Signal Tracking Research Articles

LMI-Based MPC Design Applied to the Single-Phase PWM Inverter with LC Filter under Uncertain Parameters.

This work proposes a design methodology for predictive control applied to the single-phase PWM inverter with an LC filter. In the design, we considered that the PWM inverter has parametric uncertainties in the filter inductance and output load resistance. The control system purpose is to track a sinusoidal signal at the inverter output. The designed control system with an embedded integrator uses the principle of receding horizon control, which underpinned predictive control. The methodology was described by linear matrix inequalities, which can be solved efficiently using convex programming techniques, and the optimal solution is obtained. MATLAB-Simulink and real-time FPGA-in-the-loop simulations illustrate the viability of the proposed control system. The LMI-based MPC reveals an effective performance for tracking of a sinusoidal reference signal and disturbance rejection of input voltage and load perturbations for the inverter subject to uncertainties.

Enhancing Roads Infrastructure Monitoring with FBG Sensors and Multi-Threshold Signal Tracking

Accurate monitoring techniques are needed to improve pavement durability by ensuring their structural integrity and longevity. This study developed an innovative real-time monitoring system utilizing fiber Bragg grating (FBG) sensors embedded in asphalt layers. The data collected by FBG sensors includes a baseline primarily influenced by temperature and peak shape data associated with short-term loading from passing vehicles. Therefore, analyzing FBG data and identifying statistical patterns poses a challenge. To address this challenge, employing a signal tracker proves to be a valuable option for monitoring the baseline and scanning signals for subsequent analysis. Moreover, considering the varying loading weights on FBG sensors due to diverse vehicles, tracking FBG signals across multiple thresholds enhances precision. A MATLAB-based program was developed incorporating a multi-threshold signal tracker capable of efficiently processing FBG data by tracking signals in both positive and negative multi-thresholds. This tracker effectively distinguishes between different loading events and extracts the baseline signal after tracking. Subsequently, the system provides outputs, including loading distribution, number of loading events, traffic, and temperature effects. Finally, to validate the system, real FBG data collected during an extensive monitoring campaign was processed using the developed program. The obtained outputs contribute to a comprehensive assessment of pavement performance, thereby facilitating the development of more accurate maintenance and rehabilitation strategies.

Fixed-time adaptive neural tracking control for high-order nonlinear switched systems with input saturation and dead-zone

This article investigates the problem of tracking control for high-order switched nonlinear systems with input saturation and dead-zone. The uncertain nonlinear functions are estimated via applying radial basis function neural networks (RBF NNs). An improved transformation approach is designed to simplify the design complexity caused by input nonlinearities. In particular, a novel filter is presented to handle the difficulty of “explosion of complexity”. With the support of the common Lyapunov function (CLF) approach, a novel neural fixed-time dynamic surface control (DSC) scheme is proposed to assure all the signals in closed-loop systems are bounded and the output signal tracks the expected signal within fixed time. The simulation example illustrates the validity of the proposed control algorithm.

Development of an Adaptive Beamforming Algorithm for Signal Tracking and Acquisition in a Mobile Radio Antenna System

Development of an Adaptive Beamforming Algorithm for Signal Tracking and Acquisition in a Mobile Radio Antenna System

Dissipative sliding mode tracking control for discrete-time singular T-S fuzzy systems via a preview target mechanism

This study focuses on the dissipative sliding mode preview tracking control (SMPTC) of discrete-time singular T-S fuzzy systems (STSFSs) via a preview target mechanism. Due to the presence of singular matrix and input matrices with fuzzy rules in the system, the existing preview control approaches cannot be directly adopted. As a result, a novel singular augmented error system (AES) is derived based on a general method. Furthermore, the tracking problem has been translated into the stabilisation of singular AES. A linear sliding mode surface (SMS) is proposed for singular AES, and a suitably SMPTC law is presented. Sufficiency conditions for relaxation are derived to guarantee that the sliding mode dynamics is admissible with the dissipative criterion, and the sliding mode region (SMR) can be reached. The difference singular matrix is fully considered in the whole design process such that the derived conditions can be checked easily. Finally, two examples have shown the effective tracking of the original output signal of system by utilising the proposed SMPTC law.

