Fundamental Control Research Articles

Research on the hydraulic parameters and leak rate of natural gas flow in natural gas pipelines based on the methods of characteristic line and successive approximation

Pressure and flow rate are the most important hydraulic parameters in natural gas pipeline flow, and leak rate is the most crucial parameter after a leak accident occurs. The study of these parameters is vital to the safey of natural gas pipelines and risk assessment after accidents. In this research, based on the conservation laws universally applicable to the motion of objects, we establish the fundamental control equation group for natural gas flow. Then, for both normal and leak conditions of pipelines, we use the characteristic line method to derive the corresponding difference equations for the fundamental control equations, thereby providing calculation methods for pressure and flow rate. Finally, we investigate the calculation method of natural gas pipeline leak rate under different leak aperture sizes, and validate the accuracy of this method through simulation examples.

The Zoonotic Aspect of Toxoplasma Gondii in Human and Animals: A Review

Toxoplasmosis is caused by the apicomplexan parasite Toxoplasma gondii, which may infect any nucleated cell in mammals. This parasite infects over two billion individuals worldwide, and while only a tiny fraction of infected persons may develop significant disease, the parasite's ubiquity makes it one of the most highly dangerous zoonotic infections in the world. This disease can cause serious encephalitis in immunocompromised persons, miscarriage or congenital malformations in the newborns if infected during pregnancy, and significant ocular illness even in immunocompetent people. The illness has a complicated aetiology, as it is caused by ingesting oocysts shed in the faeces of definitive feline hosts that pollute water. In this review we demonstrated the current insight into the zoonotic aspect of toxoplasmosis in humans, and animals providing a complete discussion of the environmental mechanisms via which T. gondii oocysts, and tissue cysts might infect animals and humans, such as contaminated foods, water, animals’ meat or soil. This review also included mode of transmission and preventative strategies outlining fundamental control measures for lowering the threat of oocyst direct contact, as well as chances for future collaboration and new studies possibilities targeting reducing oocysts load and tissue cyst-borne toxoplasmosis in people, farm and wild animals. Conclusively, the infection occurs in both humans and animals, causing abortion in women and serious economic losses in animals. Transmitted to humans horizontally by ingestion of food and water contaminated by oocysts, also meat of infected farm animals or vertically through the placenta. Cats get infected through ingestion of intermediate host-containing tissue cysts. Heating, salting, freezing and radiation are the main ways enforced to reduce tissue cyst burden in animal meat used for human consumption

Designing of a Reduced Switch MLI-Based Standalone Solar Inverter Suitable for Water Pump Application

Designing of a reduced switch multi-string cross-connected source type multilevel inverter (CCS-MLI)-based solar pump is introduced in this article. Integration of the Photovoltaic (PV) system with the inverter is achieved through a DC–DC converter equipped with maximum power point tracking (MPPT) to enhance overall reliability. The asymmetrically switched CCS-MLI utilizes only 8 switches to generate 13-level waveform and facilitates power control between battery-assisted PV panels and the single-phase Induction Motor (IM). Multicarrier Pulse Width Modulation (MCPWM) is employed for frequency and fundamental component control in the output voltage. Solar-powered drive systems face the challenge of maintaining intended motor operation amid varying power generation from the PV array. The addition of batteries through a bidirectional DC/DC converter, mitigates this issue by supporting the load during reduced power output from PV panels due to unpredictable solar irradiation levels. Besides ensuring power quality, the proposed control technique realizes constant (V/f) control enabling stable drive operation. The efficacy of the proposed scheme is tested in MATLAB SIMULINK platform with a solar battery combination, considering changing environmental conditions. Furthermore, a hardware prototype of the battery-assisted CCS-MLI-based solar inverter is implemented, and various results are rigorously tested and analyzed using an equivalent machine circuit.

Modeling and simulation of earth coverage of a low earth orbit (LEO) satellite

Efficient management of operations in near space, just beyond the Earth’s atmosphere, relies on the precise control of satellites positioned relatively close to our planet. Satellite systems, serving critical functions in telecommunications, observation, exploration, and more, have demonstrated their prowess as a transformative technology, consistently delivering high-precision data over numerous years. Among satellite systems, Low Earth Orbit (LEO) technology is gaining prominence due to its advantages, including lower power requirements for transmission, reduced propagation delays, and heightened coverage for polar regions. Achieving optimal efficiency from LEO satellites necessitates a thorough understanding of their fundamental orbital parameters and precise control over them. This study explores the orbital analysis and Earth coverage considerations of LEO satellites, scrutinizing orbital parameters in detail to compute coverage areas across various scenarios. Through this investigation, the potential benefits of data exchange with ground stations facilitated by LEO satellites are explored. In addition, the implications are discussed regarding the adjustment of data exchange topologies according to geographical locations and country borders.

