Robust <i>H</i>_∞Observer-Based Tracking Control for the Photovoltaic Pumping System

In this paper, we propose a H∞ robust observer-based control DC motor based on a photovoltaic pumping system. Maximum power point tracking is achieved via an algorithm using Perturb and Observe method, with array voltage and current being used to generate the reference voltage which should be the PV panel’s operating voltage to get maximum available power. A Takagi-Sugeno (T-S) observer has been proposed and designed with non-measurable premise variables and the conditions of stability are given in terms of Linear Matrix Inequality (LMI). The simulation results show the effectiveness and robustness of the proposed method.

Assessment of Left Ventricular Function after Transcatheter Aortic Valve Implantation in Sever Aortic Stenosis: A Speckle Tracking Imaging Study

Background: Long standing aortic stenosis leads to elevated left ventricular (LV) pressure and as a result LV hypertrophy and myocardial fibrosis shall increase. The left ventricular ejection fraction (EF) usually remains adequately-preserved until advanced and late stages of aortic stenosis. But the preserved muscle of the LV is only limited to a portion of the entire myocardium. Speckle tracking echocardiography has proved its superiority to the standard two-dimensional echocardiography method in the detection of Left Ventricular (LV) function. Global Longitudinal strain (GLS) is considered as the most robust myocardial strain component.?Objective: The aim of the study is to assess the early course of left ventricular reverse remodelling after Transcutaneous Aortic Valve Implantation (TAVI) in patients with symptomatic severe aortic valve stenosis.?Methods: 50 patients with severe symptomatic valvular aortic stenosis undergoing TAVI as decided by the heart team after comprehensive discussion.?Standard transthoracic echocardiography including Doppler analysis was performed. 2D speckle-tracking strain assessment of Global radial, circumferential and longitudinal strain at parasternal mid-ventricular short-axis view (at the level of papillary muscle) and from the apical long-axis, two-chamber and four-chamber views with a frame rate between 40 and 80 frames per second. Tracing of endocardial borders was done. Patients with significant coronary artery disease were fully revascularized by percutaneous coronary intervention prior to the study and the procedure. Results: 23 (46%) patients were males, while 27 (54%) were females. The patients’ stratification according to comorbidities/associated risk factors revealed that 54% of the patients had DM, 86% were hypertensive, 38% had chronic kidney disease (CKD), and 32% had a previous percutaneous coronary intervention (PCI).?The mean age for our study participants ranged?from 60 to 92 years (Mean ± SD = 76.60 ± 5.96). Left ventricular diastolic diameter (LVDd) was 44.24?±?2.8?mm before TAVI that became 45.5?±?2.6?mm after TAVI, and ejection fraction (EF) increased from 52.82?±?6.3?before TAVI to 56.70?±?5.4?after TAVI, both with highly significant difference (P P value less than 0.001. Global circumferential strain (GCS) also improved significantly from -20.14?±?1.8 before TAVI to -21.72?±?1.7 after TAVI with a P value less than 0.001. Global radial strain (GRS) also increased significantly from 37.38?±?8 before TAVI to 41.68?± 6.3 after TAVI with a P value less than 0.001. Conclusion: TAVI is effective in improving left ventricular function presented not only by ejection fraction (EF%), but also in global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS).

QPSK DS-CDMA System over Rayleigh Channel with a Randomly-Varying Frequency Narrow-Band Interference: Frequency Tracking Analysis

This paper analyses frequency tracking characteristics of a complex-coefficient adaptive infinite-impulse response (IIR) notch filter used for suppression of narrow-band interference (NBI) with a randomly-varying frequency in a quadriphase shift keying (QPSK) modulated direct-sequence code-division multiple-access (DS-CDMA) communication system. The QPSK DS-CDMA signals are transmitted over a frequency non-selective Rayleigh fading channel. The analysis is based on a first-order real-coefficient difference equation with respect to steady-state instantaneous frequency tracking error from which a closed-form expression that relates frequency tracking mean square error (MSE) with number of DS-CDMA active users and NBI power is obtained. Closed-form expressions for optimum notch bandwidth coefficient and step size constant that minimize the frequency tracking MSE are also derived. Computer simulations are included to substantiate the accuracy of the analyses.

