Performance Of Filter Research Articles

A Gaussian approximation filter for nonlinear systems with compound noises

In practical applications, measurements may contain many different noise components due to complex environments and other factors. The Gaussian approximation filter, constrained by its requirement for Gaussian characteristics in measurement noises, faces challenges in obtaining a satisfactory filtering performance under compound noise environments. In this article, an improved Gaussian approximation filter is designed for nonlinear systems with compound measurement noises. Hypothesis tests on the prior and posterior residuals are designed to identify the types of noise present in the system. Subsequently, a posterior residual-based adaptive compensation is proposed to mitigate the adverse effects of compound noise on the Gaussian approximation filter. Moreover, it is demonstrated that when the measurement acceptance rate exceeds a certain critical threshold, the estimation error remains bounded. Finally, the effectiveness of the proposed algorithm and analysis is validated through simulations in the context of target tracking.

Electric-field activating on-surface tailored (OST) coarse polyester fibers for efficient airborne particle removal: Interfacial morphologies and electrical response

Fibrous filtration is the most-used method for indoor particulate matter (PM) removal. The filtration performances are governed by filters’ intrinsic geometries, displaying the tradeoff among efficiency, resistance, and lifespan. In this contribution, we provided a chemically-synthesized strategy to improve the performance of coarse filters while preserving their ultralow initial resistances. After elucidating PM-fiber interactions, the fibrous interfacial nano-morphologies were tailored by different dielectric coatings based on commercially-available substrates. Activated by fiber polarizing, the tuned morphologies with ∼100 nm surface roughness and enhanced electrostatic potential are considered the drivers of boosted filtration efficiency. In practice, a 10-mm-thick polydopamine (PDA)-MnOx coated polyester filter possessed an improved efficiency of 97.7 % for 300–500 nm particles, and the ultralow resistance of 11.2 Pa at 0.5 m/s filtration velocity. The strong surface adhesion facilitated long-term efficiency of 95.6 % in a continuous 25-day period without any decay. The nanoscale coatings, which were just one-thousandth in thickness of the fiber gaps, enabled more than 50-fold improvement of the filters’ quality factor. We further established dimensionless factors to evaluate the cost-performance effect. We expect the strategy and techniques can pave the way to better understand electrostatic air filtration, being competitive candidates in the air filtration community.

Low-permittivity BaCuSi4O10-based dielectric Ceramics: An available solution to connect low temperature cofired ceramic technology and millimeter-wave communications

Low temperature cofired ceramic (LTCC) technology can serve for next-generation millimeter-wave electronic products to bring the advantages of integration, miniaturization and excellent high-frequency performance. However, challenges such as the performance of LTCC powders, quality of green tapes and Ag co-firing compatibility still need to be addressed for the application of LTCC technology. In this work, a systematic investigation from powder modification, LTCC process to filter design were carried out based on novel BaCuSi4O10-based dielectric ceramics. Multiple effects in terms of suitable sintering temperature (840 ℃ suit for Ag co-firing), low-permittivity (εr ∼ 5.7) and good thermal stability (temperature coefficient of resonant frequency ∼ − 27 ppm/℃, thermal expansion coefficient ∼3.9 ppm/℃) were achieved by introducing Li-B-Si glass and LiF composite additive. The origin of dielectric response of this LTCC system were discussed using the FIR reflectivity spectrum and THz-TDS. After optimizing the tape casting process for the LTCC powder, green tapes with uniform thickness, smooth surface and no cracking were obtained. Furthermore, the bandpass and lowpass filters exhibited a high level of filtering performance own to excellent dielectric properties and low surface roughness of the LTCC. Consequently, the BaCuSi4O10-based dielectric ceramic is an attractive candidate as LTCC technology expands into millimeter-wave communications.

LIDON: Loopback interconnect datacenter optical network

A loopback interconnect datacenter optical network (LIDON) is proposed for switching in datacenters with commercial devices. The intra- and inter-Pod switching in datacenters is accomplished with the Rack Expansion Module (REM) and the Loopback Interconnect Module (LIM) operating collectively. By developing the new functions of diagnostic ports of a wavelength selective switch, LIDON boasts several features, such as high path diversity and robust tolerance. Moreover, the scale of LIDON can be expanded by the proposed scheme to support the flexible switching volume. The feasibility of dividing intra- and inter-Pod signals was demonstrated by the filtering performance experiments. The simulations of the task completion time (TCT) for different services bore witness to the robust fault tolerance of LIDON.