Reviewing Control Paradigms and Emerging Trends of Grid-Forming Inverters—A Comparative Study

Grid-forming inverters (GFMs) have emerged as crucial components in modern power systems, facilitating the integration of renewable energy sources and enhancing grid stability. The significance of GFMs lies in their ability to autonomously establish grid voltage and frequency, enabling grids to form and improve system flexibility. Discussing control methods for grid-forming inverters is paramount due to their crucial role in shaping grid dynamics and ensuring reliable power delivery. This paper explores the fundamental and advanced control methods employed by GFMs, explaining their operational principles and performance characteristics. Basic control methods typically involve droop control, voltage and frequency regulation, and power-balancing techniques to maintain grid stability under varying operating conditions. Advanced control strategies encompass predictive control, model predictive control (MPC), and adaptive control, which influence advanced algorithms and real-time data for enhanced system responsiveness and efficiency. A detailed analysis and performance comparison of different control methods for GFM is presented, highlighting their strengths, limitations, and suitability for diverse grid environments. Through comprehensive studies, this research interprets the ability of various control strategies to mitigate grid disturbances, optimize power flow, and enhance overall system stability.

Coherent Microwave, Optical, and Mechanical Quantum Control of Spin Qubits in Diamond

AbstractDiamond has emerged as a highly promising platform for quantum network applications. Color centers in diamond fulfill the fundamental requirements for quantum nodes: they constitute optically accessible quantum systems with long‐lived spin qubits. Furthermore, they provide access to a quantum register of electronic and nuclear spin qubits and they mediate entanglement between spins and photons. All these operations require coherent control of the color center's spin state. This review provides a comprehensive overview of the state‐of‐the‐art, challenges, and prospects of such schemes, including high‐fidelity initialization, coherent manipulation, and readout of spin states. Established microwave and optical control techniques are reviewed, and moreover, emerging methods such as cavity‐mediated spin–photon interactions and mechanical control based on spin–phonon interactions are summarized. For different types of color centers, namely, nitrogen–vacancy and group‐IV color centers, distinct challenges persist that are subject of ongoing research. Beyond fundamental coherent spin qubit control techniques, advanced demonstrations in quantum network applications are outlined, for example, the integration of individual color centers for accessing (nuclear) multiqubit registers. Finally, the role of diamond spin qubits in the realization of future quantum information applications is described.

Transient acceleration waveform replication of electro-hydraulic systems using convex combined adaptive controller with input shaping technique

Electro-hydraulic systems are extensively utilized to generate desired acceleration waveforms to provide a vibration environment for testing the performance and reliability of objects in various industrial applications. However, as electro-hydraulic systems are often affected by some inevitable drawbacks resulted from hydraulic nonlinearities, unwanted dynamic variations and disturbances, the generated acceleration waveform is generally far behind the expectation. In this paper, a convex combined adaptive controller with input shaping technique is proposed for enhancing the transient acceleration waveform replication accuracy of electro-hydraulic systems. The proposed controller is comprised of a three variable controller at the bottom level, an input shaping technique controller at the middle level, and a convex combined adaptive controller at the upper level. The three variable controller is firstly utilized for the establishment of a fundamental closed-loop acceleration control system, and then the input shaping technique controller is constructed by introducing an offline designed inverse prefilter utilizing the multi-innovation recursive least squares algorithm and the zero magnitude error tracking algorithm. The convex combined adaptive controller at the upper level is comprised of two individual adaptive filters with high and low step sizes, which provides the merits of fast convergence rate and high tracking accuracy, and it is further exploited to address for system’s dynamic variations, model uncertainties and unexpected perturbations. Comparative experiments of the proposed controller with a manually generated random waveform and a recorded earthquake waveform as the testing inputs are conducted on a typical electro-hydraulic test bench, and the corresponding results demonstrate the feasibility and superiority of the proposed controller in improving the transient acceleration waveform replication performance of electro-hydraulic systems.

The study of iron- and copper-binding proteome of Fusarium oxysporum and its effector candidates.