Parasitic Effects on the Performance of DC-DC SEPIC in Photovoltaic Maximum Power Point Tracking Applications

This paper presents an analysis of the effect of parasitic resistances on the performance of DC-DC Single Ended Pri- mary Inductor Converter (SEPIC) in photovoltaic maximum power point tracking (MPPT) applications. The energy storage elements incorporated in the SEPIC converter possess parasitic resistances. Although ideal components significantly simplifies model development, but neglecting the parasitic effects in models may sometimes lead to failure in predicting first scale stability and actual performance. Therefore, the effects of parasitics have been taken into consideration for improving the model accuracy, stability, robustness and dynamic performance analysis of the converter. Detail mathematical model of SEPIC converter including inductive parasitic has been developed. The performance of the converter in tracking MPP at different irradiance levels has been analyzed for variation in parasitic resistance. The converter efficiency has been found above 83% for insolation level of 600 W/m2 when the parasitic resistance in the energy storage element has been ignored. However, as the parasitic resistance of both of the inductor has increased to 1 ohm, a fraction of the power managed by the converter has dissipated;as a result the efficiency of the converter has reduced to 78% for the same insolation profile. Although the increasing value of the parasitic has assisted the converter to converge quickly to reach the maximum power point. Furthermore it has also been observed that the peak to peak load current ripple is reduced. The obtained simulation results have validated the competent of the MPPT converter model.

Point Selection for Triangular 2-D Mesh Design Using Adaptive Forward Tracking Algorithm

Two-dimensional mesh-based motion tracking preserves neighboring relations (through connectivity of the mesh) and also allows warping transformations between pairs of frames;thus, it effectively eliminates blocking artifacts that are common in motion compensation by block matching. However, available uniform 2-D mesh model enforces connec-tivity everywhere within a frame, which is clearly not suitable across occlusion boundaries. To overcome this limitation, BTBC (background to be covered) detection and MF (model failure) detection algorithms are being used. In this algorithm, connectivity of the mesh elements (patches) across covered and uncovered region boundaries are broken. This is achieved by allowing no node points within the background to be covered and refining the mesh structure within the model failure region at each frame. We modify the occlusion-adaptive, content-based mesh design and forward tracking algorithm used by Yucel Altunbasak for selection of points for triangular 2-D mesh design. Then, we propose a new triangulation procedure for mesh structure and also a new algorithm to justify connectivity of mesh structure after motion vector estimation of the mesh points. The modified content-based mesh is adaptive which eliminates the necessity of transmission of all node locations at each frame.

Intravascular ultrasound-guided “extended” reverse controlled antegrade and retrograde subintimal tracking technique using a cutting balloon for recanalizing chronic coronary total occlusion with a side branch

Percutaneous coronary intervention (PCI) of chronic total occlusion (CTO) represents the most technically challenging procedure in contemporary interventional cardiology.[1] Blunt lesions and presence of proximal side branch are considered to be strong predictors of reduced technical success.[ 2,3] For such lesions, the antegrade approach may not be feasible or desirable, and the retrograde approach can be used as the initial crossing strategy. However, when treating the blunt CTO with a large side branch proximal to the occlusion, the side branch might be occluded after stent implantation if the retrograde guidewire passed the occluded segment through the subintimal space and re-entered into the true lumen at the opposite side of the side branch.[4] We reported a useful method to solve the above issue which utilizes intravascular ultrasound (IVUS) to guide “extended” reverse controlled antegrade and retrograde subintimal tracking (CART) technique with a cutting balloon.

Joint resource allocation scheme for target tracking in distributed MIMO radar systems

A joint resource allocation scheme concerned with the sensor subset,power and bandwidth for range-only target tracking in multiple-input multiple-output(MIMO)radar systems is proposed.By selecting an optimal subset of sensors with the predetermined size and implementing the power allocation and bandwidth strategies among them,this algorithm can help achieving a better performance within the same resource constraints.Firstly,the Bayesian Cramer-Rao bound(BCRB)is derived from it.Secondly,a criterion for minimizing the BCRB at the target location among all targets tracking in a certain range is derived.Thirdly,the optimization problem involved with three variable vectors is formulated,which can be simplified by deriving the relationship between the optimal power allocation vector and the bandwidth allocation vector.Then,the simplified optimization problem is solved by the cyclic minimization algorithm incorporated with the sequential parametric convex approximation(SPCA)algorithm.Finally,the validity of the proposed method is demonstrated with simulation results.

