Coordination Control Research Articles

A coordinated control strategy for active transient voltage support in DFIG-based wind farms

During the implementation of active voltage support in wind farms, coordinating the operation of multiple wind turbines presents significant challenges. The dynamic response of the entire wind farm becomes complex during grid faults, making it difficult to achieve coordinated voltage support across different wind turbines. To address this, a coordination control strategy for doubly fed wind farms is here proposed which is based on Q-learning informed by the sensitivity of voltage. First, a method for calculating the voltage sensitivity of DFIG-based wind farms is introduced, utilizing the arbitrary polynomial chaos approach. Additionally, the operational constraints of wind farms are defined based on the average short-circuit ratio of reactive power. The voltage support characteristics of multi-machine wind farms under grid fault conditions are then thoroughly explored. Subsequently, an improved Q-learning algorithm is developed, based on the sensitivity of voltage. This algorithm aids in optimizing the control commands, thus enhancing the effectiveness of the voltage support system. Finally, adopting this voltage sensitivity as the basis for the coordinated control commands and applying the improved Q-learning algorithm as the implementation mechanism, a coordinated control strategy for active voltage support in DFIG-based wind farms is proposed. Simulation results demonstrate that the proposed control strategy can provide effective active voltage support during grid faults.

Investigating Motor Coordination Using BXD Recombinant Inbred Mice to Model the Genetic Underpinnings of Developmental Coordination Disorder.

The fundamental skills for motor coordination and motor control emerge through development. Neurodevelopmental disorders such as developmental coordination disorder (DCD) lead to impaired acquisition of motor skills. This study investigated motor behaviors that reflect the core symptoms of human DCD through the use of BXD recombinant inbred strains of mice that are known to have divergent phenotypes in many behavioral traits, including motor activity. We sought to correlate behavior in basic motor control tasks with the known genotypes of these reference populations of mice using quantitative trait locus (QTL) mapping. We used 12 BXD strains with an average of 16 mice per group to assess the onset of reflexes during the early neonatal stage of life and differences in motor coordination using the tests for open field, rotarod, and gait behaviors during the adolescent/young adulthood period. Results indicated significant variability between strains in when neonatal reflexes appeared and significant strain differences for all measures of motor coordination. Five strains (BXD15, BXD27, BXD28, BXD75, BXD86) struggled with sensorimotor coordination as seen in gait analysis, rotarod, and open field, similar to human presentation of DCD. We identified three significant quantitative trait loci for gait on proximal Chr 3, Chr 4, and distal Chr 6. Based on expression, function, and polymorphism within the mapped QTL intervals, seven candidate genes (Gpr63, Spata5, Trpc3, Cntn6, Chl1, Grm7, Ogg1) emerged. This study offers new insights into mouse motor behavior, which promises to be a first murine model to explore the genetics and neural correlates of DCD.

Reduced-order interval observer-based coordination control for discrete-time multi-agent systems

Reduced-order interval observer-based coordination control for discrete-time multi-agent systems

Optimization model for tram departure interval and multi-path traffic signal coordination control

Efficient coordination between tram operation and traffic signal control is significantly critical for improving urban multi-modal traffic system mobility. This study proposes an innovative optimization model for tram departure intervals and multi-modal multi-path traffic signal coordination, promoting general traffic efficiency and tram stability and reliability. The tram signal priority frequency is mathematically analyzed according to tram timetables and signal control schemes. An optimization method for tram departure intervals and signal cycles is proposed to minimize tram signal priority frequency and adapt to diverse traffic conditions at intersections. Based on the optimized results, a multi-modal multi-path coordinated signal control model is developed to maximize the general traffic green wave bandwidth and ensure tram smooth passages at intersections. Case studies conducted in a numerical network and Dresden network verify the proposed method outperforms traditional methods.

