Control Strategy Research Articles

On the stabilizing contribution of different grid‐forming controls to power systems

AbstractThe increasing penetration of power‐electronics interfaced resources brings new challenges regarding the small‐signal stability of power systems. To address this issue, grid‐forming (GFM) controlled converters have emerged as an alternative to their conventional grid‐following counterparts. This paper investigates the mechanisms behind converters driven stability and quantifies the stabilizing effect of GFM controls. The linearized state‐space model of different combinations of control strategies is analysed in a multi‐infeed system considering various operating points. Through a parametric sensitivity study and an examination of the participation factors of key eigenvalues of the linearized models, it is confirmed that GFM controls contribute to system stabilization. Moreover, this paper demonstrates that this stabilizing effect varies significantly depending on the specific GFM control implemented: whether a current control loop is used or not notably impacts stability.

Dictyocaulosis in cattle: Retrospective analysis of 20 outbreaks in Central Argentina

Bovine lungworms (Dictyocaulus viviparus) are nematodes which cause a respiratory disease known as verminous bronchitis or pneumonia. In this paper, we describe 20 outbreaks of bovine dictyocaulosis recorded between 2000 and 2023 in Central Argentina. Outbreaks occurred more frequently during the autumn-winter season (from April to August) and affected cattle under 1 year old in beef production systems. An average morbidity and mortality of 26.22 % and 8.44 % were registered, respectively. The main clinical signs observed were respiratory distress (coughing, tachypnea, dyspnea, and nasal discharge), weight loss, weakness, decubitus, and diarrhea. Necropsies were performed in thirty-one calves, heifers, and steers. Gross findings included diffuse interstitial or multifocal pneumonia, with marbled appearance intermingling atelectasis and red-gray firm areas of consolidation, and subpleural and interlobular emphysema and edema. Microscopically, lungs were characterized by abundant edema and mixed intra-alveolar multifocal to coalescent infiltrate. Frequently, adult worms and/or larvae were spotted in the bronchi or alveoli, respectively. Some cases exhibited proliferation of type 2 pneumocytes and hyaline membranes covering the alveolar septa. Co-infections with gastrointestinal nematodes were frequently found in fecal samples. Given the perspective of anthelmintic resistance and future changes in environmental conditions due to climate change, integrated parasitic control strategies are mandatory and should be tailored to each production system. The information gathered in this research provides an overview of lungworm infections in livestock production systems from Central Argentina and could be useful for surveilling, monitoring and designing strategic interventions for the control of this important parasitic disease in the region.

Offline and online exergy-based strategies for hybrid electric vehicles

Abstract Exergy-based control strategies for ground hybrid electric vehicles (HEVs) enable to pursue unconventional optimization goals that are inaccessible when standard energy-based modeling frameworks based on fuel consumption minimization are used. In this work, we formulate and solve offline and online exergy-based optimization strategies for military HEVs aimed at the minimization of genset exergy destruction and thermal emissions to increase vehicle efficiency and minimize the risk of thermal imaging detection, respectively. We refer to the offline version of these strategies as exergy minimization strategies (ExMSs). Adaptive ExMSs (A-ExMSs) are then formulated for online implementation. Moreover, charge increasing ExMSs and A-ExMSs are developed to charge the battery as much as possible during a driving mission followed by a silent watch phase. To assess the performance of the proposed strategies, the results obtained by the ExMSs and A-ExMSs are compared to the benchmark solutions obtained by Dynamic Programming.

Enhanced frequency control of a hybrid microgrid using RANFIS for partially shaded photovoltaic systems under uncertainties

Nowadays environmental concerns and fossil fuel limitations, as well as economic benefits and technical issues such as reliability lead conventional distribution networks to smart microgrids, where the renewable energy resources are merged with the grids. Nevertheless, the systems face new challenges due to the intermittent nature and uncertainties in the distributed generations, which cause frequency fluctuations in the microgrid. The photovoltaic cells are the main part of the contemporary microgrids. Although the photovoltaic (PV) systems depend on solar irradiance, and temperature and are affected by the partial shading phenomenon they could contribute to improving the microgrid frequency stability with a proper control scheme. In this paper, the frequency control strategy is designed for a hybrid stand-alone microgrid, which is robust against load disturbances, variations in weather conditions, and uncertainties in the microgrid parameters. The proposed intelligent control scheme relies on the Recurrent Adaptive Neuro Fuzzy Inference System (RANFIS). The Whale Optimization Algorithm (WOA) is employed to optimize the RANFIS controller structure and generate the parameters of membership functions. In this multi-objective optimization, the objectives are settling time (ST), overshoot (Osh), and Integral Square Error (ISE). The simulation results verify the high robustness and performance of the proposed RANFIS controller, compared to other controllers, during various operational circumstances, as well as the sporadic behavior of renewable energy resources (RES) such as fluctuations in solar radiation and certain uncertainties in the microgrid parameters.