Validation of induction/steering reserve-boosting active power control by a wind tunnel experiment with dynamic wind direction changes

This paper presents an experimental validation of an active power control methodology that combines induction control and wake steering to maximize the power reserve of the wind turbines in a farm. The experiments are carried out on a cluster of three scaled wind turbines in a boundary-layer wind tunnel, by dynamically varying the wind direction, and by considering a time-varying power tracking signal that mimics secondary frequency control of the grid. The methodology is compared with three active power control algorithms sourced from the literature. Results indicate that the instantaneous power reserves are indeed improved by an appropriate handling of wake effects, achieving a more accurate tracking of the power signal.

Experimental test and analysis of impact suppression for hydraulic-driven leg using a new MR damper with multi-channels

When hydraulic-legged robots move under high loads on irregular ground, they are vulnerable to ground impacts. Vibration affects the motion performance of the robot and damages its mechanical structure. This study aims to improve the properties of vibration absorption and impact resistance of hydraulic-legged robots. Because the traditional MR damper (MRD) has small output in finite volume, a novel MRD with a multistage flow channel (MFC-MRD) can output a large damping force designed. First, an MRD prototype was designed for a mechanical leg’s driving joint. Subsequently, the system is analyzed theoretically, and a semi-active control strategy is designed and simulated. Finally, the vibration and impact resistance of the prototype were tested. The experimental results show that in the signal tracking experiment, the maximum overshoot under semi-active control was reduced by 53.0%, and the settling time was reduced by 76.9% compared with the passive control. The impact test reduced the maximum displacement fluctuation by 41.09%, and the buffer time is only 0.24 s.

Event-Triggered Supercavitating Vehicle Terminal Sliding Mode Control Based on Non-Recursive Observation

Supercavitating vehicles present significant issues in controller design due to their multiphase flow-coupling characteristics. This study addresses force analysis and the construction of a 6-degree-of-freedom mathematical model for a supercavitating vehicle. A terminal sliding mode control law is intended to guarantee the quick tracking of the command signal for high-precision attitude control. To drastically lower the frequency of actuation and communication, a mechanism to trigger events is also introduced into the control link. A disturbance observer, which estimates system uncertainty using a non-recursive differentiator, improves the robustness of the system. The Lyapunov approach is used to prove that the system is stable. Numerical simulation results validate that the proposed method enhances control accuracy and robustness. The event-trigger mechanism reduces the execution frequency to 18.59%, effectively reducing the communication burden.

Design and Implementation of a Wide-Swing CMOS Multiplier for AC Source Signal Tracking and Modulation

Design and Implementation of a Wide-Swing CMOS Multiplier for AC Source Signal Tracking and Modulation

WiFi-CSI Difference Paradigm

Passive tracking plays a fundamental role in numerous applications such as elderly care, security surveillance, and smart home. To utilize ubiquitous WiFi signals for passive tracking, the Doppler speed extracted from WiFi CSI (Channel State Information) is the key information. Despite the progress made, existing approaches still require a large number of samples to achieve accurate Doppler speed estimation. To enable WiFi sensing with minimum amount of interference on WiFi communication, accurate Doppler speed estimation with fewer CSI samples is crucial. To achieve this, we build a passive WiFi tracking system which employs a novel CSI difference paradigm instead of CSI for Doppler speed estimation. In this paper, we provide the first deep dive into the potential of CSI difference for fine-grained Doppler speed estimation. Theoretically, our new design allows us to estimate Doppler speed with just three samples. While conventional methods only adopt phase information for Doppler estimation, we creatively fuse both phase and amplitude information to improve Doppler estimation accuracy. Extensive experiments show that our solution outperforms the state-of-the-art approaches, achieving higher accuracy with fewer CSI samples. Based on this proposed WiFi-CSI difference paradigm, we build a prototype passive tracking system which can accurately track a person with a median error lower than 34 cm, achieving similar accuracy compared to the state-of-the-art systems, while significantly reducing the required number of samples to only 5%.

