Tracking Ability Research Articles

An adaptive online monitoring system using NFSOGI-PLL for three-phase voltage unbalance in grids

The extensive utilization of unbalanced and nonlinear loads has significantly impacted power quality in modern grids. Among various metrics, the three-phase voltage unbalance factor (TPVUF) stands out as a crucial indicator. To mitigate the challenges posed by harmonics and DC components that interfere with accurate TPVUF measurements, this paper introduces the Notch Filter-based Second-Order Generalized Integrator Phase-Locked Loop (NFSOGI-PLL) for the first time and designs an adaptive online monitoring system for TPVUF based on NFSOGI-PLL. To validate its performance, the hardware design and rapid software development of the NFSOGI-PLL-based TPVUF online monitoring system are thoroughly implemented, and the system is tested under various conditions. The results indicate that the proposed system not only provides real-time performance and high accuracy, complying with the rigorous standards set by GB/T 15543-2008 and IEC 61000-4-27, but also demonstrates remarkable stability under diverse influences. These findings underscore the exceptional filtering and tracking abilities of the NFSOGI-PLL in power systems, as well as the accuracy and anti-interference capabilities of the NFSOGI-based TPVUF online monitoring system, which holds great potential for widespread application in power system control and research.

LIVS: a tightly coupled LiDAR, IMU, and camera-based SLAM system under scene degradation

In increasingly complex environments, single-sensor-based SLAM systems face scene degradation problems such as strong light, dynamic obstacle interference, and lack of structural features in the environment, which severely constrain the localization accuracy and mapping effectiveness of SLAM systems. To address this problem, this paper proposes a tightly coupled laser-IMU-visual SLAM system (LIVS) based on factor graph optimization. LIVS consists of two subsystems: the laser inertial system (LIS) and the visual inertial system (VIS). The pose estimation of the LIS can provide an initialization for the VIS; LiDAR suffers scene degradation in environments lacking structural features, while the VIS provides better constraints for Lidar in this environment. Firstly, a method of selecting keyframes based on ORB features and the relative motion of the mobile robot is proposed as a means of improving the positioning accuracy and tracking ability of the system in the case of strenuous motion, and a strategy of local sliding window optimization is adopted to effectively improve the real-time performance and robustness of the system. Meanwhile, in order to further improve the global map consistency and positioning accuracy, a hybrid closed-loop detection method based on laser and vision is proposed, which utilizes the geometrical features of laser and the image features of vision to accomplish the hybrid closed-loop detection. Secondly, the laser inertia factor, IMU pre-integration factor, vision inertia factor, and closed-loop factor are globally optimized in a factor map framework to achieve accurate estimation of the robot pose. Finally, this paper presents experimental evaluations on both public and homemade datasets and compares the performance of the proposed algorithm with that of other algorithms. Experimental results show that the algorithm in this paper exhibits better performance in both localization accuracy and mapping effectiveness.

ADP-based adaptive control of ship course tracking system with prescribed performance

In this paper, an adaptive dynamic programing (ADP)-based adaptive control problem is studied for the ship course tracking system with prescribed performance. Firstly, the complex sea conditions will bring difficulty to ship course tracking when unmanned ship sailing on sea. In order to overcome this difficulty, a prescribed performance feedforward term is designed in the controller to improve the course tracking ability of ship. Secondly, by defining a cost function, an ADP technology is exploited to achieve an optimal control of ship course tracking system. Finally, the stability of the closed loop system is turned out by Lyapunov stability theory and all signals are uniformly ultimately bounded (UUB). Simulation results validate the effectiveness of the proposed method.

A heavy-duty tracked vehicle model with a reduced feasible domain for motion tracking control considering dynamic characters of hybrid powertrain

Motion tracking control is an essential part of heavy-duty unmanned tracked vehicles to realize autonomous mobility, which adjusts the vehicle motion in real-time by controlling the driving torques. Achieving accurate motion tracking strongly depends on the use of a precise vehicle dynamic model. To support the motion tracking ability, a vehicle dynamic model with a reduced feasible domain is proposed for heavy-duty unmanned tracked vehicles. Firstly, a vehicle dynamic model is established based on the vehicle kinematics and dynamics. Building upon the established vehicle dynamic model, a graph neural network (GNN) is employed to reduce the feasible domain of the vehicle dynamic model, specifically focusing on the limitation of the powertrain. The powertrain components and their interconnections are abstracted into a graph, which is analyzed to study the interactions between the components using the GNN. Finally, the proposed vehicle dynamic model with a reduced feasible domain is verified through actual heavy-duty tracked vehicle experiments in various cases. Compared with the back propagation neural network, the evaluation error of the driving torque decreased by 25.86%. Results show that the proposed vehicle dynamic model with a reduced feasible domain is closer to the performance of the actual heavy-duty tracked vehicle and their powertrain. And the vehicle dynamic model accurately reduces the solution time of the motion tracking control, resulting in improved accuracy and efficiency of the motion tracking control.