An optimized filter design approach for enhancing imaging quality in industrial linear accelerator.

The polychromatic X-rays generated by a linear accelerator (Linac) often result in noticeable hardening artifacts in images, posing a significant challenge to accurate defect identification. To address this issue, a simple yet effective approach is to introduce filters at the radiation source outlet. However, current methods are often empirical, lacking scientifically sound metrics. This study introduces an innovative filter design method that optimizes filter performance by balancing the impact of ray intensity and energy on image quality. Firstly, different spectra under various materials and thicknesses of filters were obtained using GEometry ANd Tracking (Geant4) simulation. Subsequently, these spectra and their corresponding incident photon counts were used as input sources to generate different reconstructed images. By comprehensively comparing the intensity differences and noise in images of defective and non-defective regions, along with considering hardening indicators, the optimal filter was determined. The optimized filter was applied to a Linac-based X-ray computed tomography (CT) detection system designed for identifying defects in graphite materials within high-temperature gas-cooled reactor (HTR), with defect dimensions of 2 mm. After adding the filter, the hardening effect reduced by 22%, and the Defect Contrast Index (DCI) reached 3.226. The filter designed based on the parameters of Average Difference (AD) and Defect Contrast Index (DCI) can effectively improve the quality of defect images.

Forecasting the Remaining Useful Life of Filters in Nuclear Power Plants

To function effectively, nuclear power plants rely on the effective filtration of air, water, and process fluids, examples of which include inlet sea water, reactor coolant, plant drinking water, and moderator purification. Filtration assets degrade over time, which impairs their filtering performance and reduces the flow rate. Being able to determine the remaining useful life (RUL) of a filter could result in benefits, particularly when moving from a time-based to a condition-based maintenance strategy that would optimize the filter replacement procedure and reduce early replacement of filters that are still fit for purpose. For many filter applications, a time-based strategy is sufficient. For strategically important assets, such as fueling machines, there are benefits to be gained from the development of predictive maintenance strategies. In this paper, we propose a predictive condition-based strategy using differential pressure data as a proxy for filter health. The key objective in this work was the creation of a model that could predict a filter asset RUL. The differential pressure for 7 to 14 days is predicted by a heuristic-based regression model of the history of each filter. This approach has been demonstrated using a civil nuclear generation application but could be applied to wider applications. While this model is still undergoing on-site evaluation, it has been estimated that there will be an operationally significant lifetime cost reduction.

PM reduction performance according to filter grade and diffuser position in a school classroom

Ventilation performance for indoor air quality (IAQ) in schools has emerged as an important social issue due to the high concentrations of particulate matter (PM). The PM reduction performance is analyzed according to filter grade and the location of return diffusers, upper and floor return, selected based on indoor airflow distribution. Performance evaluation has been experimentally analyzed in the full-scale school environmental performance test-bed equipped with a fan filter unit (FFU). Through the experimental measurements in the classroom, it is found that the PM reduction time of the floor return is relatively shorter than that of the upper return. This is due to the increased ventilation efficiency by decreasing the stagnation flow inside the classroom. Although the supply air flowrate is relatively small at 800 cubic meter per hour (CMH), it has a PM reduction effect similar to 1200 CMH for all particle sizes due to the replacement of the conventional upper return with a floor return. Considering that the energy consumption of the Minimum Efficiency Reporting Value (MERV) 16 filter is approximately 1.7 times that of the MERV13 filter, a MERV13 filter is sufficient to demonstrate the performance of a MERV16 filter with the optimal installation of return diffusers.

Convex Optimization Based Design of FIR Filters for Reference Shaping

Abstract This paper explores design of Finite Impulse Response filters for controlling underdamped systems while dealing with uncertainties in model parameters. By setting magnitude constraints in the frequency domain within a convex programming framework, it ensures that dominant resonant modes are attenuated at the end of the maneuver, high-frequency unmodeled modes are not excited, and there is no inordinate accentuation of frequencies in the passband of the filter. A mobile platform with an attached flexible beam serves as a testbed to validate the designs for rest to rest maneuvers, demonstrating how different cost functions of error between the desired and optimized magnitude response affect the filter performance. The study also examines robustness in the notch area by shifting the natural frequencies of the system by shifting a tip mass at the free end of the beam. The total energy at the final maneuver time of the first three system modes is calculated as a vibration suppression metric and is used to compare established input shapers with the proposed Finite Impulse Response filters.