Fusarium oxysporum f.sp. lycopersici is a phytopathogen which causes vascular wilt disease in tomato plants. The survival tactics of both pathogens and hosts depend on intricate interactions between host plants and pathogenic microbes. Iron-binding proteins (IBPs) and copper-binding proteins (CBPs) play a crucial role in these interactions by participating in enzyme reactions, virulence, metabolism, and transport processes. We employed high-throughput computational tools at the sequence and structural levels to investigate the IBPs and CBPs of F. oxysporum. A total of 124 IBPs and 37 CBPs were identified in the proteome of Fusarium. The ranking of amino acids based on their affinity for binding with iron is Glu > His> Asp > Asn > Cys, and for copper is His > Asp > Cys respectively. The functional annotation, determination of subcellular localization, and Gene Ontology analysis of these putative IBPs and CBPs have unveiled their potential involvement in a diverse array of cellular and biological processes. Three iron-binding glycosyl hydrolase family proteins, along with four CBPs with carbohydrate-binding domains, have been identified as potential effector candidates. These proteins are distinct from the host Solanum lycopersicum proteome. Moreover, they are known to be located extracellularly and function as enzymes that degrade the host cell wall during pathogen-host interactions. The insights gained from this report on the role of metal ions in plant-pathogen interactions can help develop a better understanding of their fundamental biology and control vascular wilt disease in tomato plants.

High-Efficient Direct Power Control Scheme Using Predictive Virtual Flux for Three-Phase Active Rectifiers

In recent years, the pulse-width-modulation (PWM) converter has been found to have extensive applications in renewable energy, industrial fields, and others. The high efficiency requirement is crucial to operating a PWM rectifier in various applications, in addition to the fundamental control objectives of sinusoidal grid currents and the correct DC bus voltage. Additionally, in practical application, another issue arises when the grid voltage frequently experiences distortion, leading to a distorted grid current and a significant rise in total harmonic distortion (THD). To resolve these problems, a model predictive virtual flux-based direct power control (MPVFDPC) with improved power loss performance is proposed based on an integrated switching state predetermination strategy. The proposed MPVFDPC for PWM rectifier inherits the merits of both virtual flux control and direct power control, which have fast dynamic performance and the grid current THD is considerably decreased under distorted grid voltage states. The proposed technique aims to minimize switching loss under ideal and distorted grid voltage states by exploiting the discontinuous modulation concept by using a switching state predetermination strategy. The MPVFDPC with switching state predetermination strategy is proven by employing it in experiments as well as simulations in comparison with previous models: predictive direct power control (Conv. MPDPC) and conventional MPVFDPC (Conv. MPVFDPC). The acquired waveforms and quantitative data are employed to prove the effectiveness of the developed algorithm.

Embedded Physical Intelligence in Liquid Crystalline Polymer Actuators and Robots.

Responsive materials possess the inherent capacity to autonomously sense and respond to various external stimuli, demonstrating physical intelligence. Among the diverse array of responsive materials, liquid crystalline polymers (LCPs) stand out for their remarkable reversible stimuli-responsive shape-morphing properties and their potential for creating soft robots. While numerous reviews have extensively detailed the progress in developing LCP-based actuators and robots, there exists a need for comprehensive summaries that elucidate the underlying principles governing actuation and how physical intelligence is embedded within these systems. This review provides a comprehensive overview of recent advancements in developing actuators and robots endowed with physical intelligence using LCPs. This review is structured around the stimulus conditions and categorizes the studies involving responsive LCPs based on the fundamental control and stimulation logic and approach. Specifically, three main categories are examined: systems that respond to changing stimuli, those operating under constant stimuli, and those equip with learning and logic control capabilities. Furthermore, the persisting challenges that need to be addressed are outlined and discuss the future avenues of research in this dynamic field.

Effectiveness of vaccination, travel load, and facemask use control strategies for controlling COVID Delta variant: the case of Sydney Metropolitan Area