Enhanced path tracking control of hydraulic support pushing mechanism via adaptive sliding mode technique in coal mine backfill operations

The hydraulic support pushing mechanism is the primary equipment utilized in coal mine backfill operations, playing a crucial role in enhancing filling efficiency, ensuring a stable filling body, and managing gob safety. This paper focuses on analyzing the dynamic model and the interrelationship of the hydraulic cylinder, which serves as the power source for the pushing mechanism. To address the intricate coupling effects arising from the hydraulic cylinders and the displacement-force induced by the shared pump, this study employs feedforward compensation for decoupling analysis. Additionally, this article introduces an adaptive sliding mode approach law and an adaptive synovial controller to combat issues such as buffeting and interference. The simulation results demonstrate that the sliding mode reaching law proposed in this paper can achieve a stable state in approximately 3 seconds, which is significantly better than other methods. Combining the experimental equipment information from a mining area in Hebei Province with Amesim-Simulink simulation results, it is evident that the adaptive sliding mode controller exhibits an error range between approximately 1.33E-4 and 1.5E-4 during the stable phase. This performance surpasses traditional PI and fuzzy PID controllers in terms of path tracking ability, effectively enabling precise control of the filling support pushing mechanism.

Discovery of a novel near-infrared triphenylamine-dicyanoisophorone fluorescent probe with a large Stokes shift for long-term tracking of lysosomes in live cells

Fluorescent probes are powerful tools for real-time tracking of lysosomal movements and spatial distribution, which appears to be essential for understanding the biology of lysosomes. However, the commercially used lysosomal trackers exhibited some limitations, such as narrow Stokes shifts, poor photostability, and green to red instead of near-infrared (NIR) emission. In this study, we have developed a fluorescent probe by incorporating the triphenylamine fragment into the dicyanoisophorone fluorophore. This probe displayed impressive NIR emission (centered at 755 nm) and remarkable Stokes shift (235 nm), which was then demonstrated to be insensitive to lysosomal pH as well as viscosity, and expressed long-term lysosomal tracking ability with little cytotoxicity in live cells. Altogether, this study provided an ideal NIR fluorescent probe for lysosomal tracking.

Transpulmonary cardiac output with room temperature saline is accurate and tracks directional changes in anesthetized dogs.

To assess the performance of transpulmonary thermodilution (TPTD) using room-temperature saline (CORT) and waveform-derived continuous CO (CCO) compared with TPTD using iced saline (COICED) as the indicator for measurements of CO in isoflurane-anesthetized dogs. 8 Beagles aged 1 to 2 years (7.4 to 11.2 kg) were enrolled in this experimental study from March 21 to 31, 2023. Dogs were anesthetized with 0.01 mg/kg acepromazine, 5 to 6 mg/kg propofol, and isoflurane and were mechanically ventilated. Dogs were instrumented with a central venous catheter and a femoral arterial catheter equipped with a thermistor. The COICED, CORT, and pulse wave-derived CCO values were obtained at baseline, during infusions of phenylephrine and norepinephrine, and during blood withdrawal and replacement. Data were analyzed with a mixed effect model, Bland-Altman plots, and concordance. Percent error was calculated. P < .05 was used for significance. Data were collected from 8 dogs. Significant effects of time and the interaction of time and method were found. Bland-Altman plots showed negligible bias with limits of agreement between -0.35 and 0.25 L/min for CORT versus COICED and -1.23 and 1.15 L/min for CCO versus COICED. Percent errors were 17.7% and 66.6%, respectively. In the 4-quadrant plots, the concordance rate was 95% and 68% for measurements obtained with CORT and for CCO, respectively. Transpulmonary thermodilution using room temperature saline was accurate and able to track changes in CO. Continuous CO had a large percent error and low tracking ability. Transpulmonary thermodilution using room temperature saline is reliable for monitoring CO and obviates the need for iced preparations in clinical scenarios.