An Integrated Face Tracking and Facial Expression Recognition System

This article proposes a feature extraction method for an integrated face tracking and facial expression recognition in real time video. The method proposed by Viola and Jones [1] is used to detect the face region in the first frame of the video. A rectangular bounding box is fitted over for the face region and the detected face is tracked in the successive frames using the cascaded Support vector machine (SVM) and cascaded Radial basis function neural network (RBFNN). The haar-like features are extracted from the detected face region and they are used to create a cascaded SVM and RBFNN classifiers. Each stage of the SVM classifier and RBFNN classifier rejects the non-face regions and pass the face regions to the next stage in the cascade thereby efficiently tracking the face. The performance of tracking is evaluated using one hour video data. The performance of the cascaded SVM is compared with the cascaded RBFNN. The experiment results show that the proposed cascaded SVM classifier method gives better performance over the RBFNN and also the methods described in the literature using single SVM classifier [2]. While the face is being tracked, features are extracted from the mouth region for expression recognition. The features are modelled using a multi-class SVM. The SVM finds an optimal hyperplane to distinguish different facial expressions with an accuracy of 96.0%.

Verification of Dosimetric and Positional Accuracy of Dynamic Tumor Tracking Intensity Modulated Radiation Therapy

Purpose: We performed both, dosimetric and positional accuracy verification of dynamic tumor tracking (DTT) intensity modulated radiation therapy (IMRT), with the Vero4DRT system using a moving phantom (QUASAR respiratory motion platform;QUASAR phantom) and system log files. Methods: The QUASAR phantom was placed on a treatment couch. Measurement of the point dose and dose distribution was performed for conventional IMRT, with the QUASAR phantom static and moving;for DTT IMRT, this was performed with the phantom moving for pyramid shaped, prostate, paranasal sinus, and pancreas targets. The QUASAR phantom was driven by a sinusoidal signal in the superior-inferior direction. Furthermore, predicted positional errors induced by the Vero4DRT system and mechanical positional errors of the gimbal head, were calculated using the system log files. Results and Conclusion: For DTT IMRT, the dose at the evaluation point was within 3% compared with the verification plan, and the dose distribution in the passing rates of γ was 97.9%, with the criteria of 3% dose and 3 mm distance to agreement. The position error calculated from the log files was within 2 mm, suggesting the feasibility of employing DTT IMRT with high accuracy using the Vero4DRT system.

Methods and Means for Small Dynamic Objects Recognition and Tracking

A literature analysis has shown that object search,recognition,and tracking systems are becoming increasingly popular.However,such systems do not achieve high practical results in analyzing small moving living objects ranging from 8 to 14 mm.This article examines methods and tools for recognizing and tracking the class of small moving objects,such as ants.To fulfill those aims,a customized You Only Look Once Ants Recognition(YOLO_AR)Convolutional Neural Network(CNN)has been trained to recognize Messor Structor ants in the laboratory using the LabelImg object marker tool.The proposed model is an extension of the You Only Look Once v4(Yolov4)512×512 model with an additional Self Regularized Non–Monotonic(Mish)activation function.Additionally,the scalable solution for continuous object recognizing and tracking was implemented.This solution is based on the OpenDatacam system,with extended Object Tracking modules that allow for tracking and counting objects that have crossed the custom boundary line.During the study,the methods of the alignment algorithm for finding the trajectory of moving objects were modified.I discovered that the Hungarian algorithm showed better results in tracking small objects than the K–D dimensional tree(k-d tree)matching algorithm used in OpenDataCam.Remarkably,such an algorithm showed better results with the implemented YOLO_AR model due to the lack of False Positives(FP).Therefore,I provided a new tracker module with a Hungarian matching algorithm verified on the Multiple Object Tracking(MOT)benchmark.Furthermore,additional customization parameters for object recognition and tracking results parsing and filtering were added,like boundary angle threshold(BAT)and past frames trajectory prediction(PFTP).Experimental tests confirmed the results of the study on a mobile device.During the experiment,parameters such as the quality of recognition and tracking of moving objects,the PFTP and BAT,and the configuration parameters of the neural network and boundary line model were analyzed.The results showed an increased tracking accuracy with the proposed methods by 50%.The study results confirmed the relevance of the topic and the effectiveness of the implemented methods and tools.

Value of two-dimensional speckle tracking imaging in quantitative assessment of left ventricular function in patients with OSAS