Robust adaptive non‐linear alignment algorithm for SINS/DVL integrated navigation system based on variational Bayesian

AbstractThe problem of dynamic attitude alignment for strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) integrated navigation has become a research hotspot. Underwater complex environment makes DVL output vulnerable to non‐Gaussian noise pollution, which makes it difficult to converge the SINS misalignment angle to within 1° based on analytical coarse alignment. This is to say, the performance of SINS fine alignment via Kalman filter will be degraded because the model of initial alignment exhibits non‐linearity. The inaccurate and/or unknown prior information of measurement noise statistical characteristics will also degrade the filtering performance. To ensure the SINS/DVL alignment accuracy under non‐linear, non‐Gaussian and uncertain conditions, this paper proposed a robust adaptive unscented Kalman filter (UKF) based on Variational Bayesian (VB) method (VBRAUKF). The proposed VBRAUKF improves the adaptability and robustness of UKF from the following two main aspects. Firstly, an adaptive estimation strategy for the measurement noise covariance is designed based on the VB algorithm, which can restrain the effect of inaccurate observation model and improve the adaptive ability of the filtering method. Secondly, an expansion factor is designed based on Mahalanobis distance algorithm, which can restrain the effect of non‐Gaussian noise and improve the robustness of the filtering method. The experimental results for the problem of the SINS/DVL dynamic alignment under mixed Gaussian noise and/or outlier conditions demonstrate the superiority of the proposed VBRAUKF over the traditional ones.

Mobile Sensor Path Planning for Kalman Filter Spatiotemporal Estimation.

The estimation of spatiotemporal data from limited sensor measurements is a required task across many scientific disciplines. In this paper, we consider the use of mobile sensors for estimating spatiotemporal data via Kalman filtering. The sensor selection problem, which aims to optimize the placement of sensors, leverages innovations in greedy algorithms and low-rank subspace projection to provide model-free, data-driven estimates. Alternatively, Kalman filter estimation balances model-based information and sparsely observed measurements to collectively make better estimation with limited sensors. It is especially important with mobile sensors to utilize historical measurements. We show that mobile sensing along dynamic trajectories can achieve the equivalent performance of a larger number of stationary sensors, with performance gains related to three distinct timescales: (i) the timescale of the spatiotemporal dynamics, (ii) the velocity of the sensors, and (iii) the rate of sampling. Taken together, these timescales strongly influence how well-conditioned the estimation task is. We draw connections between the Kalman filter performance and the observability of the state space model and propose a greedy path planning algorithm based on minimizing the condition number of the observability matrix. This approach has better scalability and computational efficiency compared to previous works. Through a series of examples of increasing complexity, we show that mobile sensing along our paths improves Kalman filter performance in terms of better limiting estimation and faster convergence. Moreover, it is particularly effective for spatiotemporal data that contain spatially localized structures, whose features are captured along dynamic trajectories.

A Modified Variable Power Angle Control for Unified Power Quality Conditioner in a Distorted Utility Source

The distorted supply voltage degrades the control performance of a unified power quality conditioner (UPQC). This problem causes incorrect calculations in the harmonic identification and reference signal generation processes. This paper proposes a modified harmonic identification of the UPQC. The reference compensating current calculation for the shunt active power filter (shunt APF) is developed using the sliding window with the Fourier analysis (SWFA) method. In addition, the variable power angle control (PAC) is applied to operate the reference signal generation of the series APF and the shunt APF of the UPQC. Under the distorted voltage and nonlinear load conditions, the proposed approach can provide accurate reference compensating signals and successfully share the load reactive power compensation between the shunt APF and the series APF. In this work, a three-phase, three-wire power system with linear and nonlinear loads was implemented. The proposed method was validated using the processor-in-the-loop technique on an eZdsp™ F28335 board and the MATLAB/Simulink program. The testing results indicated that SWFA has excellent filtering performance and enhances harmonic identification compared to the operation without any filter or with low pass filters (LPF). With the proposed approach, the percentage of total harmonic distortion of voltage and current could be maintained within the IEEE519-2022 standard, and the magnitude of the RMS voltage across the load was in the recommended range specified by ANSI C84.1-2016.