A preference adjustable capacity configuration optimization method for hydrogen-containing integrated energy system considering dynamic energy efficiency improvement and load fast tracking

The new hydrogen-containing integrated energy system proposed in this paper has complementary coupling of multiple energy forms such as electricity, gas, cold, heat, and hydrogen. For the same type of load demand, equipment with different energy input forms can be dispatched for joint supply. However, different equipment differ in dynamic response speed and energy utilization efficiency, and the reasonable configuration of equipment capacity will directly affect the overall dynamic characteristics and energy efficiency level of the system. Therefore, this paper first proposes an evaluation index that can comprehensively characterize the dynamic energy efficiency and load tracking ability of energy equipment. In addition, a preference adjustable capacity configuration optimization method based on utopian point tracking is proposed with the two optimization objectives of this indicator and the system's equivalent annualized investment cost, and the solution complexity is reduced through segmented linearization of the objective. Simulations presented here show that the capacity configuration optimization method proposed in this paper has a positive effect on improving the dynamic energy efficiency and load tracking ability of the new hydrogen-containing integrated energy system, and can also meet the preference setting needs of different investment entities for capacity configuration optimization goals.

Evaluation of the Noninvasive Estimated Continuous Cardiac Output System for Pediatric Patients: A Prospective Observational Study.

The estimated continuous cardiac output (esCCO) system is a hemodynamic monitor that uses electrocardiograms and pulse oximeter waves to noninvasively estimate cardiac output. The coefficients for esCCO measurement have been established for adult patients, but the appropriate coefficients for pediatric patients are unclear. Therefore, this study determined esCCO coefficients for pediatric patients and validated the accuracy and tracking ability of a modified esCCO system. An initial study compared cardiac output measurements using transthoracic echocardiography and esCCO in 60 pediatric patients aged <15 years who underwent elective noncardiac surgery. Consequently, the coefficients for the esCCO measurements were redefined for pediatric patients. The main study compared cardiac output measurements between transthoracic echocardiography and modified esCCO in 80 pediatric patients. Measurements were performed pre- and postoperatively, and the accuracy and trending ability of the cardiac output measurements were evaluated using Bland-Altman analysis and a polar plot. The correlation coefficients between the modified esCCO and transthoracic echocardiography were 0.96 and 0.98 in the pre- and postoperative measurements, respectively. In Bland-Altman analysis, the bias (standard deviation [SD]), 95% limits of agreement, and percentage error were 0.03 (0.28), -0.53 to 0.60, and 18% in the preoperative measurement, and -0.04 (0.19), -0.42 to 0.35, and 15% in the postoperative measurement, respectively. The polar plot showed that the cardiac output changes were well tracked, with an angular bias (SD) of 2.9° (6.0°) and radial 95% limits of agreement ranging from -9.2° to 14.9°. Cardiac output measurement by esCCO with modified coefficients for pediatric patients showed high accuracy and tracking ability compared with cardiac output measurement by transthoracic echocardiography. This noninvasive cardiac output measurement could benefit perioperative hemodynamic monitoring in children.

Multi-scale prediction of remaining useful life of lithium-ion batteries based on variational mode decomposition and integrated machine learning

Accurate and reliable prediction of the remaining useful life (RUL) of lithium-ion batteries (LIB) is very important for the safety of power systems. To solve the nonlinear and time-varying problems of LIB aging trajectories, an RUL prediction method based on variational mode decomposition (VMD) and integrated machine learning is proposed. First, the VMD algorithm is used to mine the internal information in LIB data to capture the long-term downward trend and capacity regeneration hidden in the capacity degradation. After that, the Elman neural network optimized by the gray wolf algorithm and Gaussian process regression were used to model and predict the intrinsic mode function (IMF) and residual sequence respectively. Next, the predicted IMF component and residual sequence are fused to obtain the LIB aging trajectory, and the capacity prediction error is corrected through the bidirectional long short-term memory network. Finally, the LIB data set is used as the test data of the algorithm. The results show that the proposed method has better robustness and nonlinear tracking ability, the mean absolute error is controlled within 1.5 %, and the RUL prediction error is within 3 cycles.

A Robust Filtered-x Least Mean Square Algorithm with Adjustable Parameters for Active Impulsive Noise Control

In active noise control (ANC) systems, the traditional filtered-x least mean square (FxLMS) algorithm has poor control effect on impulsive noise. To overcome this drawback, a robust cost function was designed in this paper by embedding the cost function of the FxLMS algorithm into the framework of hyperbolic tangent function; this paper thus proposes a robust filtered-x least hyperbolic tangent (FxLHT) algorithm in ANC systems. Moreover, the value of λ in the FxLHT algorithm greatly affects the robustness and convergence performance of the algorithm. Therefore, a variable λ-parameter was proposed to enhance the performance of the FxLHT algorithm. Simulation results show that in the active control of impulsive noise, compared with the FxLMS algorithm and other robust ANC algorithms, the proposed FxLHT algorithm and variable λ-parameter FxLHT algorithm not only exhibit good robustness and noise reduction performance but also have a better tracking ability.

