Minimum Phase Research Articles

Dual Control Strategy for Non-Minimum Phase Behavior Mitigation in DC-DC Boost Converters Using Finite Control Set Model Predictive Control and Proportional–Integral Controllers

Model Predictive Control (MPC) has emerged as a promising alternative for controlling power converters, offering benefits such as flexibility, simplicity, and rapid control response, particularly when short-horizon algorithms are employed. This paper introduces a system using a short-horizon Finite Control Set MPC (FCS-MPC) strategy to specifically address the challenge of non-minimum phase behavior in boost converters. The non-minimum phase issue, which complicates the control process by introducing an initial inverse response, is effectively mitigated by the proposed method. A Proportional–Integral (PI) controller is integrated to dynamically adjust the reference current based on the output voltage error, thereby enhancing overall system stability and performance. Unlike conventional PI-MPC methods, where the PI controller has an influence on the system dynamics, the PI controller in this approach is solely used for tuning the reference current needed for the FCS-MPC controller. The PI controller addresses small deviations in output voltage, primarily due to model prediction inaccuracies, ensuring steady-state accuracy, while the FCS-MPC handles fast dynamic responses to adapt the controller’s behavior based on load conditions. This dual control strategy effectively balances the need for precise voltage regulation and rapid adaptation to varying load conditions. The proposed method’s effectiveness is validated through a multi-stage simulation test, demonstrating significant improvements in response time and stability compared to traditional control methods. Hardware-in-the-loop testing further confirms the system’s robustness and potential for real-time applications in power electronics.

Experimental Study of Airfoil Aerodynamic Behavior under Oscillating Motion in Ground Effect

When a flying vehicle approaches a water or land surface, it induces changes in the fluid flow field pattern known as the "ground effect." This research analyzes the ground effect phenomenon, exploring its impact on aerodynamic coefficients and flow patterns around the NACA0012 airfoil in an incompressible subsonic regime under static and dynamic conditions with pitch movements. Numerical simulations and experimental testing in an incompressible subsonic wind tunnel were deployed. The flow field solution is derived from the Navier-Stokes equations, incorporating the Transition SST turbulence model. Initially, the impact of the ground effect phenomenon was investigated at varying distances from the surface in the static state. Subsequently, the airfoil underwent a sinusoidal pitching oscillation at each distance with a specified frequency and amplitude. This allowed for examining its aerodynamic characteristics over time. The static analysis results reveal alterations in the curve's behavior and pressure distribution on the airfoil surface at close distances to the surface. This is attributed to the ground effect phenomenon, which reduces lift force to a certain height and then increases. Dynamic analysis further demonstrates changes in lift coefficient oscillation amplitude. It also exhibits a minimum and maximum lift point phase difference as the airfoil approaches the surface.

Robust load frequency control in interval power systems via reduced-order generalized active disturbance rejection control

Abrupt load changes, structural discrepancies, and parametric uncertainties cause degraded performance of the high-order power systems. This situation creates a problematic endeavor while analyzing the performance of such high-order systems. Hence, a simple and efficient lower-order control methodology can be deployed to sort out the issues related to load frequency control (LFC) in such systems. This study resolves the LFC problem in parametric bounded power systems by developing a worst-case reduced-order generalized active disturbance rejection control (WRGADRC) method. The core concept of the proposed technique entails that a controller will perform well in nominal scenarios if it performs satisfactorily in worst-case conditions. Therefore, an interval system’s worst-case reduced-order model is first obtained from its different uncertain models; the reduced order controller is then designed using the GADRC technique. The proposed scheme is rigorously validated on various parametric bounded minimum and non-minimum phase single-area and multi-area power systems, instilling confidence in its ability to achieve minimum frequency deviation in multiple scenarios. The supremacy of the proposed scheme is highlighted over some well-established control techniques in the literature related to the LFC problem.