Objective: To research the clinical application of two-dimensional speckle tracking imaging (2D-STI) in quantitative assessment of left ventricular function in patients with obstructive sleep apnea-hypopnea syndrome (OSAS). Method: From July 2016 to December 2018, 86 patients with OSAS were selected as OSAS group. According to sleep apnea hypopnea index (AHI), they were divided into mild OSAS group (24 cases), moderate OSAS group (29 cases) and severe OSAS group (33 cases). Another 50 healthy volunteers who underwent physical examination in our hospital during the same period were selected as the control group. The left ventricular function of all patients was quantitatively assessed by 2D-STI. The left ventricular function of all patients was quantitatively assessed by 2D-STI. The results of routine echocardiography and left ventricular global strain parameters of the OSAS group, the control group and the OSAS patients with different severity were compared and analyzed. Result: There were no significant differences in the levels of left ventricular ejection fraction (LVEF), left ventricular end diastolic diameter (LVEDd), left ventricular end systolic diameter (LVESd) between the two groups and OSAS patients with different severity (P>0.05). The levels of IVST, LVPW and LVMI in the OSAS group were significantly higher than those in the control group, the levels of end-diastolic interventricular septal thickness (IVS), left ventricular posterior wall thickness (LVPW), left ventricular mass index (LVMI) in the severe OSAS group were significantly higher than those in the mild and moderate OSAS group, and the levels of IVST, LVPW and LVMI in the moderate OSAS group were significantly higher than those in the mild OSAS group, there were significant differences between groups (P<0.05). The levels of GLS, GRS and GCS in the OSAS group were significantly lower than those in the control group (P<0.05). GLS, GRS and GCS levels in the severe OSAS group were significantly lower than those in the mild OSAS group and the moderate OSAS group, while the levels of global longitudinal strain (GLS), global radial strain (GRS) and global circumferential strain (GCS) in the moderate OSAS group were significantly lower than those in the mild OSAS group (P<0.05). Conclusion: The left ventricular systolic function of OSAS patients is obviously impaired. Left ventricular function in OSAS patients can be assessed timely and accurately by two-dimensional speckle tracking imaging.

Magnetic resonance diffusion tensor imaging and fibertracking diffusion tensor tractography in the management of spinal astrocytomas

Some specially imaging of magnetic resonance imaging,the diffusion-weighted imaging(DWI),the diffusion tensor imaging and fractional anisotropy(FA),are useful to described,detect,and map the extent of spinal cord lesions.FA measurements may are used to predicting the outcome of patients who have spinal cord lesions.Fiber tracking enable to visualizing the integrity of white matter tracts surrounding some lesions,and this information could be used to formulating a differential diagnosis and planning biopsies or resection.In this article,we will describe the current uses for DWI and fiber tracking and speculate on others in which we believe these techniques will be useful in the future.

Tracking a Time-Varying Number of Targets with Radio-Frequency Tomography

Radio-frequency(RF) tomography is an emerging technology which derives targets location information by analyzing the changes of received signal strength(RSS) in wireless links. This paper presents and evaluates a novel RF tomography system which is capable of detecting and tracking a time-varying number of targets in a cluttered indoor environment. The system incorporates an observation model based on RSS attenuation histogram and a multi-target tracking-by-detection filtering approach based on probability hypothesis density(PHD) filter. In addition, the sequential Monte Carlo method is applied to implement the multi-target filtering. To evaluate the tracking system, the experiments involving up to 3 targets were performed within an obstructed indoor area of 70 m2. The experimental results indicate that the proposed tracking system is capable of tracking a time-varying number of targets.

Evaluation of Left Ventricular Function after Percutaneous Recanalization of Chronic Coronary Occlusions: The Role of Two-Dimensional Speckle Tracking Echocardiography

Background: The recanalization of a chronic total coronary occlusion is the possible way to improve left ventricular (LV) function through the recovery of hibernating myocardium. Aim: The aim of this study is to evaluate the role of 2D speckle tracking in evaluation of the left ventricular (LV) systolic function in chronic total occlusion (CTO) patients before and at 1 day as well as 3 months after percutaneous coronary intervention (PCI). Patients and Methods: A prospective observational study included 40 patients diagnosed with coronary angiography to have a chronic total occlusion. Percutaneous coronary revascularization was performed according to standard practices with the femoral approach. Conventional 2D echocardiography was used to assess LV functions and wall motion abnormalities scoring index (WMAI). Using speckle-tracking echocardiography was to measure global longitudinal strain (GLS) and. Follow-up of patients was done at day 1 and 3 months later after PCI. Results: Forty patients were included in this study, with a mean age of 58.55 ± 7.98 years. GLS and WMAI difference at baseline and follow-up shows a positive correlation with left ventricular ejection fraction (LVEF) changes at baseline and follow-up (p Conclusion: The results of this study provide evidence to support the clinical use of 2D-STE to monitor the early changes of LV function. In patients undergoing CTO revascularization, change in GLS was more sensitive predictors for LV function improvement at 3-month follow-up.