Optimization and improvement method for complementary power generation capacity of wind solar storage in distributed photovoltaic power stations

Abstract With the increasing energy demand, distributed photovoltaic power generation and wind energy are used as new energy sources for sustainable development. To solve this problem, this paper optimizes and improves the distributed photovoltaic power station. This project will fully consider the complementary relationship between photovoltaic, wind and energy storage, and optimize the charging and discharging strategy of energy storage batteries. An optimal scheduling method based on fuzzy C-mean clustering is proposed to improve the power supply reliability and energy utilization of distributed photovoltaic power generation systems. The test results show that the output of the wind turbine and solar cell designed in this paper is quite high, and has good tracking ability. The research results of this project will provide an effective way to efficiently utilize wind energy and wind energy resources in distributed photovoltaic power stations.

Endoscopic endonasal optic nerve decompression in children younger than 2 years old with congenital optic canal stenosis: illustrative cases.

Congenital optic canal stenosis causing compressive optic neuropathy is a rare disorder that presents unique diagnostic and treatment challenges. Endoscopic endonasal optic nerve decompression (EOND) has been described for optic nerve compression in adults and adolescents but has never been reported for young children without pneumatized sphenoid sinuses. The authors describe preoperative and intraoperative considerations for three patients younger than 2 years of age with congenital optic canal stenosis due to genetically confirmed osteopetrosis or chondrodysplasia. Serial ophthalmological examinations, with a particular focus on object tracking ability, fundoscopic examination, and visual evoked potential trends in preverbal children, are important for detecting progressive optic neuropathy. The lack of pneumatization of the sphenoid sinus presents unique challenges and requires the surgical creation of a sphenoid sinus with the use of neuronavigation to determine the limits of bony exposure given the lack of easily identifiable anatomical landmarks such as the opticocarotid recess. There were no perioperative complications. EOND for congenital optic canal stenosis is safe and technically feasible even given the lack of pneumatization of the sphenoid sinus in young patients. The key operative step is surgically creating the sphenoid sinus through careful bony removal with the aid of neuronavigation. https://thejns.org/doi/10.3171/CASE23559.

Head tracking using an optical soft tactile sensing surface.

This research proposes a sensor for tracking the motion of a human head via optical tactile sensing. It implements the use of a fibrescope a non-metal alternative to a webcam. Previous works have included robotics grippers to mimic the sensory features of human skin, that used monochrome cameras and depth cameras. Tactile sensing has shown advantages in feedback-based interactions between robots and their environment. The methodology in this paper is utilised to track motion of objects in physical contact with these sensors to replace external camera based motion capture systems. Our immediate application is related to detection of human head motion during radiotherapy procedures. The motion was analysed in two degrees of freedom, respective to the tactile sensor (translational in z-axis, and rotational around y-axis), to produce repeatable and accurate results. The movements were stimulated by a robot arm, which also provided ground truth values from its end-effector. The fibrescope was implemented to ensure the device's compatibility with electromagnetic waves. The cameras and the ground truth values were time synchronised using robotics operating systems tools. Image processing methods were compared between grayscale and binary image sequences, followed by motion tracking estimation using deterministic approaches. These included Lukas-Kanade Optical Flow and Simple Blob Detection, by OpenCV. The results showed that the grayscale image processing along with the Lukas-Kanade algorithm for motion tracking can produce better tracking abilities, although further exploration to improve the accuracy is still required.

Advanced Servo Control and AI Integration in 3-DoF Platforms for Enhanced Simulation Interactivity

This paper proposes a new approach to enhance the realism and interactivity of shooting simulation systems by integrating a three-degree–of–freedom (3-DoF) platform with sensory and interactive elements, as well as digital content. The system employs visual effects computers and servo controls, utilizing network packet messages for communication based on different scene definitions. When the control handle sends commands, the visual effects computer transmits control parameters to the image generator. Additionally, AI-controlled aircrafts act as enemy planes, autonomously determining flight paths, tracking targets, and engaging in combat, thereby enhancing realism in interactive mechanisms. An iterative learning control (ILC) is designed to provide the platform with good dynamic response, load capacity, and tracking ability when operated by a manual control handle. The core control uses a TMS320F28377D digital signal processor from Texas Instruments, integrated with visual effects computers for three-axis control, controller computation, finite state machines, and network communication operations. Experimental results demonstrate the feasibility and effectiveness of the developed three-axis shooting platform, achieving immersion and coordination with AI enemy aircrafts.