Optimal and simultaneous synthesis of fractional order QFT controllers and prefilters for non-minimum phase hydro power systems

Abstract Ideally, the operating frequency of the power units, working in parallel, must not deviate from its nominal value. However, due to the dynamic nature of the load, operating frequency varies throughout the day; thus, the control of governors in the prime movers is essential to balance out the demand, and prevent any frequency deviation. To address this, present study investigates the design of optimal and robust quantitative feedback theory based (QFT) controllers and pre-filters for single area load frequency control of hydro power systems. Hydropower system model considered in the present study features a right-hand side zero, thus exhibiting non-minimum phase; these characteristics make the control more challenging. Also, the work investigates the optimal design of the QFT controllers and prefilters simultaneously by automating the loop shaping procedure, which else follows a sequential manual process on Nichols charts. The proposed automation also empowers the control designer to predefine the controller structure. In the present work the design of fractional order QFT controllers and pre-filters is considered. The study also compares the proposed work with the methods proposed in the existing literature as well as the optimal controllers obtained using the time domain indices. The obtained results establishes that the developed fractional QFT controller offers good tracking, stability, and robustness to disturbances when compared to existing approaches. The proposed fractional order QFT controllers offer the elimination of the overshoot and the undershoot from the closed loop response of the system; outperforms the existing controllers in terms of disturbance rejection; offers 0% steady-state deviation, while providing improved phase margin (60.1°) for enhanced stability compared to existing controllers. Also, the proposed QFT-GA attains the ideal values for both the peak complementary sensitivity functions; thus, establishing excellent robustness. Also, the proposed controllers ensure adequate tolerance to frequency deviation in case of load change.

Statistical Study of the Occurrence of Coronal Holes in the Solar Corona During Solar Cycle 24

In this article we look at: (a) the occurrence of coronal holes as a function of the different phases of solar cycle 24, (b) the variability of the annual number of coronal holes from 2009 to 2019, (c) the distribution of polar and non-polar coronal holes, irrespective of the phase but also as a function of the different phases of the cycle. From the phase minimum to the descending phase of solar cycle 24, the occurrences of coronal holes observed on the solar disc are 38%, 24%, 9% and 29% respectively. The annual number of coronal holes observed on the solar disc does not always follow the expected evolution of the two components of the solar magnetic field and the annual number of sunspots. Regardless of the phase of the solar cycle, the majority of coronal holes, around 65%, are located in the polar regions. During the early and late phases of the solar cycle, polar coronal holes predominate, whereas during the ascending phase and phase maximum, non-polar coronal holes predominate. The number of polar coronal holes is highest during the minimum phase of the solar cycle and lowest during the maximum phase. During the phases of the solar cycle, coronal hole activity appears to be in phase opposition with sunspot activity. There is a fairly good correlation between variations in the number of polar coronal holes and the expected evolution of the poloidal component of the solar magnetic field.

A new forward‐flyback converter without right half plane zero

AbstractDue to its unique features, the flyback converter is widely used to convert DC to DC power. This converter has a non‐minimum phase (NMP) dynamic behavior, which is one of its most significant disadvantages. By changing the topology of the flyback converter to a forward‐flyback (FF) converter, the dynamic behavior of the converter can be minimum phase (MP) while the main advantages of the flyback converter such as isolation of the output from the input and simple topology are maintained. This article proposes an innovative FF converter topology by doubling the forward path and adding only one diode and one capacitor. In addition to better dynamic behavior, the proposed double FF (DFF) converter has the same advantages as the conventional FF converter. A new method is used to obtain the transfer function of the output voltage to the duty cycle of the proposed converter. The converter is designed in continuous conduction mode (CCM) with minimum phase dynamics. Finally, simulation and experimental results of both conventional FF and the proposed DFF converters are obtained and compared to validate the superiority of the proposed converter.

