Peak Tracking Research Articles

A Compact, Voltage-Mode Type-I PLL With Gain-Boosted Saturated PFD and Synchronous Peak Tracking Loop Filter

Despite their inherent stability, area-efficient loop filters, and insensitivity to phase-frequency detector nonlinearity and dead-zone, type-I phase-locked loops (PLLs) are used infrequently because of two major limitations—limited lock-range and large reference spurs. This paper introduces a type-I PLL that takes advantage of the inherent benefits of the architecture, while tackling its limitations by means of gain boosting in the forward path for lock-range improvement and synchronous peak tracking of the voltage-controlled oscillator control voltage for reference spur reduction. Sampling in the loop filter changes the loop dynamics, and methods to accurately predict the closed-loop response, starting from state-space equations, are provided. A digital-friendly, voltage-mode topology is proposed that does not need charge pumps or opamps. A prototype 2.2–2.8-GHz PLL occupies a core area of 0.12 mm2 in 0.13- $\mu \text{m}$ CMOS and achieves −103.4 dBc/Hz in-band phase noise, −65-dBc reference spur, and 2.5- $\mu \text{s}$ worst-case lock-time while consuming 6.8 mW from a 1.2-V supply.

Instantaneous frequency estimation of intersecting and close multi-component signals with varying amplitudes

Instantaneous frequency (IF) estimation of multi-component signals with closely spaced and intersecting signal components of varying amplitudes is a challenging task. This paper presents a novel iterative time–frequency (TF) filtering approach to address this problem. The proposed algorithm first adopts a high-resolution time–frequency distribution to resolve close components in the TF domain. Then, IF of the strongest signal component is estimated by a new peak detection and tracking algorithm that takes into account both the amplitude and the direction of peaks in the TF domain. The estimated IF is used to remove the strongest component from the mixture, and this process is repeated till the IFs of all signal components are estimated. Experimental results show the superiority of the proposed method as compared to other state-of-the-art methods.

Maximum Power Extraction from a Partially Shaded PV System Using an Interleaved Boost Converter

The partially shaded photovoltaic (PSPV) condition reduces the generated power and contributes to hot spot problems that may lead to breakdown of shaded modules. PSPV generates multiple peak, one global one and many other local peaks. Many efficient, accurate and reliable maximum power point tracker (MPPT) techniques are used to track the global peak instead of local peaks. The proposed technique is not limited to global peak tracking, but rather it is capable of tracking the sum of all peaks of the PV arrays using an interleaved boost converter (IBC). The proposed converter has been compared with the state of the art conventional control method that uses a conventional boost converter (CBC). The converters used in the two PSPV systems are interfaced with electric utility using a three-phase inverter. The simulation findings prove superiority of the PSPV with IBC compared to the one using CBC in terms of power quality, reliability, mismatch power loss, DC-link voltage stability, efficiency and flexibility. Also, IBC alleviates partial shading effects and extracts higher power compared to the one using CBC. The results have shown a remarkable increase in output generated power of a PSPV system for the three presented scenarios of partial shading by 61.6%, 30.3% and 13%, respectively, when CBC is replaced by IBC.

Improvements on the cross-correlation algorithm used for tracking fractional Bragg grating wavelength shifts in multimode fibres

Abstract In this paper we report on the deployment of Finite Impulse Response (FIR) filters as an extension to the common cross-correlation algorithm (CCA), for accurate peak tracking of multimode and single mode fibre Bragg gratings when dealing with wavelength shifts below the sampling resolution of the demodulator; the well-known peak-locking effect. The performance of the common CCA under these conditions was studied using simulations for single and multiple peak grating spectra and was compared with the performance of proposed, improved CCA method. We studied the cases where fibre Bragg gratings are wavelength-shifted with triangular and sinusoidal manner and how the proposed method behaves under these conditions. We experimentally evaluated our proposed method by utilising strain measurements using a fibre Bragg grating inscribed in a multimode gradient index CYTOP polymer fibre. The method and algorithm showed significant improvement concerning the peak-locking effect, while maintaining the response speed.