Tracking Ability of iShares Country ETFs During Covid–19 Pandemic

Tracking Ability of iShares Country ETFs During Covid–19 Pandemic

Design of Novel STASOSM Controller for FOC Control of Dual Star Induction Motor Drives

In this paper, a Novel Super-Twisting Algorithm combined with Improved Second - Order Sliding Mode (NSTASOSM) for the Field-Oriented Control (FOC) of high performance SPIM drives is proposed. This structure, on the one hand, effectively solves the weaknesses of traditional backstepping control (BS) and sliding mode (SM) control that are the dependent on the change of parameters, load disturbance and the phenomenon of chattering, on the other hand, increases the convergence speed and the reference tracking ability, enhance the robust and stably of drive systems even when working in conditions of uncertain parameter and load disturbances, eliminates the chattering phenomenon. The obtained results by simulation using the Matlab/ Simulink tool verified the performance of this proposed control structure.

On Tracking and Antidisturbance Ability of PID Controllers

On Tracking and Antidisturbance Ability of PID Controllers

Echogenic Gold Nanorod Incorporated Hybrid Poly(2-oxazoline) Nanocapsules for Real-Time Ultrasound/Fluorescent Imaging and Targeted Cancer Theranostics.

In recent years, various nanocarrier systems have been explored to enhance the targeting of cancer cells by improving the ligand-receptor interactions between the nanocarrier and cancer cells for selective cancer cell imaging and targeted delivery of anticancer drugs. Herein, we report multifunctional hydrogen-bonded multilayer nanocapsules functionalized with both folic acid-derived quantum dots (FAQDs) and gold nanorods (AuNRs) for targeted cancer therapy and cancer cell imaging using fluorescence microscopy and medical-range ultrasound imaging systems. The encapsulation efficiency of nanocapsules was found to be 49% for 5-fluorouracil (5-FU). The release percentage reached a plateau at 37% after 1 h at pH 7.4 and increased to 57% after 3 h when the release pH was decreased to pH 5.5 (i.e., the pH of the tumor environment). Under ultrasound irradiation, the release was significantly accelerated, with a total release of 52% and 68% after only 6 min at pH 7.4 and pH 5.5, respectively. While the sonoporation process plays an important role in anticancer activity experiments under ultrasound exposure by generating temporary pores, the targeting ability of FAQDs brings the capsules closer to the cell membrane and improves the cellular uptake of the released drug, thereby increasing local drug concentration. In vitro cytotoxicity experiments with HCT-116 and HEp-2 cells demonstrated anticancer activities of 96% and 98%, respectively. The nanocapsules showed enhanced ultrasound scattering signal intensity and bright spots under ultrasound exposure, most likely caused by high scattering ability and internal reflections of preloaded AuNRs in the interior structure of the nanocapsules. Hence, the demonstrated nanocapsule system not only has the potential to be used as an integrated system for early- stage detection and treatment of cancer cells but also has the ability for live tracking and imaging of cancer cells while undergoing treatment with chemotherapy and radiation therapy.

Development of a manganese complex hyaluronic acid hydrogel encapsulating stimuli-responsive Gambogic acid nanoparticles for targeted Intratumoral delivery

Gambogic acid is a natural compound with anticancer properties and is effective for many tumors. But its low water solubility and dose-dependent side effects limit its clinical application. This study aims to develop a novel drug delivery system for intratumoral delivery of gambogic acid. In our experimental study, we propose a new method for encapsulating gambogic acid nanoparticles using a manganese composite hyaluronic acid hydrogel as a carrier, designed for targeted drug delivery to tumors. The hydrogel delivery system is synthesized through the coordination of hyaluronic acid-dopamine (HA-DOPA) and manganese ions. The incorporation of manganese ions serves three purposes:1.To form cross-linked hydrogels, thereby improving the mechanical properties of HA-DOPA.2.To monitor the retention of hydrogels in vivo in real-time using magnetic resonance imaging (MRI).3.To activate the body's immune response. The experimental results show that the designed hydrogel has good biosafety, in vivo sustained release effect and imaging tracking ability. In the mouse CT26 model, the hydrogel drug-loaded group can better inhibit tumor growth. Further immunological analysis shows that the drug-loaded hydrogel group can stimulate the body's immune response, thereby better achieving anti-tumor effects. These findings indicate the potential of the developed manganese composite hyaluronic acid hydrogel as an effective and safe platform for intratumoral drug delivery. The amalgamation of biocompatibility, controlled drug release, and imaging prowess positions this system as a promising candidate for tumor treatment.