Prediction of Ionospheric Scintillations Using Machine Learning Techniques during Solar Cycle 24 across the Equatorial Anomaly

Ionospheric scintillation is a pressing issue in space weather studies due to its diverse effects on positioning, navigation, and timing (PNT) systems. Developing an accurate and timely prediction model for this event is crucial. In this work, we developed two machine learning models for the prediction of ionospheric scintillation events at the equatorial anomaly during the maximum and minimum phases of solar cycle 24. The models developed in this study are the Random Forest (RF) algorithm and the eXtreme Gradient Boosting (XGBoost) algorithm. The models take inputs based on the solar wind parameters obtained from the OMNI Web database from the years 2010–2017 and Pc5 wave power obtained from the Bear Island (BJN) magnetometer station. We retrieved data from the Scintillation Network and Decision Aid (SCINDA) receiver in Egypt from which the S4 index was computed to quantify amplitude scintillations that were utilized as the target in the model development. Out-of-sample model testing was performed to evaluate the prediction accuracy of the models on unseen data after training. The similarity between the observed and predicted scintillation events, quantified by the R2 score, was 0.66 and 0.74 for the RF and XGBoost models, respectively. The corresponding Root Mean Square Errors (RMSEs) associated with the models were 0.01 and 0.01 for the RF and XGBoost models, respectively. The similarity in error shows that the XGBoost model is a good and preferred choice for the prediction of ionospheric scintillation events at the equatorial anomaly. With these results, we recommend the use of ensemble learning techniques for the study of the ionospheric scintillation phenomenon.

Development and experimental validation of high-order sliding mode control for quadratic boost converters in fuel cell electric vehicles

The global energy evolution is at a critical juncture, necessitating an urgent transition towards clean and sustainable energy sources, notably green hydrogen, to combat climate change and the inevi-table depletion of fossil fuels. This transition is underscored by the emergence of fuel cell electric vehicles (FCEVs) as a promising solution for clean transportation, demanding advanced DC-DC power converter technologies to ensure their efficiency and reliability. This paper addresses the topic of control for the Quadratic Boost Converter, which presents a challenge due to its non-minimum phase characteristic and nonlinear nature. To tackle this, a nonlinear controller is developed using dual-loop control employing STA-SMC and Lyapunov theory as the control ap-proach. Simulation and experimental validation evaluate the controller's performance, testing ro-bustness against varying load currents and under time-varying reference voltages to assess its ef-fectiveness.

Analysis of nonminimum phase components of noise control filters in active noise control

In the active noise control (ANC), it is known that the optimal filter becomes a noncausal filter due to the effect of the nonminimum phase components of the secondary path. We have investigated how to make the causal optimal filter by replacing the nonminimum phase components with the frequency components of the primary path. Through the computer simulations, we have confirmed that this filter maintained some noise reduction performance and can be used as a quasi-optimal filter. In this paper, as another approach, we attempt to identify noncausal components using the pre-trained adaptive noise control filter. The nonminimum phase components of the secondary path exist in the frequency band below the lowest resonance frequency of the secondary loudspeaker. Based on this fact, we design a noise control filter by using band-limited white noise only with the low frequency components below the lowest resonance frequency in advance. Then, we design another adaptive noise control filter by using the band-limited white noise with high frequency components above the lowest resonance frequency. Finally, we combine these filters in the frequency domain. Through the computer simulations, we show the difficulty to handle the nonminimum phase components in the ANC system.

Recommendations on bioacoustical metrics relevant for regulating exposure to anthropogenic underwater sounda).

Metrics to be used in noise impact assessment must integrate the physical acoustic characteristics of the sound field with relevant biology of animals. Several metrics have been established to determine and regulate underwater noise exposure to aquatic fauna. However, recent advances in understanding cause-effect relationships indicate that additional metrics are needed to fully describe and quantify the impact of sound fields on aquatic fauna. Existing regulations have primarily focused on marine mammals and are based on the dichotomy of sound types as being either impulsive or non-impulsive. This classification of sound types, however, is overly simplistic and insufficient for adequate impact assessments of sound on animals. It is recommended that the definition of impulsiveness be refined by incorporating kurtosis as an additional parameter and applying an appropriate conversion factor. Auditory frequency weighting functions, which scale the importance of particular sound frequencies to account for an animal's sensitivity to those frequencies, should be applied. Minimum phase filters are recommended for calculating weighted sound pressure. Temporal observation windows should be reported as signal duration influences its detectability by animals. Acknowledging that auditory integration time differs across species and is frequency dependent, standardized temporal integration windows are proposed for various signal types.