Topology, dynamics, and control of a muscle-architected soft arm

Muscular hydrostats, such as octopus arms or elephant trunks, lack bones entirely, endowing them with exceptional dexterity and reconfigurability. Key to their unmatched ability to control nearly infinite degrees of freedom is the architecture into which muscle fibers are weaved. Their arrangement is, effectively, the instantiation of a sophisticated mechanical program that mediates, and likely facilitates, the control and realization of complex, dynamic morphological reconfigurations. Here, by combining medical imaging, biomechanical data, live behavioral experiments, and numerical simulations, an octopus-inspired arm made of [Formula: see text]200 continuous muscle groups is synthesized, exposing "mechanically intelligent" design and control principles broadly pertinent to dynamics and robotics. Such principles are mathematically understood in terms of storage, transport, and conversion of topological quantities, effected into complex 3D motions via simple muscle activation templates. These are in turn composed into higher-level control strategies that, compounded by the arm's compliance, are demonstrated across challenging manipulation tasks, revealing surprising simplicity and robustness.

Randomness suppress backward bifurcation in an epidemic model with limited medical resources

This paper delves into the dynamic features of a stochastic SIR epidemic model featuring a perturbed transmission rate influenced by white noise. Our primary aim is to unravel the intricate interplay between restricted medical resources, their supply efficiency, and environmental stochasticity, shedding light on their collective impact on the transmission dynamics of infectious diseases. Our findings bring to light a notable distinction from the deterministic counterpart of the model. Specifically, under varying scenarios of medical resource availability and supply efficiency, the stochastic model exhibits a departure from bifurcation phenomena. This stands in contrast to the deterministic model, which is characterized by the presence of both backward bifurcation and Hopf bifurcation phenomena. To complement and validate our theoretical findings, numerical simulations are employed, providing concrete illustrations of the dynamical phenomena discussed in the paper. This research contributes to a nuanced understanding of the intricate interplay between stochastic environmental factors, medical resource constraints, and disease transmission dynamics, offering valuable insights for public health management and epidemic control strategies.

A Wide Output Voltage Range and High Efficiency Dual-Channel WPT System Employing Multimode Control Strategy

A Wide Output Voltage Range and High Efficiency Dual-Channel WPT System Employing Multimode Control Strategy

Campylobacter control strategies at postharvest level.

Campylobacter is highly associated with poultry and frequently causes foodborne illness worldwide. Thus, effective control measures are necessary to reduce or prevent human infections. In this review, Campylobacter control methods applicable at postharvest level for poultry meat during production, storage, and preparation are discussed. Drying and temperature are discussed as general strategies. Traditional strategies such as steaming, freezing, sanitizing, organic acid treatment, and ultraviolet light treatment are also discussed. Recent advances in nanotechnology using antibacterial nanoparticles and natural antimicrobial agents from plants and food byproducts are also discussed. Although advances have been made and there are various methods for preventing Campylobacter contamination, it is still challenging to prevent Campylobacter contamination in raw poultry meats with current methods. In addition, some studies have shown that large strain-to-strain variation in susceptibility to these methods exists. Therefore, more effective methods or approaches need to be developed to substantially reduce human infections caused by Campylobacter.

The Amount and Pattern of Reciprocal Compensations Predict Performance Stability in a Visually Guided Finger Force Production Task.

Previous work suggests that synergistic activity among motor elements implicated in force production tasks underlies enhanced performance stability associated with visual feedback. A hallmark of synergistic activity is reciprocal compensation, that is, covariation in the states of motor elements that stabilizes critical performance variables. The present study examined if characteristics of reciprocal compensation are indicators of individuals' capacity to respond adaptively to variations in the resolution of visual feedback about criterion performance. Twenty healthy adults (19.25 ± 1.25years; 15 females and five males) pressed two sensors with their index fingers to produce a total target force equivalent to 20% of their maximal voluntary contraction under nine conditions that differed in the spatial resolution of real-time feedback about their performance. By combining within-trial uncontrolled manifold and sample entropy analyses, we quantified the amount and degree of irregularity (i.e.,non-repetitiveness) of reciprocal compensations over time. We found a U-shaped relationship between performance stability and gain. Importantly, this relationship was moderated by the degree of irregularity of reciprocal compensation. Lower irregularity in reciprocal compensation patterns was related to individuals' capacity to maintain (or minimize losses in) performance under changes in feedback resolution. Results invite future investigation into how interindividual variations in reciprocal compensation patterns relate to differences in control strategies supporting adaptive responses in complex, visually guided motor tasks.

