of Lanzhou of the Yellow River in China, showing excellent convergence capabilities and the ability to escape local optima. The reduction rates of flood peaks achieved by EHLOA for the two millennial floods and two decamillennial floods were 55.6%, 52.8%, 58.1%, and 56.4%, respectively. Additionally, the generated operation schemes showed that the reservoir volumes changes were reasonable, and the discharge processes were stable under EHLOA's operation. Overall, EHLOA can be considered a reliable algorithm for addressing the MRFCO problem. [ABSTRACT FROM AUTHOR]

Rotor bar breakage in induction motors is often detected by analysing the signatures in the stator current. However, due to the alteration of the current spectrum, traditional methods may fail when inverter-fed motors operate with closed-loop control using a cascade structure to regulate the speed. In this paper, the potential of zero-sequence voltage analysis to detect this fault is investigated, and a new index to quantify the severity of the fault based on this signal is proposed. Signals from motors operating under different control strategies and signals from motors powered from the mains are considered to verify the robustness of the proposed fault severity index. As a result, in all the analysed conditions the value of the proposed index for the healthy motor is found to be approximately 0.010, while for the faulty machine it is between 0.110 and 0.252. [ABSTRACT FROM AUTHOR]

Model-based fault diagnosis serves as a powerful technique for addressing fault detection and isolation issues in control systems. However, diagnosing faults in closed-loop control systems is more challenging due to their inherent robustness. This paper aims to detect and isolate actuator and sensor faults in the cascade electro-hydraulic control system of a turbofan engine. Based on the fault characteristics, we design a robust unknown perturbation decoupling residual generator and an optimal fault observer specifically for the inner and outer control loops to detect potential faults. To locate the faults, we analyze the steady-state propagation laws of actuator and sensor faults within the loops using the final value theorem. Based on this, we establish the minimal-dimensional fault influence distribution matrix specific to the cascade turbofan engine control system. Subsequently, we construct the normalized residual vectors and monitor its vector angles against each row of the fault influence distribution matrix to isolate faults. Experiments conducted on an electro-hydraulic test bench demonstrate that our proposed method can accurately locate four typical faults of actuators and sensors within the cascade electro-hydraulic control system. This study enriches the existing fault isolation methods for complex dynamic systems and lays the foundation for guiding component repair and maintenance. [ABSTRACT FROM AUTHOR]