Enhancing disturbance rejection in boost converter for CPL: A controller design approach with partial pole placement and approximate model matching

In DC microgrids, the cascade operation of the DC-DC converters leads to a constant power load fed by the boost converter, resulting in unstable behavior in addition to the non-minimum phase dynamics. An enhanced load disturbance rejection control scheme based on partial pole placement and an approximate model matching technique is proposed. This approach is inspired by the well-known direct synthesis method to achieve optimal load disturbance rejection performance. The effectiveness of the proposed control scheme has been validated through hardware implementation, demonstrating its capability in setpoint tracking and load disturbance rejection under variations in load power and input voltage. The robust stability of the suggested scheme has been investigated through the Kharitonov theorem and Monte-Carlo simulation, considering different performance matrices. The suitability of the presented scheme has been established by analyzing the comparative performance of recently reported works. The proposed controller reduces peak overshoot and settling time by ∼50%, handles system uncertainties up to 75%, and outperforms FOPID controllers tuned with particle swarm optimization, queen bee genetic algorithm, and chaos game optimization methods.

Maximum Likelihood Sequence Estimation Optimum Receiver Design with Channel Identification Based on Zero Distribution

In this paper, a novel maximum likelihood sequence estimation (MLSE) optimum receiver design is proposed to reduce the complexity of the conventional optimum receiver. We first propose a multipath channel classification method according to the zero distribution of the channel impulse response; that is, the multipath channel is divided into a minimum phase channel and a non-minimum phase channel. Then, an MLSE optimum receiver design with channel identification based on zero distribution is also proposed. In this design, the distribution of zero can be obtained directly by calculating the Z transform of the channel. Thus, the complexity is reduced. The number of the multiplication reduced is N(2N+1). In addition, 2N+1 memory units storing the autocorrelation sequence are reduced. The simulation results indicate that this channel classification method effectively represents the characteristics of the channel. Moreover, the MLSE optimum receiver proposed performs similarly and is less complex than the conventional one. The performance is greatly improved compared with the minimum mean square error (MMSE) equalizer.

Bias control for optical single-sideband transmitter based on single IQ modulator

The optical in-phase and quadrature modulator (IQM) is typically utilized as an optical single-sideband (SSB) transmitter for its simple structure and low cost. It requires the modulator biases to be slightly offset for generating the optical carrier. However, this poses significant challenges in the bias control circuits, as most off-the-shelf automatic bias control (ABC) modules are designed to stabilize the IQM at its carrier suppression point for coherent optical communication. In this paper, a novel arbitrary ABC scheme is proposed to stabilize the carrier-to-signal power ratio (CSPR) of an optical SSB signal over long-term operation. This scheme uses SSB rather than double-sideband (DSB) sinusoidal signals as the dither signals. It does not violate the minimum phase condition, thus avoiding performance penalties compared to the conventional ABC scheme in which the DSB dither signal is used. We also develop a closed-form expression to reveal the relationship between the control parameter in the ABC algorithm and the CSPR of the optical SSB signal. By this means, the optical SSB transmitter can automatically adjust its bias voltages and stabilize them at a given CSPR value. The experimental results with ∼80 Gb/s optical SSB signal show that our proposed ABC scheme is effective in stabilizing the bias of the IQM at any point and maintains the CSPR value of the optical SSB signal over hours. It is also shown that the proposed method leads to 1 dB improvement in the receiver sensitivity compared with the traditional ABC technique.

A Joint Active Damping Strategy Based on LCL-Type Grid-Connected Inverters for Grid Current Feedback and PCC Voltage Unit Feedforward.