Thermal characteristics analysis and cooling model optimization of motorized spindle

Aiming at the influence of poor cooling conditions and traditional cooling control strategy on motorized spindle temperature and machining performance. Firstly, the heat transfer model of the motorized spindle cooling system is studied. Secondly, the influence of coolant inlet flow rate and temperature on the thermal characteristics of the motorized spindle is studied. Then, a thermal network model is established to solve the temperature of each temperature measuring point. Finally, the thermal characteristic experiment of the motorized spindle is carried out, and the cooling fluid flow optimization model is established based on the particle swarm optimization algorithm and simulated annealing algorithm. The results show that the temperature difference of the motorized spindle does not exceed 45°C, the thermal deformation does not exceed 40.2μm, and the thermal elongation is inhibited by 36%. The maximum error of the Thermal Network Method and Finite Element Method（FEM）is 14.24%. The utilization of the average logarithmic temperature difference for assessing the cooling effectiveness of optimal flow rates revealed that the particle swarm optimization algorithm demonstrates a comparatively lower average logarithmic temperature difference in comparison to the simulated annealing algorithm. The heat exchange efficiency of the motorized spindle is higher under the optimal flow rate obtained by the particle swarm algorithm.

An iteratively optimized downscaling method for city-scale air quality forecast emission inventory establishment

Air quality models (AQMs) are pivotal in forecasting air quality and shaping pollution control strategies. Nonetheless, the effectiveness of AQMs is often compromised in many cities due to the absence of accurate local emission inventories. To address this gap, this study presents a novel AQM-ready emission inventory generation technique with iterative optimization ability for city-scale applications in China. An efficient emission processing tool was introduced in this study, which utilizes the High-Resolution Multi-resolution Emission Inventory for China (HR-MEIC) as input. Using environmental observations and a region map, the tool can justify emissions of different regions iteratively. With the iterative optimization method, the model performance can be notably improved even without local emissions. The optimization was realized by splitting model-ready emissions into different regions and adjusting the emissions using scale factors calculated with the modeling results and the observations of each region. This methodology was applied to the Eight Cities in the Chengdu Plain (CP8C), located in the western margin of Sichuan Basin with complex topography and meteorological conditions, southwestern China, monthly throughout 2023. Air quality modeling was carried out using Weather Forecast and Research Model (WRF) and the Community Multiscale Air Quality Model (CMAQ). The results showed that the optimization acquired a good performance after five cycles for PM2.5 and NO2, with correlation coefficients (R values) surging from 0.62 and 0.37 to 0.77 and 0.73, respectively, while their normalized mean bias (NMB) substantially decreased from 22.8 % and 100.4 % to 3.6 % and 3.3 %. The underestimation on O3 concentration was also improved by the optimization, although enhancements in O3 modeling remained modest. This technique provides an easy-to-copy method to generate reasonable AQM-ready emission files with open emission data and observation data, which would be beneficial for the cities' air quality forecast in cities without local emission inventories.

Pelvic floor muscle electrical coupling in chronic pelvic pain: Insights into pathophysiology and botulinum toxin treatment effects

This study aimed to assess the electrical coupling between both pelvic floor muscle (PFM) sides (two-sided coupling) and within individual PFM sides (one-sided coupling) in chronic pelvic pain (CPP) before and after botulinum neurotoxin type A (BoNT/A) treatment. Surface electromyographic (sEMG) signals were recorded from the left and right PFM of 24 patients (P) with CPP before and after being treated with BoNT/A (Weeks 0,8,12,24). Recordings were also made in 24 healthy women (H). PFM two-sided and one-sided coupling was evaluated during contractions by the cross-correlation (CC) and the imaginary part of coherency (iCOH) of their sEMG signals. Significant differences between their values were assessed comparing P(0) vs. P(8,12,24) and H vs. P(0,8,12,24). This study showed that PFM two-sided coupling is similar across groups before treatment, while PFM one-sided coupling on the patients’ most painful side is deranged before and also after BoNT/A treatment: amplitude coupling is lower (<CC) and phase difference is greater (>iCOH) than healthy women’s. This could be justified by altered neuromotor control strategies developed as an adaptation to muscle pain, structural and electrical changes in PFM, and alterations in their innervation pattern, which may influence the onset, perpetuation, or recurrence of CPP after treatment.

