Output Filter Research Articles

Design of a Univariate Dual‐Loop Voltage System Based on the Multisampling Method

ABSTRACTThis study presents an innovative control framework designed for voltage source inverters (VSIs) equipped with LC output filters. The objective of this control framework is to reduce delay and suppress aliasing effects by employing multisampling techniques and implementing repetitive filtering methods. The multisampling approach can significantly reduce control delays, thereby enhancing both the bandwidth and stability margins of the system. The implementation of multisampling techniques for inverter voltage can enhance dynamic performance. However, it may introduce high‐frequency ripples in the control loop, resulting in low‐order aliasing harmonics and ultimately leading to output voltage distortion. To address this issue, a multiple notch filter with minimal phase delay is employed suppress aliasing. The optimal parameters of the system are determined by evaluating the filter specifications, filtering effectiveness, output voltage ripple, and overall system performance, while also considering the actual filtering requirements and circuit size. Its effectiveness and performance are carefully verified by experimental results.

Simultaneous state and fault estimation for a class of nonlinear Markov jump systems by distributed fault-tolerant observers

This paper investigates the estimation problem of a class of nonlinear Markov jump systems with actuator and sensor faults. The main goal is to design a distributed fault-tolerant observer to estimate system states and actuator faults simultaneously. Firstly, a novel distributed observer network is constructed to compensate the missing information of unobservable nodes of the system. Next, a class of new redundant sensors are set up on each distributed observer node to obtain more output measurement samples. More importantly, when some of the mentioned sensors occur faults, an index of sensor heath level is constructed to characterize the quality of the faulty sensor information. Further, a novel algorithm is designed to mask low quality output information and filter out relatively healthy one automatically. Based on the selected healthy output information, the system state and actuator fault are estimated in the case of sensor failure. Finally, an example is provided to demonstrate the effectiveness of the proposed method.

Efficient rectifier with wide input power range for 5G applications

This article presents three efficient rectifiers for radio frequency energy harvest-ing (RFEH) systems operating at the fifth generation (5G) band (3.5 GHz). Eachrectifier operates at various input power levels (high, low, and across a widepower range). The high and low-power rectifiers feature a single serial topologyusing HSMS-2860 and SMS-7630 Schottky diodes, respectively, along with mi-crostrip lines to implement the input and output filters and the impedance match-ing network. At an radio frequency (RF) power level of 15 dBm, the high-powerrectifier harvests 67.4% to direct current (DC) power with a 300Ωload resistorand an output voltage of 2.5V. The low-power rectifier achieves its maximumpower conversion efficiency (PCE) at -2 dBm, reaching 45% efficiency with a1200Ωload. The rectifier with a extended input power range comprises twobranches of subrectifiers functioning at both high and low power levels. De-pending on the power level, the considered subrectifier harvests radio frequencypower into DC power, while the other subrectifier is deactivated. Across a powerspan of 32.5 dB (ranging from -13 to 19.5 dBm), the rectifier maintains an effi-ciency above 30%. The proposed rectifiers are efficient and suitable for imple-mentation in 5G-enabled RFEH systems.

Inverse Class‐E power amplifier with broadband capability at different switch‐off duty ratio

AbstractThe paper explores the investigation of an inverse Class‐E amplifier featuring a series output filter across various switch‐off duty ratios D. Analysis of different duty ratios as a design parameter reveals their impact on peak switch voltage, output power capability, and maximum operating frequency. Notably, it is demonstrated that adjusting the D ratio affects these parameters, with specific emphasis on achieving a maximum normalized switch voltage lower than 2 and an output power capability exceeding 0.1 for D = 0.7. Furthermore, the paper considers both parasitic shunt capacitance and series inductor in the load network, a departure from previous works that solely focused on the series inductor. The proposed circuit is highlighted for its ease of implementation compared with conventional reactance compensation circuits employing parallel resonant circuits, which are challenging to form directly. An innovative approach is introduced to showcase the broadband performance of the inverse Class‐E amplifier. The measured drain efficiency and output power versus input power at 430 MHz are 82% and 45.3 dBm, respectively. A similar performance can be achieved within the frequency range of 380–600 MHz by proper tuning at saturated power. The measurement results demonstrate a maximum high power‐added efficiency (PAE) of 79% and drain efficiency of 82% within this frequency range, accompanied by a gain exceeding 12.0 dB and output power surpassing 44 dBm.

A buck converter with adaptive on-time control based on ripple compensation

Abstract This paper proposes a novel adaptive on-time control Buck converter based on ripple compensation. By superimposing high-sampling-precision inductor current ripples on the feedback loop, the ripple of the feedback voltage is enhanced. This approach effectively addresses subharmonic oscillations observed in ripple-controlled Buck converters, particularly when the equivalent series resistance (ESR) of the output filter capacitor is low. The proposed control method enhances system stability and exhibits excellent transient response characteristics. Simulations using Simplis demonstrate high accuracy in the output voltage (with ripples as low as 2mV). The comparative analysis establishes the superior merit of this design.