The negative high-pass filter feedback of the grid current (NFGCF) can offer active damping for the LCL-type grid-connected inverter. Due to the control delay in digital control systems, this damping can cause the system to exhibit non-minimum phase behavior within specific frequency ranges. This study proposes a joint active damping approach that combines grid current feedback and the point of common coupling (PCC) voltage unit feedforward. The proposed method introduces a dynamic damping region that varies with grid impedance. By developing suitable damping loop control parameters, this region can span the entire frequency range, even exceeding the Nyquist frequency fs/2. The research results demonstrate that the proposed approach enhances robustness against variations in grid impedance and eliminates non-minimum phase behavior. Simulation and experimental outcomes validate the effectiveness of this joint active damping method.

Use of modified chitosan as bitumen modifier and its impact on rheological properties in bitumen modification.

Conventional bitumen is a viscoelastic material composed of asphaltene and maltene. It is prepared by air-blowing, but this approach makes the bitumen more brittle and susceptible to temperatures. To decrease the temperature susceptibility, synthetic polymers or additives are used to make polymer-modified bitumens. Polymer-modified bitumens have poor storage stability and phase separation and are costly. Chitosan has free amino and hydroxyl groups. Some studies showed that chitosan can be used as a bitumen emulsifier, increasing emulsion viscosity. This study describes the synthesis of O-carboxymethyl chitosan (OCMC) from chitosan, and the same was blended in base bitumen VG10 and VG30 to improve its constitutive properties. VG10 and VG30 grade bitumen were characterized for penetration, softening point, kinematic and absolute viscosity, and ductility. OCMC-modified bitumens were also characterized by their rheological and mechanical properties. OCMC was used in the concentration range of 0.5 to 4.5 wt%. The study revealed that using sulfur increases the ductility and penetration of modified bitumen with 1.5 wt% of OCMC and meets the specification of VG40-modified bitumen as per BIS specification IS:73:2013. The study showed that blending 1.5 wt% of OCMC in VG30 base bitumen enhances the complex modulus to 76,517Pa (at 42°C) with a minimum phase angle of 68.58° and meets the VG40 bitumen specification. Simultaneously, blending 1.5 wt% of OCMC in VG10 base bitumen enhances the complex modulus to 64,454Pa with a minimum phase angle of 77.39° (at 42°C) and meets the VG30 bitumen specification. Studies showed that using SBS in a small amount of 0.25 wt% along with modified chitosan improves the rutting resistance and shear modulus by more than 67°C at 1.1kPa.

DBFact applied to minimum variance performance assessment for nonminimum phase multivariate systems from closed‐loop data

AbstractThis paper introduces an approach for determining a minimum variance control (MVC) benchmark for nonminimum phase (NMP) multi‐input multi‐output (MIMO) systems using closed‐loop operational data. The MVC benchmark is derived from the MVC law of DBFact factorization introduced by Lima, Trierweiler, and Farenzena. Unlike other factorization methods, DBFact offers advantages such as non‐iterative computation and ensuring internal stability of the MVC law. This approach considers the inherent directionality of NMP MIMO systems, enhancing the reliability of the control performance index. However, the original method relies on prior knowledge of the process model. To overcome this limitation, this paper proposes a method for calculating the MVC benchmark when prior knowledge is absent. It introduces a MIMO system identification strategy employing minimally invasive signal tests. The methodology is evaluated across various control conditions using a quadruple‐tank plant with additional time delays. The study emphasizes the importance of directionality in assessing MIMO system performance, particularly in evaluating individual loop performances. Results demonstrate the identification procedure's effectiveness in accurately calculating the proposed MVC benchmark, even with a mere 1% increase in output variance considered.