Integrating Autonomous Vehicles (AVs) into Urban Traffic: Simulating Driving and Signal Control

The integration of autonomous vehicles into urban traffic systems offers a significant opportunity to improve traffic efficiency and safety at signalized intersections. This study provides a comprehensive evaluation of how different autonomous vehicle driving behaviors—cautious, normal, aggressive, and platooning—affect key traffic metrics, including queue lengths, travel times, vehicle delays, emissions, and fuel consumption. A four-leg signalized intersection in Balgat, Ankara, was modeled and validated using field data, with twenty-one scenarios simulated to assess the effects of various autonomous vehicle behaviors at penetration rates from 25% to 100%, alongside human-driven vehicles. The results show that while cautious autonomous vehicles promote smoother traffic flow, they also result in longer delays and higher emissions due to conservative driving patterns, especially at higher penetration levels. In contrast, aggressive and platooning autonomous vehicles significantly improve traffic flow and reduce delays and emissions. Mixed-behavior scenarios reveal that different driving styles can coexist effectively, balancing safety and efficiency. These findings emphasize the need for optimized autonomous vehicle algorithms and signal control strategies to harness the potential benefits of autonomous vehicle integration in urban traffic systems fully, particularly in terms of improving traffic performance and sustainability.

Risk Mitigation in Environmental Conservation for Potato Production in Cisangkuy Sub-Watershed, Bandung Regency, West Java, Indonesia

Potatoes are a crop that thrives in highland areas, and Bandung Regency is one of the major potato production centers in West Java. This production center is located in an environmentally focused village development area within the Cisangkuy Sub-Watershed of Bandung Regency. The purpose of this study is to identify risks arising from various risk sources and to formulate risk control strategies for potato production in this region. The method used is the house of risk (HOR) method. In farming activities, farmers must comply with environmental regulations. However, many farmers are still unaware of the importance of environmental sustainability, particularly in their use of chemicals. To actively engage in environmental management efforts, it is crucial to understand the characteristics of potato farmers in Bandung Regency, especially those located in the development area of environmentally focused villages within the Cisangkuy Sub-Watershed. The results of this study identified 33 risk events. The risk event with the highest impact is waterlogged plants (E10), with an impact value of 8.9. Based on the Pareto diagram, 16 priority risk sources need to be addressed. The most significant risk source identified is the use of uncertified seeds (A29). To mitigate risks in potato production, 21 preventive actions (PAs) have been proposed. One of the most effective strategies is for farmers to purchase seed potatoes directly from Balitsa (PA1), with an effectiveness ratio (ETD) of 4372. Another recommended strategy is to purchase certified seeds from other breeders (PA2). These strategies are prioritized to reduce the risks faced by potato farmers.

Conditional Adversarial Motion Priors by a Novel Retargeting Method for Versatile Humanoid Robot Control

ABSTRACTSignificant advancements have been made in the field of humanoid robot, particularly in walking control strategies. However, achieving straight‐legged walking remains a challenge. Both the traditional model‐based and the learning‐based control methods confront with difficulties in achieving natural humanoid gait feature. To address this issue, a general motion retargeting method is developed and also evaluated for humanoid robots with different structure, size and degrees of freedom. Moreover, a conditional adversarial motion priors method is proposed based on reinforcement learning and validated on the humanoid robot GTX‐III. Through various motion segments from the motion capture database, it is shown that this method can successfully enable the humanoid robot to perform straight‐legged walking with flexible and natural transitions between different gaits within a single discriminator network.

Investigating an Outbreak of Extensively Drug-Resistant Acinetobacter baumannii in a Tertiary Healthcare Center in Lebanon Using Next-Generation Sequencing

The frequent occurrence of Acinetobacter baumannii in hospital settings and the elevated rate of antimicrobial resistance in this pathogen represent a serious clinical and public health threat worldwide and particularly in Lebanon where outbreak surveillance and control are still insufficient. Whole-genome sequencing (WGS) is currently a fast and reliable tool to study outbreaks at the molecular level and obtain actionable knowledge leading to better control measures. We collected 59 A. baumannii isolates from intensive care unit (ICU) patients and from the hospital environment between August 2022 and May 2023, performed AST and subjected their gDNA to WGS. Analysis was performed to reveal the sequence types (ST), the relatedness to strains that caused other outbreaks and the arsenal of resistance genes harbored by these bacteria. Out of 59 isolates, 81.4% were categorized as extensively drug-resistant (XDR), 13.6% as multi-drug-resistant (MDR) and 1.7% as pan-drug-resistant. All isolates belonged to international clone (IC)2, of which the majority were of ST2 (91.5%). Our isolates clustered well with those of a previous outbreak in the same hospital. In addition, isolates from Lebanese hospitals clustered well together and some clustered with those originating from different countries. The observed genetic relatedness between our current isolates with those from the previous outbreaks underscores the importance of strict surveillance to limit the threat of outbreaks. Moreover, the clustering of Lebanese isolates with others from distant countries proves the necessity of further investigations addressing the international spread of drug-resistant pathogens and resulting in the implementation of control strategies.