Unknown input observer based neuro-adaptive fault-tolerant control for vehicle platoons with sensor fault and output quantization

Sensor fault and output quantization are common issues acting on vehicle platoon, and they may lead to performance deterioration, instability and even insecurity of the platoon. Therefore, this paper investigates the fault-tolerant control (FTC) problem of vehicle platoons with regard to the above two issues. Considering the probabilistic sensor fault and quantized measurement signals, an unknown input observer (UIO) based fault detection algorithm with adaptive threshold is developed for sensor health status monitoring. Then, an augmented vehicle platoon model is constructed by introducing a low-pass output filter, and a robust UIO is established for state reconstruction. Based on the above results, a fault-tolerant control scheme is exploited by employing the back-stepping control method and adaptive radial basis function neural network (RBF NN) approximation technique, which is proved to be capable of achieving the time-domain string stability (TSS) of vehicle platoons in the presence of sensor fault and output quantization. Simulation results demonstrate the effectiveness of the proposed algorithms.

Developing and Evaluating the Operating Region of a Grid-Connected Current Source Inverter from Its Mathematical Model

Grid-connected power inverters are indispensable in modern electrical systems, playing a pivotal role in enhancing the integration of renewable energies into power grids. Their significance, primarily when functioning as grid-forming inverters, extends to maintaining the grid’s inertia and strength—a distinct advancement over traditional grid-following operations. As grid-forming inverters, these devices emulate the characteristics of synchronous generators and can act as robust voltage sources, providing essential ancillary services. This behavior is particularly relevant when integrating energy storage systems on the converters’ direct current side. Among the various inverter topologies, the current source inverter (CSI) has emerged as a promising yet underexplored alternative for grid-forming applications. CSIs, when paired with their AC output filters, can effectively operate as voltage sources, utilizing control strategies that facilitate the integration of renewable energies into the electrical system. Their design inherently manages output current fluctuations, reducing the need for restrictive current limitations or additional protective measures. This paper examines the operational region of CSIs, obtained through detailed modeling, to explore their advantages, challenges, and potential for enhancing grid-connected systems. Analyzing the operating region from the converter model verifies the limits of where the converter can operate in a plane of active and reactive powers. For a small prototype model operating with 7 amperes in DC and 120 V in AC, it is possible to supply or absorb active power exceeding 1000 W and manage maximum reactive power values around 500 VAr, as determined by its operating region. Simulations also confirm that small changes in the control reference, as little as 5%, towards the region’s right limits cause significant oscillations in the dynamic control responses. This research aims to deepen our understanding of CSIs’ operational capabilities and highlight their unique benefits in advancing grid-connected systems and promoting the integration of renewable energy using this technology.

Focusing On Fine-Tuning

Those who design and deploy generative AI models, such as Large Language Models like GPT-4 or image diffusion models like Stable Diffusion, can shape model behavior in four distinct stages: pretraining, fine-tuning, in-context learning, and input and output filtering. The four stages differ among many dimensions, including cost, access, and persistence of change. Pretraining is always very expensive and in-context learning is nearly costless. Pretraining and fine-tuning change the model in a more persistent manner, while in-context learning and filters make less durable alterations. These are but two of many such distinctions reviewed in this Essay. Legal scholars, policymakers, and judges need to understand the differences between the four stages as they try to shape and direct what these models do. Although legal and policy interventions can (and probably will) occur during all four stages, many will best be directed at the fine-tuning stage. Fine-tuning will often represent the best balance between power, precision, and disruption of the approaches.

Voltage and frequency control of microgrid in presence of micro-turbine interfaced to matrix converter

The active and reactive load changes have a significant impact on voltage and frequency. In this paper, in order to stabilize the microgrid (MG) against load variations in islanding mode, the active and reactive power of all distributed generators (DGs), including energy storage (battery), diesel generator, and micro-turbine, are controlled. The micro-turbine generator is connected to MG through a three-phase to three-phase matrix converter, and the droop control method is applied for controlling the voltage and frequency of MG. In addition, a method is introduced for voltage and frequency control of micro-turbines in the transition state from grid-connected mode to islanding mode. A novel switching strategy of the matrix converter is used for converting the high-frequency output voltage of the micro-turbine to the grid-side frequency of the utility system. Moreover, using the switching strategy, the low-order harmonics in the output current and voltage are not produced, and consequently, the size of the output filter would be reduced. In fact, the suggested control strategy is load-independent and has no frequency conversion restrictions. The proposed approach for voltage and frequency regulation demonstrates exceptional performance and favorable response across various load alteration scenarios. The suggested strategy is examined in several scenarios in the MG test systems, and the simulation results are addressed.