Contribution Of TRPV4 Channels To Calcium Signaling Profiles Of The Lung Microvascular Endothelium Under Acidic pH

Maintenance of lung endothelial barrier integrity is achieved to a great extent through effcient homeostatic endothelial calcium signaling in the lung microvasculature. The transient receptor potential vanilloid 4 (TRPV4), a non-selective calcium permeable channel has been implicated in several pulmonary pathologies involving lung barrier disruption. These channels are activated by various physical forces and chemical stimuli, but their underlying contribution to inherent and distinct microvascular endothelial Ca2+ signaling profiles are unknown. We previously assessed the role of TRPV4 channels in basal Ca2+ signaling dynamics of the pulmonary microcirculation under differing conditions of stretch and temperature. In the current study, we evaluate the impact of acidic pH (7.1, resembling acidosis) on the distinct endothelial Ca2+ signaling events in the mouse lung microcirculation and examine the participation of TRPV4 channels. Lung slices isolated from the Cdh5-GCaMP8 mice (transgenic mice with Ca2+-dependent fluorescent indicator expressed specifically within vascular endothelial cells) were mounted on Sylgard inserts with HEPES buffer (pH 7.45) and imaged for their basal signaling events using spinning disk confocal microscopy. After an initial baseline recording, the bathing solution was replaced with acidic HEPES buffer (pH 7.1) and recordings were made for approximately two minutes at 5 frames per second. These slices were then treated with the TRPV4 channel inhibitor GSK2193874 (3μM) or vehicle. The recorded image sequences were analyzed by using ImageJ and our custom signal tracking software S8, for quantification of the Ca2+ signaling profiles through event frequency, amplitude, duration and spread. Subjecting the lung slices to pH 7.1 increased the amplitude and spatial spread of the signaling events but the duration and frequency of the events remained relatively constant when compared to baseline recorded events. Addition of the channel blocker diminished the signaling event frequency, amplitude and spatial spread of the lung tissues. The normal pH and vehicle control for the above experiments did not show any relative change from the baseline signaling event profiles. To summarize, treating the lung slices to acidic pH increased the event amplitude and event spatial area distributions, indicating widespread activation of Ca2+ entry events. These increased event parameters were reduced upon addition of the antagonist, suggesting higher contribution of TRPV4 channel induced Ca2+ signaling events under acidic pH. We conclude that the channels contribute minimally to basal dynamics under homeostatic conditions but are activated to a greater extent under stimulations resembling pathological conditions like acidosis or acid aspirations. NIH P01 HL066299, R01 HL155288, NIH S10 0D020149. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Enhancing USVs navigation based on minimum error entropy of GPS vector tracking

In recent years, unmanned surface Vessels (USVs) have increasingly been used for river monitoring and hydrological surveys. USVs rely on global navigation satellite systems (GNSS) for navigation. However, signal blocking can cause the traditional GNSS vector tracking (VT) loop to increase the code phase and carrier frequency errors, leading to higher positioning errors that do not meet USVs’ requirements. To address this problem, we propose a VT method based on the minimum error entropy (MEE) in the signal tracking module. The MEE Kalman filter is adopted as the loop filter to mitigate code phase and carrier frequency errors, reduce non-Gaussian noise and random errors generated by signal blocking, and enhance the positioning accuracy and robustness of USV navigation. The measurement noise covariance of the loop filter was adjusted adaptively using the signal carrier-to-noise ratio. A field experiment was conducted using a commercial GNSS receiver as reference. The results demonstrate a 19.3% improvement in positioning accuracy compared with the traditional method in an open environment. Moreover, the proposed method maintains stable operation and achieves a 79.4% improvement in positioning accuracy during signal blocking. This novel algorithm offers a new concept for USV navigation systems to cope with signal blocking.

Implementasi Metode Moving Average dan Regresi Linier pada Peramalan Permintaan Mie di PT XYZ

PT XYZ is a company operating in the food industry. The company produces various kinds of food, such as biscuits, wafers, vermicelli and noodles. Noodle products are the most popular products, and there are often significant changes in each period. This causes fluctuations and results in uncontrolled inventory. PT XYZ can avoid this problem if it has a way to estimate noodle demand. Forecasting is a planning method for estimating products in the future. The moving average and linear regression methods are the methods used in this research. Based on the results of the calculations carried out, the method chosen is the linear regression method because the smallest Mean Squared Error (MSE) value is 620370900 and the tracking signal results from the linear regression method are close to zero. The results of forecasting the need for noodle products for the next period were 169,524 pcs. It is hoped that the results of this forecasting can help PT XYZ in carrying out production planning.