Enhanced consensus control architecture for autonomous platoon utilizing multi‐agent reinforcement learning

AbstractCoordinating a platoon of connected and automated vehicles significantly improves traffic efficiency and safety. Current platoon control methods prioritize consistency and convergence performance but overlook the inherent interdependence between the platoon and the the non‐connected leading vehicle. This oversight constrains the platoon's adaptability in car‐following scenarios, resulting in suboptimal optimization performance. To address this issue, this paper proposed a platoon control framework based on multi‐agent reinforcement learning, aiming to integrate cooperative optimization with platoon tracking behavior and internal coordination strategies. This strategy employs a bidirectional cooperative optimization mechanism to effectively decouple the platoon's tracking behavior from its internal coordination control, and then recouple it in a multi‐objective optimized manner. Additionally, it leverages long short‐term memory networks to accurately capture and manage the platoon's dynamic nature over time, aiming to achieve enhanced optimization outcomes. The simulation results demonstrate that the proposed method effectively improves the platoon's cooperative effect and car‐following adaptability. Compared to the consensus control strategy, it reduces the average spacing error by 8.3%. Furthermore, the average length of the platoon decreases by 19.1%.

Trends in smoking prevalence and socio-economic inequalities across regions in England: A population study, 2006 to 2024.

In addition to national policies and interventions, certain regions in England (particularly in the North) coordinate regional tobacco control programmes. This study aimed to (i) examine trends in tobacco smoking prevalence and socioeconomic inequalities in smoking across regions and (ii) explore how trends in smoking prevalence have differed between regions with and without dedicated regional tobacco control activity. Observational study using data drawn from nationally representative monthly cross-sectional household surveys, conducted between November 2006 and July 2024. England. 368 057 adults (≥16 years old). We used logistic regression to estimate time trends in current smoking by region, and tested interactions with occupational social grade to explore differences between more and less advantaged groups. Smoking prevalence declined most in the North [28.8% to 15.8%; -12.9 percentage points (95% confidence interval -14.4 to -11.5)], similar to the national average in the Midlands [25.2% to 16.0%; -9.2 (-10.6 to -7.9)], and least in the South [22.7% to 17.3%; -5.3 (-6.5 to -4.0)], reducing regional disparities such that prevalence was similar across regions in 2024. Socioeconomic inequalities in smoking prevalence between more and less advantaged social grades fell most in Yorkshire and the Humber [from 17.9 percentage points (14.1-21.8) to 3.7 (0.4-7.0)] and the West Midlands [from 16.1 (12.8-19.6) to 3.0 (-0.03 to 6.0)]. Regions with sustained regional tobacco control activity saw greater declines in smoking prevalence [-13.3 (-15.3 to -11.3)] than regions with none [-9.3 (-10.0 to -8.5)]. Between 2006 and 2024, smoking rates in the North of England fell faster than the national average, narrowing the geographic inequalities in smoking prevalence and bringing the North of England into alignment with other regions by 2024. Regional tobacco control programmes appeared to contribute to this progress.

Acceptability and Preliminary Efficacy of a Novel Web-Based Physical Activity for the Heart (PATH) Intervention Designed to Promote Physical Activity in Adults With Obesity: Protocol for a Pilot Randomized Controlled Trial.

Even in the absence of weight loss, any level of physical activity (PA) can reduce the risk of cardiovascular disease among individuals with obesity. However, these individuals face multifaceted barriers that reduce their motivation and engagement in PA. They prefer programs that are convenient, fun to engage in, and feature people who they can relate to. Yet, there is a paucity of PA interventions that are designed to incorporate these preferences. We designed the web-based PA for The Heart (PATH) intervention to address this gap. This study aimed to describe the protocol of a study that aims to examine the acceptability and preliminary efficacy of PATH intervention among insufficiently active adults with obesity aged at least 18 years. This is a 6-month pilot randomized controlled trial (RCT), using a parallel design with 1:1 allocation to intervention or control group. The PATH intervention group is given access to the PATH platform, but the resources each participant can access are tailored according to their baseline fitness level. Control group receives a self-help PA handout. Both groups self-monitor their PA using Fitbit (Google) and have Zoom (Zoom Video Communications) meetings twice a month with either the health coach (intervention) or study coordinator (control). The outcomes at 6-months include acceptability, changes in PA, and cardiometabolic risk from baseline to 6-months. We screened 763 individuals for eligibility and 89 participants were enrolled and randomized to the intervention (45/504, 50.6%) and control arms (44/504, 49.4%). The average age was 48.7 (SD 12.17) years, and most participants were female (81/504, 90.1%), Black (45/504, 50.6%), and non-Hispanic (83/504, 93.3%). No systematic differences in baseline characteristics were observed between the study arms. The 6-month intervention is currently underway, and the completion of follow-up data collection is expected in February 2025, with results to be published soon after. The PATH intervention offers a promising, evidence-based approach to overcoming the barriers that have hindered previous PA programs for adults with obesity. It can support new and existing programs to foster long-term maintenance of health-enhancing PA. ClinicalTrials.gov NCT05803304; https://clinicaltrials.gov/study/NCT05803304. DERR1-10.2196/67972.