Terahertz dual-band bandpass filter based on spoof surface plasmon polaritons with wide upper stopband suppression

In this paper, a terahertz (THz) dual-band bandpass filter based on spoof surface plasmon polaritons (SSPPs) with wide upper stopband suppression is proposed. The filter utilizes two types of SSPP unit cells loaded on a double-sided quasi-SSPPs transmission line to achieve dual-band filtering responses and wide upper stopband suppression simultaneously. The performance and bandwidth of the filter's passbands can be adjusted by modifying the SSPP unit cells within the dual-band filtering part. The detailed design method is provided to enhance understanding of the operating principle of the presented filter. The simulation results of the designed THz filter demonstrate its excellent dual-band filtering performance. It features a wide stopband spanning from 0.91 to 1.45 THz with |S21| < -35 dB. To validate the proposed approach, a microwave filter with a similar design is implemented. Finally, the simulated and measured S-parameter responses of the filter are provided for comparison and evaluation.

Performance of pitcher-type POU filters for the removal of 75 PFAS from drinking water: comparing different water sources

This study presents a comprehensive assessment of the performance of popular pitcher-type point-of-use (POU) water filters to remove PFAS contaminants from tap waters. The evaluated filters, Brita (Elite and Standard), ZeroWater, Aquagear, and ClearlyFiltered, were tested for their efficacy in removing 75 targeted PFAS, total organic carbon (TOC), total dissolved solids (TDS), chloride, and sulfate from two Canadian tap waters with background Σ75 PFAS concentrations of 13 and 56 ng/L. Overall, the performances of the filters varied depending on the structure of the filter media, the water source, and the specific contaminants present. ZeroWater was the top performer in the case of total PFAS removal. The volume-weighted average removal of total PFAS after 160 L of filtration using Saint-Donat tap water was 99% for ZeroWater, 99% for ClearlyFiltered, 77% for Aquagear, and 20% for Brita (Elite). In the case of Montreal tap water, which had different water characteristics and lower total PFAS levels, the volume-weighted average removal for PFAS was ≈100% for ZeroWater, 96% for ClearlyFiltered, 60% for Aquagear, 48% for Brita (Elite), and 38% for Brita (Standard). Both laboratory and home tests involving ZeroWater filters yielded similar high-performance results using Montreal tap water. Although ZeroWater exhibited high PFAS removal (99%) in Saint-Donat water, TDS and TOC desorption and a significant drop in pH were observed after 80 L, a phenomenon which was explained by the higher total concentration of anions in this water. In contrast, no desorption was observed in Montreal tap water for TDS and TOC due to the lower concentrations of anions. The Aquagear filter demonstrated an unusual increase in concentrations of sulfate after the initial 20 L, which needs further evaluation. This study discusses individual filter performance, the influence of tap water characteristics, and the potential to meet the new NSF guidelines, which provides valuable insights for consumers seeking to choose an appropriate easy-to-use water filtration system to ensure safe and clean drinking water in different regions.

Combining descriptive and predictive modeling to systematically design depth filtration-based harvest processes for biologics.

Advances in upstream production of biologics-particularly intensified fed-batch processes beyond 10% cell solids-have severely strained harvest operations, especially depth filtration. Bioreactors containing high amounts of cell debris (more than 40% particles <10 µm in diameter) are increasingly common and drive the need for more robust depth filtration processes, while accelerated timelines emphasize the need for predictive tools to accelerate development. Both needs are constrained by the current limited mechanistic understanding of the harvest filter-feedstream system. Historically, process development relied on screening scale-down depth filter devices and conditions to define throughput before fouling, indicated by increasing differential pressure and/or particle breakthrough (measured via turbidity). This approach is straightforward, but resource-intensive, and its results are inherently limited by the variability of the feedstream. Semi-empirical models have been developed from first principles to describe various mechanisms of filter fouling, that is, pore constriction, pore blocking, and/or surface deposit. Fitting these models to experimental data can assist in identifying the dominant fouling mechanism. Still, this approach sees limited application to guide process development, as it is descriptive, not predictive. To address this gap, we developed a hybrid modeling approach. Leveraging historical bench scale filtration process data, we built a partial least squares regression model to predict particle breakthrough from filter and feedstream attributes, and leveraged the model to demonstrate prediction of filter performance a priori. The fouling models are used to interpret and provide physical meaning to these computational models. This hybrid approach-combining the mechanistic insights of fouling models and the predictive capability of computational models-was used to establish a robust platform strategy for depth filtration of Chinese hamster ovary cell cultures. As new data continues to teach the computational models, in silico tools will become an essential part of harvest process development by enabling prospective experimental design, reducing total experimental load, and accelerating development under strict timelines.