Correction of Peak Tracking Ripple in Solid State Spectrometers

Errors in peak wavelengths from fiber Bragg gratings (FBGs) when monitored using a pixel-based solid state spectrometer have been investigated. These errors show a pseudo-sinusoidal ripple superimposed upon the expected linear response. The error is analogous to a peak-locking effect common to subpixel resolution particle tracking by CCD camera in particle image velocimetry. The amplitude of the error is calibrated as a proportion of the scaled variation of the change in the peak power of the calculated peak as the spectral peak is scanned across the pixel array. An error correction algorithm has been developed and verified in order to provide an increase in the accuracy of sensing solutions when using pixel-based spectrometers. The methods presented here permit the correction of pixel induced ripple errors in real time using data commonly available from many interrogation spectrometers. Calibration prior to use can be achieved by scanning each FBG spectral peak across the width of a single pixel. The proposed method of error correction is applied to a fiber optic sensor array utilized for biomedical pressure and temperature measurement and demonstrates a clear ability to increase the accuracy of measured signals.

A Digital Disturbance Estimator (DDE) for Multiobjective Grid Connected Solar PV Based Distributed Generating System

The disturbances including harmonics, distortions, transients, fluctuations, and dc offsets in the grid voltages and uncertain load currents, are the most challenging issues in the scenario of renewable sources based energy generating systems integrated to the conventional grid. A three-phase, double stage, grid tied solar photovoltaic based distributed generating (SPVDG) system fulfilling multiple objectives, is presented using an adaptive digital disturbance estimator (DDE) and a peak power tracking scheme. The adaptive DDE has the detection proficiency of all the harmonics and lumped disturbances resulting fundamental component estimation of the periodic signals such as grid voltages and load currents. This system deals with objectives such as reactive power compensation, load balancing, peak solar power extraction, operation at grid voltage sags and swells, estimation of harmonics, dc offsets, disturbances, etc. and their elimination. Moreover, this system ensures the active power flow from the SPVDG system to the local loads as well as the grid through a three-phase voltage source converter (VSC). An adaptive technique is used to adjust the dc-link voltage with respect to the grid voltage variation(s) that is advantageous in terms of losses in the VSC. A Lyapunov function candidate is considered to estimate the gains of the disturbance estimator confirming its parameter convergence. Considering the aforementioned objectives, SPVDG system with the proposed DDE-based control scheme, is simulated using <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Matlab</small> /Simulink environment and then practically implemented using a prototype developed in the laboratory to confirm its performance under steady and dynamic conditions.

Combining Adaptive Filter and Phase Vocoder for Heart Rate Monitoring Using Photoplethysmography During Physical Exercise.

This study presents a robust heart rate monitoring algorithm using photoplethysmography (PPG) signal during physical exercise. The proposed method combines two stage: motion artifact removal and frequency refinement. The cascaded normalized least mean square adaptive filter is used to attenuate the noise introduced by motion artifacts in the PPG signal. A phase vocoder technique is used to refine the frequency calculated by Fourier Transform, from which the heart rate is finally tracked. On a publicly available database of twelve PPG recordings, the proposed technique obtains an average absolute error (AAE) of 1.08 beat per minute (BPM). Person correlation coefficient of 0.997 is achieved between true heart rate and estimated heart rate. In contrast to other available approaches, the proposed method has merely one parameter to tune in spectral peak tracking step for heart rate estimation.

A Maximum Likelihood Formulation To Exploit Heart Rate Variability for Robust Heart Rate Estimation From Facial Video.