Low/Middle-Frequency Positive External- Damping Design Under Self-Stability Constraint for Inner Control Loop of Grid-Forming Converters

The inner voltage control loop and inductor current active damping loop of grid-forming (GFM) converters perform the output voltage control and filter resonance damping, and their stability design has been widely developed in the literature. However, the equivalent external-damping characteristics have not been fully explored. In this paper, the analysis shows that inappropriate design focusing only on self-stability would lead to negative external-damping in a wide low/middle-frequency band when LC resonant frequency is greater than one-sixth sampling frequency and less than one-third sampling frequency, which may cause system instability when interacting with loads or grids. Therefore, a low/middle-frequency positive external-damping design method under self-stability constraint is proposed for inner control loop of GFM converters. Detailed design process is presented with simple implementation. The key feature is the use of negative proportional gain of voltage controller. Through the proposed design method, the GFM converters can improve system damping capability, which is beneficial to promoting large-scale integration of distributed generation systems based on power electronics. Simulation and experimental results are finally provided to verify the feasibility and effectiveness of the design method.

Modeling and control of a single-phase grid-tied medium-frequency isolated converter for active and reactive power management in photovoltaic applications

A single-phase photovoltaic converter formed by the full-bridge dc–dc converter with a capacitive output filter and a grid-tied full-bridge inverter is studied in this paper. The switched model, the average model based on a modified-conventional approach, and the linear state-space model of the dc stage operating in discontinuous conduction mode are presented and compared with the behavior of the state variables obtained from a simulator. A duty-ratio constraint is obtained from the modified average model, which is eliminated by expressing its dependency on the control and the state variables. In addition, the modeling of the ac stage is carried out in the dq reference frame. Linear controllers are designed to guarantee the maximum power point tracking, the regulation of the dc-link voltage, the injection of the active power generated, and the reactive power management as an ancillary function. The controllers proposed, according to the transfer functions derived from the linear models, are validated via simulation for a 1.41 kVA converter.

Adaptive output-feedback control for switched nonlinear systems with measurement sensitivity based on double-side event-triggering mechanisms

This article concentrates on the problem of adaptive event-triggered control with double-side event-triggering mechanisms for a family of switched nonlinear systems with measurement sensitivity. In order to circumvent the negative effect of intermittent transmission and sensor measurement sensitivity on the output, an extended system is constructed by introducing a first-order output filter. Then, an input-driven neural switched observer is designed to estimate unmeasurable system states. To deal with the mutual interaction between the triggering and the switching mechanisms and their negative effect on the positive lower bound of inter-execution intervals, an incremental compensation is incorporated in the event-triggering mechanism (ETM) at the output sensor side. At last, a novel event-triggered control scheme built on both sides of the controller and output is proposed, which exhibits superior efficacy compared to the one-side event-triggered control scheme. By using the methods of the average dwell time (ADT) and the backstepping design, it is guaranteed that all signals of the switched closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and the Zeno phenomenon is excluded. The efficacy of the proposed methodology is validated by using a numerical simulation and a one-link robot system.

Improving Low-Frequency Digital Control in the Voltage Source Inverter for the UPS System

Today voltage source inverters (VSIs) operate with high switching frequencies (let us assume higher than 50 kHz) owing to the fast Si (Silicon) or SiC (Silicon Carbide) switching transistors. However, there are some applications, e.g., with slower switches (e.g., IGBT—Isolated Gate Bipolar Transistor) or when lower dynamic power losses are required when the switching frequency is low (let us assume about 10 kHz). The resonant frequency of the output filter is usually below 1 kHz. The measurements of Bode plots of the measurement traces of various microprocessor-controlled VSIs show that in this frequency range, the characteristics of these channels can be simply approximated through two or three switching periods delay. For the high switching frequency, it is not noticeable, but for the low frequency it can cause some oscillations in the output voltage. One of the solutions can be to use the predictor of the measured state variables based on the full-state Luenberger observer or the linear Kalman filter. Both solutions will be simulated in MATLAB/Simulink and the chosen one will be tested in the experimental VSI. The research aims to omit delays in the measurement channels for the low switching frequency by using the predictions for the measured state variables and finally increasing the gains of the controller to decrease the output voltage distortions.