Research of electret air filter: A review

AbstractThe harmful effects of air pollution on humans are multifaceted and are closely linked to outbreaks of various infectious viruses. Thus, design of high‐performance air filters that are lightweight, flexible, and easy to prepare is urgent. The electret air filter can utilize the electrostatic force of charge to capture dust particles, making it efficient and convenient, which is highly favored by people. In this study, a summary of the research on electret filters for highly efficient air purification is presented. First, this study outlines the mechanisms of air filtration methods and discusses three factors that evaluate filter performance. The methods of manufacturing electret air filters are then presented, and the advantages and limitations of different methods are discussed. Then, electrification, including corona discharge, friction electrification, electrospinning, thermal electrification, and water electrification as methods, enhances the physical charge adsorption performance of materials, while the use of fluorinate polymer, non‐fluorinate polymer, and biobased polymer as functional substrates exhibits varying degrees of electrification effects. Different materials and manufacturing techniques give the filters additional advantages, such as being self‐degradable and antibacterial. Finally, the challenges that remain in the development of electret filters for use in air purification are also discussed in terms of material type and fabrication technology. It is expected that highly efficient air purification with low energy consumption can be achieved by electret filters with multifunctional capabilities.

Influence patterns of shear-thickening gel on overload transmission: a numerical simulation study

To address signal aliasing challenges encountered by smart munition fuzes during penetration and layer counting processes, this study employs shear-thickening gel (STG) as a cushioning protective material for accelerometers. Based on the SHPB test platform, the test is designed and the finite element numerical simulation is carried out. The thickness of the shear-thickening gel specimen is treated as a research variable, enabling a systematic analysis of its mechanical filtering effect on overload acceleration. Furthermore, a spring-damping physical model for the cushioning structure is established, facilitating a theoretical exploration of the filtering mechanism on the acceleration signal. Research findings indicate that within a certain frequency bandwidth, STG materials can effectively filter out high-frequency signals received by the accelerometer. Additionally, augmenting the thickness of STG materials has a positive impact on achieving superior filtering performance within the high-frequency range.

Bio-inspired gradient poly(lactic acid) nanofibers for active capturing of PM0.3 and real-time respiratory monitoring

The concept of bio-inspired gradient hierarchies, in which the well-defined MOF nanocrystals serve as active nanodielectrics to create electroactive shell at poly(lactic acid) (PLA) nanofibers, is introduced to promote the surface activity and electroactivity of PLA nanofibrous membranes (NFMs). The strategy enabled significant refinement of PLA nanofibers during coaxial electrospinning (∼40 % decline of fiber diameter), accompanied by remarkable increase of specific surface area (nearly 1.5 m2/g), porosity (approximately 85 %) and dielectric constants for the bio-inspired gradient PLA (BG-PLA) NFMs. It largely boosted initial electret properties and electrostatic adsorption capability of BG-PLA NFMs, as well as charge regeneration by TENG mechanisms even under high-humidity environment. The BG-PLA NFMs thus featured exceptionally high PM0.3 filtration efficiencies with well-controlled air resistance (94.3 %, 163.4 Pa, 85 L/min), in contrast to the relatively low efficiency of only 80.0 % for normal PLA. During the application evaluation of outdoor air purification, excellent long-term filtering performance was demonstrated for the BG-PLA for up to 4 h (nearly 98.0 %, 53 Pa), whereas normal PLA exhibited a gradually declined filtration efficiency and an increased pressure drop. Moreover, the BG-PLA NFMs of increased electroactivity were ready to generate tribo-output currents as driven by respiratory vibrations, which enabled real-time monitoring of electrophysiological signals. This bio-inspired gradient strategy opens up promising pathways to engender biodegradable nanofibers of high surface activity and electroactivity, which has significant implications for intelligent protective membranes.