Research on the Control Method of a Brushless DC Motor Based on Second-Order Active Disturbance Rejection Control

This research addresses the issues of weak anti-disturbance ability, fast response, and incompatibility of overshoot in the control process of brushless DC motors (BLDCs). A six-step commutation control method based on second-order active disturbance rejection control (ADRC) is derived following the analysis of the BLDC model and the mathematical model of ADRC. A control model of the BLDC using both PI and ADRC is constructed. Detailed comparative and quantitative analyses of the simulation results using PI and ADRC are conducted, focusing on the anti-load disturbance capabilities using the integrated square error (ISE), integrated time square error (ITSE), integrated absolute error (IAE), and integrated time absolute error (ITAE). Experimental testing on the STM32F4 controller is also carried out, analyzing four error integral criteria in depth. The results indicate that both the ADRC and PI control modes can track the target signal without overshooting, demonstrating strong anti-load disturbance ability and robustness at varying working speeds. In the BLDC control system, using the ADRC control method can achieve fast and non-overshoot tracking of target signals compared to the PI control method, and ADRC has stronger resistance to load disturbances.

State of charge estimation of electrical vehicle battery by Using Box Particle Filter Signal Tracking Method

ABSTRACT This paper concentrates on the effective study of the online state of charge (SoC) estimation of lithium-ion batteries used in electric vehicles (EVs). Box Particle filters (BPF) are commonly used in the estimation of multivariate systems under noisy environments. In this study, a Joint-estimator is proposed which uses the forgetting factor recursive least square (FF-RLS) method for the 1-RC battery model online parameter estimation and the lithium-ion battery SoC is estimated using battery terminal voltage signal tracking with (BPF). The implemented method is compared with a Sequential Importance Resampling Particle Filter (SIR-PF) which shows that the proposed BPF has reduced the number of particles and computational time and maintained the efficiency comparable to the SIR-PF. The BPF performance is further evaluated at assorted voltage signal tracking accuracy, the number of boxes and the initial dimension of the boxes. The BPF method requires less number of boxes as compared to the SIR-PF with compatible efficiency. Therefore, BPF can be used as an alternative to the complex algorithms used in the SoC estimation in battery management systems (BMS) of electric vehicles.

Design of Universal Code Generator for Multi-Constellation Multi-Frequency GNSS Receiver

A multi-constellation, multi-frequency Global Navigation Satellite System (GNSS) receiver is capable of simultaneously receiving signals from multiple satellite constellations across various frequency bands. This allows for increased observations, thereby enhancing navigation accuracy, continuity, effectiveness, and reliability. The spread spectrum code structures used in satellite navigation signals differ among systems. Compatible code generators are employed in multi-constellation, multi-frequency GNSS receivers to support tasks such as signal acquisition and tracking. There are three main types of spread spectrum code structures: Linear Feedback Shift Register (LFSR), Legendre sequences, and Memory codes. The Indian Regional Navigation Satellite System (IRNSS) released the L1-SPS (Standard Positioning Service) signal format in August 2023, which utilizes the Interleaved Z4-linear ranging code (IZ4 code) as its spread spectrum code. Currently, there is no universal code generator design compatible with the IZ4 code. In this paper, a proposed universal code generator is based on the hardware structure of the IRNSS IZ4 code generator. It achieves compatibility with all LFSR-based spread spectrum codes and enables parallel generation of multiple sets of GNSS signal spread spectrum codes, thereby improving hardware utilization efficiency. The proposed structure is implemented and validated using FPGA design, and resource consumption is provided as part of the validation results.

Driving an asynchronous motor powered by PV‐MPPT using equivalent RST controller of fractional order PI and IP, based on generalized predictive control

AbstractThe article introduces a new model of a Reference Signal Tracking (RST) controller for the fractional order quantities. The controller is applied to an indirect field‐oriented control (IFOC) system used for the speed control of an asynchronous motor powered by a photovoltaic (PV) generator with a maximum power point tracking (MPPT) algorithm. This model utilizes two fractional order controllers: the fractional order proportional‐integral (FOPI) regulator and the fractional‐order integral‐proportional (FOIP) regulator. These controllers are used with the generalized predictive control (GPC) technique. The first step in the approach is to derive the equivalent digital RST controller's model from the FOPI and FOIP controller's transfer functions. The GPC technique converts the continuous‐time FOPI (and FOIP) controller into a discrete‐time version. This conversion ensures a fast response and effective disturbance rejection. Simulation tests are conducted to analyze the rotor speed and stator current ripples to evaluate the performance of the proposed method. The results demonstrate the effectiveness of the introduced scheme in achieving improved control performance in terms of response speed and disturbance rejection. The article presents a modified RST controller model based on the fractional order approach applied to an IFOC system for motor speed control driven by a photovoltaic generator. Using FOPI, FOIP controllers, and GPC contributes to enhanced control performance, as evidenced by the simulation results.