The problem of estimating the heart rate (HR) from a racial video is considered. A typical approach for this problem is to use independent component analysis (ICA) on the red, blue, green intensity prof iles averaged over the facial region. This provides estimates of the underlying source signals, whose spectral peaks are used to predict HR in every analysis window. In this work, we propose a maximum likelihood formulation to optimally select a source signal in each window such that the predicted HR trajectory not only corresponds to the most likely spectral peaks but also ensures a realistic HR variability (HRV) across analysis windows. The likelihood function is efficiently optimized using dynamic programming in a manner similar to Viterbi decoding. The proposed scheme for HR estimation is denoted by vICA. The performance of vICA is compared with a typical ICA approach as well as a recently proposed sparse spectral peak tracking (SSPT) technique that ensures that the predicted HR does not vary drastically across analysis windows. Experiments are performed in a five fold setup using racial videos of 15 subjects recorded using two types of smartphones (Samsung Galaxy and iPhone) at three different distances (6inches, lfoot, 2feet) between the phone camera and the subject. Mean absolute error (MAE) between the original and predicted HR reveals that the proposed vICA scheme performs better than the best of the baseline schemes, namely SSPT by -8.69%, 52.77% and 8.00% when Samsung Galaxy phone was used at a distance of 6inches, lfoot, and 2feet respectively. These improvements are 12.13%, 13.59% and 18.34% when iPhone was used. This, in turn, suggests that the HR predicted from a racial video becomes more accurate when the smoothness of HRV is utilized in predicting the HR trajectory as done in the proposed vICA.

Implementation of a generic liquid chromatographic method development workflow: Application to the analysis of phytocannabinoids and Cannabis sativa extracts

A generic liquid chromatographic method development workflow was developed and successfully applied to the analysis of phytocannabinoids and Cannabis sativa extracts. Our method development procedure consists in four steps:i)The screening of primary parameters (i.e. stationary phase nature, organic modifier nature and approximate mobile phase pH) was carried out with a generic gradient on a short narrow bore column, using a system able to accommodate numerous solvents/buffers and columns. Instead of complete peak tracking, the number of peaks which can be separated was considered as a response at this level, to save time.ii)The optimization of secondary parameters (i.e. gradient conditions, mobile phase temperature and pH within a narrow range) requires only 12 initial experiments and the use of HPLC modeling software for data treatment. It allows to find out the best retention and selectivity for the selected compounds. Peak tracking was performed with a single quadruple mass detector in single ion recording mode, and UV detection (in a broad wavelength range).iii)The refinement step allows to further adjust column efficiency, by tuning column length and mobile phase flow rate. This can also be done virtually using HPLC modeling software.iv)The robustness testing step was also evaluated from a virtual experimental design. Success rate and regression coefficients were estimated in about 1 min, without the need to perform any real experiment.At the end, this method development workflow was performed in less than 4 days and minimizes the costs of the method development in liquid chromatography.

Motion Resistant Image-Photoplethysmography Based on Spectral Peak Tracking Algorithm

Medical fields have seen increasing attention being given to image based heart rate measurement in recent years. One of the major limitations is motion artifacts of subject’s head. Although there have been many studies focusing on signal extraction using different parameters and models, the development of frequency domain analysis is emerging slowly and moving in many directions. In the field of contact photoplethysmography (PPG), recent studies employed the acceleration signals to assist their spectral peak tracking algorithms. Inspired by the development of contact PPG, we are proposing a motion resistant spectral peak tracking (MRSPT) framework which eliminates the motion artifacts by integrating facial motion signals. The effectiveness of MRSPT coupled with the optimal image-based PPG (iPPG) signal has been tested against the state-of-the-art spectral peak tracking algorithms, multi-channel spectral matrix decomposition (MC-SMD), and the maximum peak selection coupled with optimal iPPG signal (Optimal MPS). Compared with MC-SMD and Optimal MPS, MRSPT uplifts the success rate-10 (success rate-5), the probability in which the absolute error is below ten (five) beats per mins, from 54.7% (36.3%) with MC-SMD and 73.0% (61.3%) with Optimal MPS to 90.7% (75.7%) with MRSPT in motion scenarios where subject moves arbitrarily with different distance or lighting. MRSPT also enhances the success rate-10 (success rate-5) from 40.7% (26.3%) with MC-SMD and 57.4% (45.7%) with Optimal MPS to 73.4% (58.4%) with MRSPT in all seven motion conditions including driving and running. Averagely, the success rate-five of Optimal MRSPT surpass the success rate-10 of both Optimal MPS and MC-SMD.