An Analysis on Position Estimation, Drifting and Accumulated Error Accuracy during 3D Tracking in Electronic Handheld Devices

This work focuses on a brief discussion of new concepts of using smartphone sensors for 3D painting in virtual or augmented reality. Motivation of this research comes from the idea of using different types of sensors which exist in our smartphones such as accelerometer, gyroscope, magnetometer etc. to track the position for painting in virtual reality, like Google Tilt Brush, but cost effectively. Research studies till date on estimating position and localization and tracking have been thoroughly reviewed to find the appropriate algorithm which will provide accurate result with minimum drift error. Sensor fusion, Inertial Measurement Unit (IMU), MEMS inertial sensor, Kalman filter based global translational localization systems are studied. It is observed, prevailing approaches consist issues such as stability, random bias drift, noisy acceleration output, position estimation error, robustness or accuracy, cost effectiveness etc. Moreover, issues with motions that do not follow laws of physics, bandwidth, restrictive nature of assumptions, scale optimization for large space are noticed as well. Advantages of such smartphone sensor based position estimation approaches include, less memory demand, very fast operation, making them well suited for real time problems and embedded systems. Being independent of the size of the system, they can work effectively for high dimensional systems as well. Through study of these approaches it is observed, extended Kalman filter gives the highest accuracy with reduced requirement of excess hardware during tracking. It renders better and faster result when used in accelerometer sensor. With the aid of various software, error accuracy can be increased further as well.

A Sensor Awakening Algorithm for Wireless Multimedia Sensor Networks Three Dimensional Target Tracking

For node awakening in wireless multi-sensor networks, an algorithm is put forward for three dimensional tar- get tracking. To monitor target dynamically in three dimensional area by controlling nodes, we constract vir- tual force between moving target and the current sense node depending on the virtual potential method, then select the next sense node with information gain function, so that when target randomly move in the specific three dimensional area, the maximum sensing ratio of motion trajectory is get with few nodes. The proposed algorithm is verified from the simulations.

Real-time accurate hand path tracking and joint trajectory planning for industrial robots(Ⅱ)

Previously, researchers raised the accuracy for a robot′s hand to track a specified path in Cartesian space mainly through increasing the number of knots on the path and the segments of the path. But, this method resulted in the heavier on line computational burden for the robot controller. In this paper, aiming at this drawback, the authors propose a new kind of real time accurate hand path tracking and joint trajectory planning method for robots. Through selecting some extra knots on the specified hand path by a certain rule, which enables the number of knots on each segment to increase from two to four, and through introducing a sinusoidal function and a cosinoidal function to the joint displacement equation of each segment, this method can raise the path tracking accuracy of robot′s hand greatly but does not increase the computational burden of robot controller markedly.

Trajectory Tracking of Autonomous Vehicle with the Fusion of DYC and Longitudinal–Lateral Control

The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the yaw stability is seldom considered during trajectory tracking. In this research, a combination of the longitudinal–lateral control method with the yaw stability in the trajectory tracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectory tracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectory tracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed control strategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle.

Fast density peak-based clustering algorithm for multiple extended target tracking

The key challenge of the extended target probability hypothesis density (ET-PHD) filter is to reduce the computational complexity by using a subset to approximate the full set of partitions. In this paper, the influence for the tracking results of different partitions is analyzed, and the form of the most informative partition is obtained. Then, a fast density peak-based clustering (FDPC) partitioning algorithm is applied to the measurement set partitioning. Since only one partition of the measurement set is used, the ET-PHD filter based on FDPC partitioning has lower computational complexity than the other ET-PHD filters. As FDPC partitioning is able to remove the spatially close clutter-generated measurements, the ET-PHD filter based on FDPC partitioning has good tracking performance in the scenario with more clutter-generated measurements. The simulation results show that the proposed algorithm can get the most informative partition and obviously reduce computational burden without losing tracking performance. As the number of clutter-generated measurements increased, the ET-PHD filter based on FDPC partitioning has better tracking performance than other ET-PHD filters. The FDPC algorithm will play an important role in the engineering realization of the multiple extended target tracking filter.

Design of a Networked Tracking Control System With a Data-based Approach

Tracking control is a very challenging problem in the networked control system(NCS), especially for the process with blurred mechanism and where only input-output data are available. This paper has proposed a data-based design approach for the networked tracking control system(NTCS). The method utilizes the input-output data of the controlled process to establish a predictive model with the help of fuzzy cluster modelling(FCM)technology. Then, the deduced error and error change in the future are treated as inputs of a fuzzy sliding mode controller(FSMC) to obtain a string of future control actions. These candidate control actions in the controller side are delivered to the plant side. Thus, the network induced time delays are compensated by selecting appropriate control action. Simulation outputs prove the validity of the proposed method.