AbstractThe Delta variant of SARS-CoV-2, specifically identified as B.1.617.2, is responsible for the severe outbreaks witnessed globally, including in various countries and cities, with Sydney Greater Metropolitan Area (Sydney GMA) being no exception. According to scientific studies, the Delta strain exhibits increased contagion and leads to a higher incidence of vaccine breakthrough cases, posing significant challenges to pandemic control efforts. In this study, we explore the efficacy of three fundamental control strategies—namely, vaccination rates, adherence to facemask usage, and the management of travel loads—in mitigating the spread of the disease and, consequently, eliminating the Delta variant pandemic in Sydney GMA. We employ an agent-based disease spread model to thoroughly investigate these strategies. Moreover, factorial MANOVA is utilised to assess the significance of variations in the impact of diverse compliance levels with the aforementioned control strategies on various attributes of the pandemic. As complete lockdowns and stringent travel regulations have the potential to induce physical and mental distress in individuals and economic crises for countries, our study examines the interactive effects of implementing control strategies to mitigate the necessity for a full lockdown. The simulation results suggest that suppressing a pandemic with similar characteristics to Delta variant of COVID is feasible with a vaccination rate of 80% or higher, as long as travel load and activity participation are maintained at pre-COVID levels. Alternatively, a more realistic and attainable combination of control measures—a vaccination rate of 60%, a facemask usage level of 60%, and a 50% compliance level for social distancing—demonstrates comparable efficacy, leading to effective pandemic control. Notably, the vaccination rate emerges as a more potent control strategy compared to others in the elimination of the disease within society.

Magnetics only real-time equilibrium reconstruction on ASDEX Upgrade

Real-time reconstruction of the magnetic equilibrium provides fundamental control of plasma shape and position in a tokamak. Details of the implementation of the equilibrium reconstruction code developed for the ASDEX Upgrade tokamak (JANET++) are summarized. Cubic Hermite splines are introduced as current density basis functions for solving the Grad–Shafranov equation. The choice of the optimal Tikhonov regularization parameter is discussed. The code is validated by comparing the results of the equilibrium reconstruction with those of further equilibrium reconstructions available on ASDEX Upgrade (CLISTE and IDE). In a high time resolution study of a discharge with edge localized modes (ELM), the poloidal asymmetry of the fits and magnetic probe measurements suggest that the real-time equilibrium reconstruction captures the essential features of the current density redistribution in an ELMing edge plasma. An efficient algorithm to locate multiple X-points and identify the active one in advanced X-divertor and snowflake divertor configurations is presented.

Stochastic in Space and Time: 2. Effects of Simulating Orographic Gradients in Daily Runoff Variability on Bedrock River Incision

AbstractThe extent to which climate and tectonics can be coupled rests on the degree to which topography and erosion rates scales linearly. The stream power incision model (SPIM) is commonly used to interpret such relationships, but is limited in probing mechanisms. A promising modification to stream power models are stochastic‐threshold incision models (STIM) which incorporate both variability in discharge and a threshold to erosion. In this family of models, the form of the topography erosion rate relationship is largely controlled by runoff variability. Applications of STIM typically assume temporally variable, but spatially uniform and synchronous runoff generating events, an assumption that is likely broken in regions with complicated orography. To address this limitation, we develop a new 1D STIM model, which we refer to as spatial‐STIM. This modified version of STIM allows for stochasticity in both time and space and is driven by empirical relationships between topography and runoff statistics. Coupling between mean runoff and runoff variability via topography in spatial‐STIM generates highly nonlinear relationships between steady‐state topography and erosion rates. We find that whether the daily statistics of runoff are spatially linked or unlinked, which sets whether there is spatial synchronicity in the recurrence interval of runoff generating events, is a fundamental control on landscape evolution. Many empirical topography—erosion rate data sets are based on data that span across the endmember scenarios of linked versus unlinked behavior. It is thus questionable whether singular SPIM relationships fit to those data can be meaningfully related to their associated hydroclimatic conditions.

The rheological response of magma to nanolitisation

Viscosity exerts a fundamental control on magmatic kinetics and dynamics, controlling magma ascent, eruptive style, and the emplacement of lava. Nanolites – crystals smaller than a micron – are thought to affect magma viscosity, but the underlying mechanisms for this remain unclear. Here, we use a cylinder compression creep technique to measure the viscosity of supercooled silicate liquids with different amounts of iron (0–20 wt% FeOtot) as a function of temperature, applied shear stress, and time. Sample viscosity was independent on the applied shear stresses, and as expected, melt viscosity decreases as temperature is increased, but only until a critical temperature where a time-dependent increase in viscosity occurs for samples contaning 6.0 wt% FeOtot or more. The magnitude of this increase is controlled by the melt iron content. At constant temperature, these changes are substantial and can reach up to three orders of magnitude for the sample with the most iron. Using transmission electron microscopy, X-ray diffraction, and viscosity modelling, we conclude that this viscosity increase is caused by the formation of nanolites. By using scaling approaches to test suspension effects with and without crystal aggregation, we conclude that the nanolites have only a minimal direct physical effect on the observed viscosity change. Rather, our models show that it is the chemical shift in the groundmass silicate melt composition associated with non-stoichiometric crystallisation that dominates the observed viscosity increase. These findings suggest that iron-rich silicates may encounter chemical viscosity jumps once certain elements are removed from the melt phase to form nanolites. Our work demonstrates an underlying mechanism for the role played by nanolites in viscosity changes of magmas.