Study on the active regeneration characteristics of DPF in diesel-methanol dual-fuel engine under different exhaust oxygen concentrations

This study proposes a method to control exhaust oxygen (O2) concentration by adjusting the intake throttle valve, achieving intake throttling, and reducing intake airflow. The impact of exhaust O2 concentration at the inlet of the diesel oxidation catalyst (DOC) the diesel particulate filter (DPF) performance during active regeneration in diesel engines is investigated. Experiments are conducted under methanol substitution rates (MSR) of 0% and 20% to investigate how different exhaust O2 concentrations affect the performance of the DOC and DPF during active regeneration. A comparative analysis of fuel consumption and cumulative CO2 emissions during DPF active regeneration under different exhaust O2 concentrations is performed. Research results indicate that decreasing exhaust O2 concentration reduces exhaust flow, raising DOC inlet temperature. This enhancement improves catalytic conversion efficiency, accelerating the rise in DPF inlet temperature. The average conversion efficiency of DOC to unburned methanol exceeds 98.07%. After initiating DPF active regeneration, O2 concentration sharply drops, leading to elevated CO2 emissions. As soot combustion advances, the required O2 diminishes, resulting in a gradual rise and eventual stabilization of O2 emissions. Economically and environmentally, irrespective of MSR (20% or 0%), there exists an optimal exhaust O2 concentration that minimizes effective regeneration time during DPF active regeneration, achieving minimal fuel consumption and the lowest CO2 mass emissions. This study offers theoretical support for optimizing energy-saving and emission-reduction processes during DPF active regeneration.

Design of a Sigma-Delta Analog-to-Digital Converter Cascade Decimation Filter

As the current mainstream high-precision ADC architecture, sigma-delta ADC is extensively employed in a wide range of domains and applications. This paper presents the design of a highly efficient cascaded digital decimation filter for sigma-delta ADCs, emphasizing the suppression of high folding band noise and the achievement of a flat passband. Additionally, this study addresses the critical balance between filter performance and power consumption. An inserting zero (IZ) filter is incorporated into a cascaded integrator comb (CIC) filter to enhance aliasing suppression. The IZ filter and compensation filter are optimized using the particle swarm optimization (PSO) algorithm to achieve greater noise attenuation and smaller passband ripple. The designed filter achieves a noise attenuation of 93.4 dB in the folding band and exhibits an overall passband ripple of 0.0477 dB within a bandwidth of 20 KHz. To decrease the power consumption in the filter design, polyphase decomposition has been applied. The filter structure is implemented on an FPGA, processing a 5-bit stream from a 64-times oversampling rate and third-order sigma-delta modulator. The signal-to-noise ratio (SNR) of the output signal reaches 91.7 dB. For ASIC design, the filter utilizes 180 nm CMOS technology with a power consumption of 0.217 mW and occupies a layout area of 0.72 mm2. The post-layout simulation result indicates that the SNR remains at 91.7 dB.

Improved performance of a shunt hybrid active power filter by a robust exponential functional link network-based nonlinear adaptive filter control to enhance power quality

This research article details the design and implementation of a nonlinear adaptive filtering (NAF) technique using an exponential functional link network (EFLN) for a shunt hybrid active power filter (SHAPF) control to solve the current-associated power quality issues on the utility side at the distribution level of electrical power systems. Separation of the fundamental component from the harmonics, achieving unity power factor operation, reducing the reactive power drawn from the source, balancing the currents during transients, and reduction of total harmonic distortion (THD) of the source current are the issues considered to resolve. The proposed technique solves these issues by generating the sinusoidal reference current and separating the fundamental current from the harmonics. When compared to conventional and existing adaptive filtering techniques such as least mean square (LMS), least mean fourth (LMF), and variable step size LMS (VSS-LMS), the proposed EFLN-NAF method excels in terms of speedy convergence, adaptability in noise-specific environments and reduced steady-state coefficient error. MATLAB/Simulink software is utilized to perform the simulations to examine the suggested strategy for the chosen SHAPF topology both in static and dynamic scenarios. For a 15 kW and 3kVAr requirement of the nonlinear load, simulation results proved that the designed PPF for 2kVAr is able to share the reactive power with the APF, thereby reducing its rating and cost. The proposed method of filtering has been proven to be fast converging with 0.049 s, and the THD in steady state is brought to 1.32 % in steady-state and to 3.77 % during transient conditions, which are under standard limits. A hardware prototype of the experimental setup is constructed at the laboratory scale with OPAL-RT (OP4510) as the controller. With an active and reactive power demand of 1.1 kW and 210VAr, the designed PPF supplies 110 VAr, whereas the rest is supplied by the APF. The practical THD in source current is observed to be 2.081 %, which meets the standards. The results from both simulations and experiments are validated, and the efficacy of the proposed technique in mitigating the aforementioned power quality issues is proved.