A Reduced Switching Loss Technique Based on Generalized Scalar PWM for Nine-Switch Inverters

For three-phase dual-output dc–ac conversion systems, the nine-switch inverter is one of the most versatile available topologies. Despite some disadvantages, recent studies show that the nine-switch inverter achieves efficiency values equivalent to or higher than its 12-switch counterpart, when operating in certain ranges of the modulation index and displacement angles. The use of proper pulse width modulation techniques is able to increase the efficiency even more, as well as to equalize the loss distribution among the switches, favoring an effective and low-cost thermal design. The available pulse width modulation techniques are complex and do not explore the full capacity of the nine-switch inverter to reduce its losses. For this reason, this paper proposes an unrestricted generalized scalar pulse width modulation for nine-switch inverters. Based on this new generalization, a current peak tracking technique is also proposed, achieving small average number of switchings and the highest overall efficiency when compared with other techniques, likewise a more balanced loss distribution among the switches. Experimental results are carried out to demonstrate the validity of the new generalization and the effectiveness of the proposed technique in reducing the switching losses.

Parameterized model based Short-time chirp component decomposition

As a specific case of chirp component, the short-time chirp component (STCC) only continues a duration in a reference interval with a birth and death. A STCC usually possesses of important information directly related to kinematic or structural characteristics of a target. In this paper, a novel method is developed to decompose a multi-component short-time chirp signal into a series of STCCs. The decomposition method is mainly based on a parameterized mathematical model, which is used to represent the STCC, and a peak tracking approach, which is adopted to extract the instantaneous frequencies (IFs), and corresponding births and deaths for all the STCCs. With the model and the extracted IFs, the decomposition can be conducted by solving a linear system of equations. The effectiveness of the proposed method is demonstrated by two simulated examples and a marine biologic sound.

A novel MPPT circuit with 99.1% tracking accuracy for energy harvesting

A novel maximum power point tracking (MPPT) circuit based on Buck–Boost converter is presented for micro-power energy harvesting, which efficiently improves the power efficiency and robustness of system. The proposed MPPT uses the low-power analog multiplier and multi-outputs self-powered common-gate comparator to track the input power, and simplifies data calculation and structure greatly. The fast dynamic switching circuit and digital control circuit are introduced to enhance the adaptability and flexibility of system. The performance of whole converter was validated by the simulation results in a 65-nm CMOS process. The minimum starting voltage is 0.15 V. The peak output power is 40.5 µW, with a power loss of 14.1 µW. The peak power efficiency and peak tracking efficiency are 92.1 and 99.1%, respectively. The proposed MPPT has the advantages such as low power, high efficiency, fast tracking speed, simple structure.

Time-domain prefilter design for enhanced tracking and vibration suppression in machine motion control

Abstract Structural flexibility can impact negatively on machine motion control systems by causing unmeasured positioning errors and vibration at locations where accurate motion is important for task execution. To compensate for these effects, command signal prefiltering may be applied. In this paper, a new FIR prefilter design method is described that combines finite-time vibration cancellation with dynamic compensation properties. The time-domain formulation exploits the relation between tracking error and the moment values of the prefilter impulse response function. Optimal design solutions for filters having minimum H2 norm are derived and evaluated. The control approach does not require additional actuation or sensing and can be effective even without complete and accurate models of the machine dynamics. Results from implementation and testing on an experimental high-speed manipulator having a Delta robot architecture with directionally compliant end-effector are presented. The results show the importance of prefilter moment values for tracking performance and confirm that the proposed method can achieve significant reductions in both peak and RMS tracking error, as well as settling time, for complex motion patterns.