Polymer Binder Blends Stabilize Alkaline Hydrogen Evolution by Heterogenized Molecular Phen-Based Cobalt Electrocatalysts through Coordination and Environmental Control.

With the increase in greenhouse gas emissions and their detrimental effect on the environment, there is a push to develop a renewable way to produce H2, a fuel source that has nonharmful byproducts, unlike traditional methods of energy production. Alkaline water electrolysis has seen increasing focus as a viable way to produce H2, but efficient and stable electrocatalysts are required to facilitate this process. Here, a heterogenized Co(II) phenanthroline-based complex for the production of H2 from alkaline water is disclosed. Activity was improved by considering the role of axial Co ligation and the reaction environment created by the polymer binder in the catalyst inks by using variable ratios of Nafion and poly-4-vinylpyridine (P4VP). A ratio of 1:1 Nafion:P4VP was found to have the highest stability, and Co nanoparticle formation was not observed when P4VP was included as part of the binder mixture. The activity and stability enhancement could not be replicated by the addition of molecular pyridine or the use of poly-2-vinylpyridine, which is sterically prevented from coordinating to Co. The increased electrochemical performance caused by the inclusion of Nafion as part of the polymer binder is attributed to a role in mass transfer to and from the Co active site during catalysis, complementing the stabilizing effect of P4VP on the molecular active site.

Distributed Frequency Regulation Method for Power Grids Considering the Delayed Response of Virtual Power Plants

To tackle the challenges of distributed flexible resource coordination and inherent control delays in virtual power plant (VPP)-participated frequency regulation (FR) for interconnected power systems, this paper proposes a novel distributed model predictive control (DMPC)-based FR strategy with time-delay compensation. A hierarchical FR architecture is first established, incorporating analytical models of communication latency in VPP coordination and detailed electro-mechanical dynamics of generation-load systems. Through state-space augmentation techniques, we develop a delay-embedded generalized predictive model that systematically integrates historical state reconstruction and future trajectory prediction. This approach constructs a time-delay-compensated DMPC (TDC-DMPC) optimization framework that uses quadratic programming to solve the objective function and generate the optimal FR control sequences for VPP flexible load clusters. Comparative simulations on a four-area interconnected power system show that the proposed TDC-DMPC strategy achieves significant progress in frequency regulation. Operating under a 30 ms communication delay, the TDC-DMPC reduces frequency deviations by 30.5% and 18.8% compared to conventional DMPC and sequence-selective DMPC (SS-DMPC), respectively, while reducing the stabilisation time to 0.4 s—a fivefold improvement over the conventional method’s 2.2 s. Robustness analysis confirms exceptional resilience, with the system maintaining stable operation under extreme conditions, including 600 ms communication delays and 20% parameter perturbations, significantly outperforming existing methods in stress scenarios.

Adaptive optimal coordination control of perturbed Bilateral Teleoperators with variable time delays using Actor-Critic Reinforcement Learning algorithm

Adaptive optimal coordination control of perturbed Bilateral Teleoperators with variable time delays using Actor-Critic Reinforcement Learning algorithm

Evaluation of the benefits of respirator breathing and vomiting training and dynamic core training on improving respiratory muscle strength.