N77 Radio Frequency Power Amplifier Module for 5G New-Radio High-Power User Equipment Mobile Handset Applications

This paper presents a highly efficient 5G New-Radio (NR) RF power amplifier module (PAM). The n77 PAM consists of a high-voltage differential-topology 2 μm GaAs HBT power amplifier, a CMOS controller, a silicon-on-insulator (SOI) switch, an integrated passive device (IPD) bandpass filter, a low-noise amplifier (LNA), and a bi-directional coupler. This PAM generates a saturation output power of 32.7 dBm including the loss of the SOI switch and output filter. The designed n77 PAM is tested with a commercial envelope tracker IC (ET-IC). The designed PAM with an ET-IC achieves an ACLR of −37 dBc at a 27 dBm output power with a DFT-s-OFDM QPSK 100 MHz NR signal and saves a dc power consumption of 950 mW compared to the APT mode. For the CP-OFDM 256QAM with the most stringent EVM requirements, it achieves an EVM of 1.22% at 23 dBm and saves 640 mW compared to the APT mode.

Sizing and experimental validation of a selfsync droop-based grid forming inverter with direct voltage control

Currently, the transient stability of the grid is mainly ensured by the inertial behavior of its synchronous generators. The increase of renewable energy sources connected to the grid through grid following (GFL) inverters is severely affecting the inertia of the grid and its stability is beginning to be compromised. Moreover, in case of a large disturbance, these renewable energy sources disconnect from the grid by design, thus exacerbating the problem. The idea of mimicking the behavior of synchronous generators in an inverter and participating in the grid stability gave birth to the so-called grid forming (GFM) inverters. This implies a change in paradigm from current controlled sources (GFL) to voltage-controlled sources (GFM). Despite known stability issues in current controlled converters, a typical approach to GFM converters with LCL output filters is based on cascaded current and voltage control loops. An internal current loop controls the inverter’s output currents and an external voltage loop controls the filter capacitors’ voltages. The problem is that this solution is complex and is also marginally stable. Alternatively, in this paper we explore a direct voltage control, which is based on droop control. The proposed control’s output is used for the direct control of the inverter’s output voltage in amplitude and phase. A complete analysis is performed, and a method is proposed to determine the appropriate control parameters as well as the sizing of the inverter components. Finally, an experimental setup is presented and the effectiveness of the proposed method is shown in simulations as well as in real-life experiments.

Two Types of Asymmetric Switched-Capacitor Five-Level Single-Phase DC-AC Inverters for Renewable Energy Applications

Two types of asymmetric switched-capacitor five-level single-phase DC-AC inverters are presented based on the clamping half-bridge circuit and the output half-bridge circuit. Furthermore, the switches of the two proposed circuits can be driven by half-bridge gate drivers and can be modularized. Moreover, the detailed analysis of the operation principle, design of clamping capacitor and output filter of these two inverters are presented. Finally, the feasibility and validity of the proposed structures are verified by PSIM-simulated results and experimental results using FPGA as the control kernel, respectively.

Incorporating sufficient physical information into artificial neural networks: A guaranteed improvement via physics-based Rao-Blackwellization

The concept of Rao-Blackwellization is employed to improve predictions of artificial neural networks by physical information. The error norm and the proof of improvement are transferred from the original statistical concept to a deterministic one, using sufficient information on physics-based conditions. The proposed strategy is applied to material modeling and illustrated by examples of the identification of a yield function, the identification of driving forces for quasi-brittle damage and rubber experiments. Sufficient physical information is employed, e.g., in the form of invariants, parameters of a minimization problem, isotropy and differentiability. It is proven how intuitive accretion of information can yield improvement if it is physically sufficient, but also how insufficient or superfluous information can cause impairment. Opportunities for the improvement of artificial neural networks are explored in terms of the training data set, the networks’ structure and output filters. Even crude initial predictions are remarkably improved by reducing noise, overfitting and data requirements.

Ripple Minimization in a Quadratic Boost Converter: Software vs. Hardware solutions

In this work, the authors have studied a quadratic boost DC-DC converter to reduce its ripple in the output voltage and the input current. This aim has been obtained by implementing two different solutions: the hardware solution consists on the use of coupled inductors and a notch output filter, the software solution is based on a random PWM and uses uncoupled inductors. The two solutions show a different impact on the output voltage and in the input current ripple. The performance of proposed solutions is evaluated and compared by simulation analysis both in time and frequency domain.

Comparison of the effect of output filters on the total harmonic distortion of line current in voltage source line converter - simulation study.

Two different output filter topologies are considered, namely the LCL- and L+LC-filter. The space vector modulation (SVM) is used to control the power switches of the converter. Design methods for both filter types are proposed. The methods are used to dimension the filter components. The performances of the filters designed are verified by simulations to meet the given line current total harmonic distortion (THD) requirement. The study reveals that the LCL-filter is more effective a filter topology in attenuating line current harmonic components than the L+LC-filter.

Distributed Controller for the Parallel Operation of Power Converters With Small Output Filters

Distributed Controller for the Parallel Operation of Power Converters With Small Output Filters