An approach to viscoelastic characterization of dispersive media by inversion of a general wave propagation model

In the characterization of elastic properties of tissue using dynamic optical coherence elastography, shear/surface waves are propagated and tracked in order to estimate speed and Young’s modulus. However, for dispersive tissues, the displacement pulse is highly damped and distorted during propagation, diminishing the effectiveness of peak tracking approaches, and leading to biased estimates of wave speed. Further, plane wave propagation is sometimes assumed, which contributes to estimation errors. Therefore, we invert a wave propagation model that incorporates propagation, decay, and distortion of pulses in a dispersive media in order to accurately estimate its elastic and viscous components. The model uses a general first-order approximation of dispersion, avoiding the use of any particular rheological model of tissue. Experiments are conducted in elastic and viscoelastic tissue-mimicking phantoms by producing a Gaussian push using acoustic radiation force excitation and measuring the wave propagation using a Fourier domain optical coherence tomography system. Results confirmed the effectiveness of the inversion method in estimating viscoelastic parameters in both the viscoelastic and elastic phantoms when compared to mechanical measurements. Finally, the viscoelastic characterization of a fresh porcine cornea was conducted. Preliminary results validate this approach when compared to other methods.

In-Silico UHPLC Method Optimization for Aglycones in the Herbal Laxatives Aloe barbadensis Mill., Cassia angustifolia Vahl Pods, Rhamnus frangula L. Bark, Rhamnus purshianus DC. Bark, and Rheum palmatum L. Roots.

For the European Pharmacopoeia (Ph. Eur.) herbal monograph draft of Cassia angustifolia Vahl. and Cassia senna L. leaves and pods, a safety limitation of aloe-emodin and rhein was proposed, due to toxicological concerns. A quantitative, analytical method of the anthraquinone aglycones in all Ph. Eur. monographed herbal laxatives is of interest. A rational method development for the aglycones aloe-emodin, rhein, emodin, chrysophanol, and physcion in five herbal drugs was realized by using 3D chromatographic modelling (temperature, solvent, and gradient time) and design of experiment (DOE) software (DryLab® 4). A methodical approach suitable for the challenging peak tracking in the chromatograms of the herbal drugs in dependence on the changes in the chromatographic conditions is described by using a combination of mass spectroscopy (MS) data (UHPLC-QDa), UV/Vis-spectra, and peak areas. The model results indicate a low robust range and showed that with the selected chromatographic system, small interferences could not be averted. The separation achieved shows a pure UV/Vis spectrum for all aglycones except for chrysophanol in Aloe barbadensis and emodin in Cassia angustifolia fruit. A gradient with the best resolution of the aglycones in all five drugs is proposed, and its suitability demonstrated for the quantification of aglycones in these herbal drugs.

Review and Analysis of Peak Tracking Techniques for Fiber Bragg Grating Sensors.

Fiber Bragg Grating (FBG) sensors are among the most popular elements for fiber optic sensor networks used for the direct measurement of temperature and strain. Modern FBG interrogation setups measure the FBG spectrum in real-time, and determine the shift of the Bragg wavelength of the FBG in order to estimate the physical parameters. The problem of determining the peak wavelength of the FBG from a spectral measurement limited in resolution and noise, is referred as the peak-tracking problem. In this work, the several peak-tracking approaches are reviewed and classified, outlining their algorithmic implementations: the methods based on direct estimation, interpolation, correlation, resampling, transforms, and optimization are discussed in all their proposed implementations. Then, a simulation based on coupled-mode theory compares the performance of the main peak-tracking methods, in terms of accuracy and signal to noise ratio resilience.