Data-Driven Modeling of DC–DC Power Converters

This article presents a data-driven methodology for modeling DC–DC power electronic converters. Using the proposed methodology, the dynamics of a converter can be captured, thereby eliminating the need for explicit theoretical modeling methods. This approach only requires the acquisition of fundamental measurements: currents through inductors and voltages across capacitors. The acquired data are used to construct a linear difference system, which is algebraically manipulated to form a state–space representation of the converter under analysis. Three DC–DC converter topologies were analyzed, and their resulting models were tested and compared with simulation data, yielding an average error deviation of approximately 2% for current signals and 4% for voltage signals, demonstrating precise tracking of the actual dynamics. The proposed data-driven methodology could simplify the implementation of adaptive control strategies in larger-scale solutions or in the interconnection of multiple converters.

A Control Strategy for Reducing Voltage Ripples in Series-Connected SiC MOSFETs Using Active Clamping Modules in High Power VSCs

A Control Strategy for Reducing Voltage Ripples in Series-Connected SiC MOSFETs Using Active Clamping Modules in High Power VSCs

Fuzzy Adaptive Impedance Control for the Two-Layered Vertical Cable-driven Parallel Robot

This study unveils a novel two-layered vertical octahedron cable-driven parallel robot (TLVO CDPR), distinctively engineered for effective force interactions with vertical surfaces while preventing collision with cables. It pioneers an innovative control strategy integrating a position-based fuzzy adaptive impedance controller with a fuzzy Proportional – Integral – Derivative (PID) controller, adeptly managing both the pose and contact force of the robot. While dual control application is often found in rigid-link robots, it remains a largely unexplored frontier in the realm of CDPRs, despite its critical importance in sectors like manufacturing and assembly. The fuzzy adaptive mechanism significantly boosts impedance control efficacy in the face of unpredictable, non-uniform working surfaces, ensuring algorithmic stability and convergence. Concurrently, fuzzy logic is harnessed to optimize PID controller performance. The forward kinematics challenge is efficiently tackled using a least squares method coupled with an Inertial Measurement Unit (IMU), ensuring swift and precise solutions. The robustness and adaptability of the robot and its control systems are thoroughly validated through extensive experimental trials, involving diverse trajectories and varying uncertainties on vertical working surfaces.

Spatiotemporal variation of polycyclic aromatic hydrocarbons in Tibetan lake sediment cores reveals the influence of forest fires

Despite declining anthropogenic emissions of polycyclic aromatic hydrocarbons (PAHs) due to global control strategies, forest fire emissions have been increasing, significantly affecting PAH dynamics in global sinks. This study investigated the spatiotemporal variations of sedimentary PAHs in three Tibetan lakes—Yiong Tso, Yamdrok Yumtso, and Urru Tso—to determine the influence of forest fires on PAH levels and historical trends. Yiong Tso Lake, located in a fire-affected watershed, exhibited the highest PAH concentrations (average of 43.4 ± 25.7 ng/g) with significant fluctuations since the 1920s, peaking in the 1960s (46.3 ng/g) and 1980s (91.3 ng/g), corresponding to periods of intense forest fires. This pattern aligned with source contribution estimates using the modified Cohen's d (mcd), indicating the dominance of forest fires as a PAH source until the 1990s. PAH concentrations decreased with increasing distance from the southeastern Tibetan Forest, as observed in Yamdrok Yumtso (average of 36.1 ± 19.9 ng/g) and Urru Tso (average of 16.4 ± 6.9 ng/g). Temporal variations in PAH concentrations and mcd values from these lakes also reflected a response to forest fires during the 1960s, suggesting a widespread influence of forest-fire-derived PAHs across the plateau. The impact of forest fires on sedimentary PAHs was expected to persist for decades, with an estimated half-life of approximately 11–12 years. These findings highlight significant emissions of PAHs from forest fires in the Tibetan Plateau, potentially transforming regional PAH dynamics and influencing global cycling.