Respiratory muscle training is a widely used method in clinical diagnosis and medical treatment. Due to the fact that the respiratory muscles are located in the core area that supports the human body. Therefore, understanding how to train the core muscle group in the correct way is of great significance in improving physical fitness and reducing the occurrence of sports injuries. This article reviews the effects of respirator breathing and vomiting training (RBVT) and dynamic core training on respiratory muscle strength and related physiological mechanisms. Both acute and long-term RBVT can promote respiratory muscle function, thereby reducing or delaying the degree of respiratory muscle fatigue, and helping to accelerate the clearance of lactate after exercise. The intra-abdominal pressure generated by dynamic core resistance training can stimulate the diaphragm, reduce discomfort caused by professional equipment training, improve respiratory muscle function, and enhance athletic performance. Low intensity core training may improve the central nervous system's control of muscle coordination, thus benefiting from increased movement efficiency, while high-intensity core training may increase the strength of core muscle groups, thus benefiting athletes' athletic performance. RBVT is not suitable for training the diaphragm, But dynamic core training can reduce discomfort caused by specialized equipment training. It can be used for rehabilitation, improve respiratory muscle function, and enhance exercise performance. However, the optimal diaphragm pressure generated by the transverse abdominal muscle and internal oblique muscle is a topic worthy of further research.

PDE-Based Leader-Following Coordination Control for Flexible Manipulators With Event-Triggered Communication Over Directed Graphs

PDE-Based Leader-Following Coordination Control for Flexible Manipulators With Event-Triggered Communication Over Directed Graphs

An improved traffic coordination control integrating traffic flow prediction and optimization

An improved traffic coordination control integrating traffic flow prediction and optimization

A power coordination control strategy of DC microgrid with electricity-hydrogen energy storage considering minimum operating cost and energy storage safety

A power coordination control strategy of DC microgrid with electricity-hydrogen energy storage considering minimum operating cost and energy storage safety

Design and Control of the Resonant Auxiliary Circuit for Voltage Regulator Module (VRM) with Fast Load Step Transient

This paper proposes a transient energy auxiliary supply circuit architecture based on resonant switched-capacitor principles, aimed at optimizing the system’s transient response to meet the growing power supply demands. This paper first introduces the relevant principles of resonant switched-capacitor converters. Based on this, a transient energy path topology based on resonant principles is designed to achieve bidirectional, fast, and low electromagnetic interference energy transmission. Corresponding system coordination control strategies and high-precision switch control based on delay lines are proposed for the designed circuit topology. A circuit model is built in SIMPLIS (V8.20a) software for system simulation, and a prototype is built based on FPGA to verify circuit functionality and performance. Experimental results demonstrate that the resonant energy auxiliary circuit can operate in conjunction with a six-phase Buck circuit prototype. Under test conditions of a 500 kHz operating frequency, 6.5 V input voltage, and 0.75 V output voltage, the overshoot voltage is reduced by more than 17% across the entire operating range. When the load steps from 200 A to 20 A, the overshoot voltage is reduced to only 85 mV, a decrease of 27.97%, while the recovery time is 28.8 µs, a reduction of 37.66%. These results confirm that the auxiliary circuit can significantly improve the system’s transient response under large load steps, meeting the design requirements.

Walking control of humanoid robots based on improved footstep planner and whole-body coordination controller.

High-speed walking is fundamental for humanoid robots to quickly reach the work site in emergency scenarios. According to biological studies, the coordinated motion of the arms and waist can significantly enhance walking speed and stability in humans. However, existing humanoid robot walking control frameworks predominantly focus on leg control, often overlooking the utilization of upper body joints. In this paper, a novel walking control framework combining the improved footstep planner and the whole-body coordination controller is proposed, aiming to improve the humanoid robot's tracking accuracy of desired speeds and its dynamic walking capability. First, we analyze the issues in traditional footstep planners based on Linear Inverted Pendulum and Model Predictive Control (LIP-MPC). By reconstructing the footstep optimization problem during walking using the Center-of-Mass (CoM) position, we propose an improved footstep planner to enhance the control accuracy of the desired walking speed in humanoid robots. Next, based on biological research, we define a coordinated control strategy for the arms and waist during walking. Specifically, the waist increases the robot's step length, while the arms counteract disturbance momentum and maintain balance. Based on the aforementioned strategy, we design a whole-body coordination controller for the humanoid robot. This controller adopts a novel hierarchical design approach, in which the dynamics and motion controllers for the upper and lower body are modeled and managed separately. This helps avoid the issue of poor control performance caused by multi-task coupling in traditional whole-body controllers. Finally, we integrate these controllers into a novel walking control framework and validate it on the simulation prototype of the humanoid robot Dexbot. Simulation results show that the proposed framework significantly enhances the maximum walking capability of the humanoid robot, demonstrating its feasibility and effectiveness.