Design of two-loop FOPID-FOPI controller for inverted cart-pendulum system

The inverted cart-pendulum system (ICPS) consists in having a pendulum mounted on a sliding cart, with the pivot point fixed. This real time experiment indeed looks like a rocket and its functionality is akin to a rocket. These are the launchers and the missile guidance and control as well as construction anti-seismic measures also. The control aim in these systems is to maintain the inverted pendulum vertically stable. The system is causal but unstable and, therefore, has no minimum phase. Therefore, the right half plane pole and zero are close to each other. Therefore, the stability of the system can be considered as problematic at some points. Unfortunately, linear time- invariant (LTI) classical controllers are incapable of offering suffient loop robustness for such systems. This paper aims to project a two-loop fractional order controller (2-LFOC) design to stabilize a higher-order nonlinear inverted cart-pendulum system (ICPS). The modeling, linearization, and control of ICPS are demonstrated in this work. The control target is adjusted so that the inverted pendulum stabilizes in its upright state when the cart reaches the required point. To fulfill the control objective, two-loop FOPID-FOPI controllers are proposed, and the Levenberg Marquardt algorithm (LMA) is utilized to tune the controllers. A novel nonlinear integral of time-associated absolute-error (ITAE) based fitness formula considering the settling time and rise time is used to fit the controller parameters for 2-LFOC. A performance comparison with the PID controller in terms of different time domain parameters such as rise_time (T R ), peak_time (T P ), settling_time (T S ), maximum overshoot (OS M ), maximum undershoot (US M ) and steady-state error (E SS ) are investigated. Stability analysis using Riemann surface observation of the system compensated with the proposed controller is presented in this work. The robust behavior of the two-loop FOPID-FOPI controller is verified by the application of disturbances in the system and the Reimann surface observation.

An Analog Predistorter for Doherty Power Amplifiers Based on Minimum Gain and Phase Deviation

An Analog Predistorter for Doherty Power Amplifiers Based on Minimum Gain and Phase Deviation

Influence of forging pretreatments on microstructure evolution and surface roughness of Al 6061 alloy

Achieving ultra-smooth surfaces is the goal of aluminum optical manufacturing. Under certain processing conditions, improving the microstructure of aluminum and understanding its relationship with surface roughness requires systematic study. The grain structure and various types of second-phase particles are of paramount importance. This study analyzed the microstructure of 6061 alloy after undergoing severe plastic deformation under various processing conditions followed by T6 homogenization heat treatment. Utilizing a white light interferometer, a comparative analysis of the surface roughness was conducted on specimens that underwent single-point diamond turning to achieve a mirror finish. The assessment of surface roughness on machined surfaces is solely based on white light interferometry. The analysis and discussion focus on the effects of phases (causing scratches and voids), the grains and grain boundaries. Experimental findings signify: the grain size, grain boundary and residual second phase can both influence the surface quality, the increase in deformation temperature and accumulated strain both facilitate the dissolution and fragmentation of the secondary phases. However, they also contribute to some extent to grain growth, resulting in a minimum secondary phase area fraction of 0.87% and grain sizes reaching 147.8 μm. Subsequent heat treatments, while effective in reducing the negative impact of the phases, reveal noticeable step-like structures affecting the quality of surface roughness, with the lowest obtained Ra value being 0.8 nm. A proposed pretreatment method in cleaner ingot processing with lower alloy element content addresses the trade-off between reducing phases and controlling grain growth, aiming to achieve improved surface roughness, promoting the application of polycrystalline aluminum alloys in the field of optics manufacturing.

Leveraging context-adjusted nighttime light data for socioeconomic explanations of global urban resilience

Urban resilience, crucial for achieving sustainable development goals, entails the adaptation and recovery of urban systems from external shocks, such as the recent global pandemic. To investigate the response of urban systems to COVID-19, this study employs context-adjusted nighttime light data to model global urban resilience by combining an evolving urban resilience metric (EURm) with the shape similarity of resilience curves. Random effect analysis and counterfactual explanations are then implemented to explore the socioeconomic impacts on urban resilience during the pandemic, providing strategic insights for improvement. Our results delineate five diverse urban resilience patterns, each characterized by distinct phases of downturn, minimum, and recovery, with examples from Malaysia, Japan, the United States, China, and South Sudan. We also find notable correlations between socioeconomic factors and urban resilience, highlighting that stringent measures may reduce resilience, whereas proactive health and containment strategies could bolster resilience. Meanwhile, economic stress reflected by inflation adversely affects resilience. Furthermore, we delve into strategic socioeconomic modifications to enhance urban resilience using counterfactual explanations, underlining the importance of customized interpretation for varying countries. Overall, this study advances our understanding of urban resilience during global crises, guiding context-specific resilience strategies in urban planning and policy-making.