Intelligent Detection Method for Satellite TT&C Signals under Restricted Conditions Based on TATR

In complex electromagnetic environments, satellite telemetry, tracking, and command (TT&C) signals often become submerged in background noise. Traditional TT&C signal detection algorithms suffer a significant performance degradation or can even be difficult to execute when phase information is absent. Currently, deep-learning-based detection algorithms often rely on expert-experience-driven post-processing steps, failing to achieve end-to-end signal detection. To address the aforementioned limitations of existing algorithms, we propose an intelligent satellite TT&C signal detection method based on triplet attention and Transformer (TATR). TATR introduces the residual triplet attention (ResTA) backbone network, which effectively combines spectral feature channels, frequency, and amplitude dimensions almost without introducing additional parameters. In signal detection, TATR employs a multi-head self-attention mechanism to effectively address the long-range dependency issue in spectral information. Moreover, the prediction-box-matching module based on the Hungarian algorithm eliminates the need for non-maximum suppression (NMS) post-processing steps, transforming the signal detection problem into a set prediction problem and enabling parallel output of the detection results. TATR combines the global attention capability of ResTA with the local self-attention capability of Transformer. Experimental results demonstrate that utilizing only the signal spectrum amplitude information, TATR achieves accurate detection of weak TT&C signals with signal-to-noise ratios (SNRs) of −15 dB and above (mAP@0.5 > 90%), with parameter estimation errors below 3%, which outperforms typical target detection methods.

A novel stability criterion and precise control for linear time delay systems based on regional configuration of the poles

This paper presents the concept of region stability and provides criteria for region stability of linear time delay systems, which can reveal the dynamic and steady-state performance of the systems more precisely. Corresponding design schemes for stabilization and tracking control that can accurately control various performance of time delay systems have also been explored. First, in the light of the connection between the poles and the dynamic properties of the system, the concept of region stability is given to describe the finer dynamic behavior of time delay systems. The criteria for the region stability are also presented. Second, the region stabilization methods are investigated, which can ensure that the system satisfies a certain dynamic performance by setting the eigenvalues in a certain convex region. Third, a precise tracking control of the linear time delay systems is addressed as an application of region stabilization. It can control the steady state performance and transient response of the tracking signal more precisely. Finally, three instances are provided to display the superiority of the new method for the performance indexes of the linear time delay systems.

EpiVar Browser: advanced exploration of epigenomics data under controlled access.

Human epigenomic data has been generated by large consortia for thousands of cell types to be used as a reference map of normal and disease chromatin states. Since epigenetic data contains potentially identifiable information, similarly to genetic data, most raw files generated by these consortia are stored in controlled-access databases. It is important to protect identifiable information, but this should not hinder secure sharing of these valuable datasets. Guided by the Framework for responsible sharing of genomic and health-related data from the Global Alliance for Genomics and Health (GA4GH), we have developed an approach and a tool to facilitate the exploration of epigenomics datasets' aggregate results, while filtering out identifiable information. Specifically, the EpiVar Browser allows a user to navigate an epigenetic dataset from a cohort of individuals and enables direct exploration of genotype-chromatin phenotype relationships. Because individual genotypes and epigenetic signal tracks are not directly accessible, and rather aggregated in the portal output, no identifiable data is released, yet the interface allows for dynamic genotype-epigenome interrogation. This approach has the potential to accelerate analyses that would otherwise require a lengthy multi-step approval process and provides a generalizable strategy to facilitate responsible access to sensitive epigenomics data. Online portal: https://computationalgenomics.ca/tools/epivar; EpiVar Browser source code: https://github.com/c3g/epivar-browser; bw-merge-window tool source code: https://github.com/c3g/bw-merge-window.