Research on Power Coordination Control Strategy of Microgrid Based on Reconfigurable Energy Storage

Research on Power Coordination Control Strategy of Microgrid Based on Reconfigurable Energy Storage

THE EFFECTIVENESS OF LAST PLANNER SYSTEM (LPS) IN INFRASTRUCTURE PROJECT MANAGEMENT

The Last Planner System (LPS) is a highly effective project management methodology widely used in infrastructure projects to enhance coordination, schedule adherence, and cost control. LPS focuses on the identification and resolution of constraints before activity execution, allowing teams to adapt quickly to unforeseen events and ensuring smoother workflow with fewer disruptions. This approach emphasizes collaborative planning, where all stakeholders are actively involved in the planning and decision-making process, promoting communication and improving the overall project execution. Additionally, integrating LPS with other tools, such as Building Information Modeling (BIM), provides further optimization, creating synergy between the methodologies to reduce waste and foster continuous improvement in the construction process. Studies across various infrastructure projects, such as the Pan-American Games facilities, highways, bridges, and dam projects, demonstrate the adaptability and positive impact of LPS in different contexts. Evidence shows that LPS not only resolves common issues like delays and excessive costs but also contributes to enhanced quality and better collaboration among project participants. The methodology’s collaborative nature allows for more effective planning, leading to organized and efficient workflows, and ensuring projects are completed on time and within the specified budget. By focusing on resolving constraints early and promoting team involvement, LPS fosters a productive and organized environment essential for success in the construction sector. This approach plays a key role in delivering high-quality infrastructure projects while maintaining cost-effectiveness and timely completion.

Deep Learning for Chromatic Optimization in Dual‐Color Mini‐LEDs for Aircraft Displays

AbstractGaN‐based miniaturized light‐emitting diodes (mini‐LEDs) have emerged as highly promising light sources for high‐performance aircraft cockpit displays. Among these diodes, vertically stacked blue‒green dual‐color mini‐LEDs are fabricated and show excellent color‐tunable properties. When packaged with K2SiF6:Mn4+, an impressive color gamut area ratio of 113.63% NTSC is demonstrated. However, vertical optical crosstalk originates from the photoluminescence (PL) effect of the green epitaxial layer when the blue mini‐LED is powered on, making precise chromatic characteristics difficult to obtain. To address this problem, a deep neural network (DNN) is proposed, which combines forward modeling and inverse design in a tandem architecture. This DNN supports a current modulation scheme that enables precise control of chromaticity coordinates, achieving a Δu′v′ of 0.003. These advancements in materials and device strategies pave the way for developing low color difference, high‐resolution display systems for aircraft cockpits.

Enhancing Voltage Stability of a Microgrid in the Presence of PV Plants Using Storage System

Due to the nearly inertia-free nature of the voltage source converter (VSC) based microgrid (MG), any fluctuations in the generation profile have an extremely detrimental effect on the voltage profile. A load imbalance at the point of common coupling (PCC) exacerbates the issue even further. Energy storage systems are critical components that ensure stability and dependability in microgrids with a significant proportion of renewable energy sources (RES). Coordination control between the PV (photo voltaic) and the BESS is necessary for power balance. This article describes a corrective voltage control (CVC) scheme for microgrid voltage regulation. An active and reactive power control strategy is suggested to reduce voltage fluctuations and thus mitigate the adverse effects of an unbalanced load. Incorporated battery energy storage devices will undergo dynamic charging during off-peak hours to minimize voltage dropouts and discharge during peak hours to prevent voltage spikes while regulating the PV inverter output's rapid fluctuations to a predetermined value. The outcomes validate the viability of the control schemes and Ess's integration into the microgrid.