Bat algorithm based maximum power point tracking for photovoltaic system under partial shading conditions

This paper presents a maximum power point tracking (MPPT) method for photovoltaic system under partial shading conditions using bat algorithm (BA). The bat algorithm is a swarm intelligence based method which was inspired by the echolocation behaviour of bats. BA have a high accuracy in the global optimisation and it can provide good dynamic performance and very quick convergence rate by automatically switching between exploration and exploitation stages during the MPPT process. To verify the performance of the proposed method, several simulations have been carried out in Matlab/Simulink environment for various shading patterns. The simulations results highlight the accuracy of the proposed scheme for optimal management of the energy available at the output of the photovoltaic panels. In addition, the comparison with the P&O and the PSO methods shows that the proposed method outperforms them in term of global search ability and dynamic performance. To verify the practical implementation of the proposed method, a modular reconfigurable architecture is designed using very high speed integrated circuit hardware description language (VHDL) and implemented on Xilinx Virtex-5 (XC5VLX50-1FFG676) Field Programmable Gate Array (FPGA). The use of FPGA for designing the MPPT controller provides high performance, increases the robustness and makes the hardware implementation more flexible. The algorithm is tested in real time application on a buck-boost converter using a real photovoltaic panel. Experimental results confirm the efficiency of the proposed method in the global peak tracking and its high accuracy to handle the partial shading.

On-Chip Photovoltaic Power Harvesting System With Low-Overhead Adaptive MPPT for IoT Nodes

Extracting maximum power from a photovoltaic (PV) harvester with minimum power transfer loss is one of the primary design goals of an energy processing circuit. This paper presents a fully integrated PV power harvesting system with a low-overhead adaptive maximum power point tracking (MPPT) scheme for Internet-of-Things (IoT) nodes. The proposed scheme tracks the MPPs within 12 $\mu \text{s}$ by utilizing an inherent negative feedback loop, within a tracking error of 0.6%. The tracking range has been improved by ~57% using a current-starved voltage-controlled oscillator (CS-VCO) instead of a polynomial VCO. The overhead area and power consumed by this tracking scheme are approximately 0.013% and 0.1%, respectively. Using commercially available solar cell of area 11.3 cm2, the proposed system can provide 833 $\mu \text{W}$ of power with a light intensity of 600 lx. The proposed energy processing circuit has been designed using 0.18- $\mu \text{m}$ CMOS technology node and the circuit simulations demonstrate that the proposed scheme can track maximum power point (MPP) under rapidly changing atmospheric conditions with a peak tracking efficiency of 99%.

A time-frequency domain approach of heart rate estimation from photoplethysmographic (PPG) signal

Objective- Heart rate monitoring using wrist type Photoplethysmographic (PPG) signals is getting popularity because of construction simplicity and low cost of wearable devices. The task becomes very difficult due to the presence of various motion artifacts. The objective is to develop algorithms to reduce the effect of motion artifacts and thus obtain accurate heart rate estimation. Methods- Proposed heart rate estimation scheme utilizes both time and frequency domain analyses. Unlike conventional single stage adaptive filter, multi-stage cascaded adaptive filtering is introduced by using three channel accelerometer data to reduce the effect of motion artifacts. Both recursive least squares (RLS) and least mean squares (LMS) adaptive filters are tested. Moreover, singular spectrum analysis (SSA) is employed to obtain improved spectral peak tracking. The outputs from the filter block and SSA operation are logically combined and used for spectral domain heart rate estimation. Finally, a tracking algorithm is incorporated considering neighbouring estimates. Results- The proposed method provides an average absolute error of 1.16 beat per minute (BPM) with a standard deviation of 1.74 BPM while tested on publicly available database consisting of recordings from 12 subjects during physical activities. Conclusion- It is found that the proposed method provides consistently better heart rate estimation performance in comparison to that recently reported by TROIKA, JOSS and SPECTRAP methods. Significance- The proposed method offers very low estimation error and a smooth heart rate tracking with simple algorithmic approach and thus feasible for implementing in wearable devices to monitor heart rate for fitness and clinical purpose.