Aliasing Suppression Method for a Three-Phase Grid-Connected Photovoltaic Inverter Based on Multi-Sampling and Mean Filtering

In order to reduce the sampling delay and improve bandwidth, sability margin, and the robustness of the active damping in LCL-filtered grid-connected inverters, real-time sampling provides a convenient method. However, aliasing is easily introduced in the control loop because of high-frequency switching harmonics, resulting in a rise in low-order harmonics. To address the challenge of aliasing under real-time sampling, a new method based on multisampling and mean filtering is proposed by combining the proposed harmonic detection and control methods in this paper. This method works by sampling and controlling the fundamental current and selective subharmonic currents separately. The fundamental current control loop without any additional filters maintains real-time sampling, while multisampling and mean filters are applied to the harmonic current control loop. The proposed control method can not only improve the dynamic response performance and control stability of the system but also effectively suppress the selective low-order current harmonics and the aliasing of sampling. Finally, the correctness of the proposed sampling scheme and control strategy is verified by the simulation based on R2018b, MathWorks, Natick, MA, USA and an experimental prototype of a three-phase grid-connected photovoltaic inverter rated at 230 V/50 Hz/40 kW.

Potential of Milk-Derived Extracellular Vesicles as Carriers for Oral Delivery of Active Phytoconstituents.

Extracellular vesicles (EVs) play a crucial role in intercellular communication and have the potential to serve as in vivo carriers for delivering active molecules. The biocompatibility advantages of EVs over artificial nanocarriers create new frontiers for delivering modern active molecules. Milk is a favorable source of EVs because of its high bioavailability, low immunogenicity, and commercial producibility. In this review, we analyzed the advantages of milk-derived EVs in the oral delivery of active molecules, discussed their research progress in delivering active phytoconstituents, and summarized the necessary technologies and critical unit operations required for the development of an oral delivery system based on EVs. The review aims to provide innovative ideas and fundamental quality control guidelines for developing the next-generation oral drug delivery system based on milk-derived EVs.

A review of continuum robot

This paper comprehensively reviews continuum robots and their application in medical domains. Unlike traditional rigid robots, continuum robots possess continuous, flexible structures that enhance dexterity and adaptability. Their compliant nature allows safer human-robot collaboration, while their deformability permits navigation through confined spaces and conformance to anatomy. These advantages make continuum robots promising for medical applications like minimally invasive surgery. The paper discusses continuum robots' fundamental principles, including kinematics, dynamics, mechanical design, modelling, and control strategies. It highlights the unique benefits of continuum robots compared to rigid counterparts, especially for medical use. Challenges such as design optimization, accurate control and modelling, sensing, miniaturization, and technology integration are also addressed. Enhancing manipulation capabilities, developing miniaturized continuum robots, achieving autonomous operation, integrating imaging modalities, and validating safety and efficacy through clinical trials are suggested for future work. This review offers valuable insights into continuum robotics technology and its immense potential to transform medical interventions through precise, minimally invasive procedures.

Effect of boron concentration on local structure and spontaneous polarization in AlBN thin films

The discovery of ferroelectricity in polar wurtzite-based ternary materials, such as Al1−xBxN, has attracted attention due to their compatibility with complementary metal–oxide–semiconductor processes and potential use in integrated non-volatile memory devices. However, the origin of ferroelectricity and the fundamental control of the polarization switching in these materials are still under intensive investigation but appear to be related to local disorder induced from the alloying. In this work, we report the effect of boron alloying on the local structure of Al1−xBxN films deposited by magnetron sputtering. Our results reveal a diminished crystalline order as a function of boron concentration, accompanied by a reduction in the spontaneous polarization. The film disorder is primarily associated with the dissimilar bond lengths between Al–N and B–N and the formation of threading dislocations induced by B incorporation in the structure.

Sizing and Control of the Electric Power Take Off for a Buoy Type Point Absorber Wave Energy Converter

This paper presents the study of power extraction and control of the electric power take off of a buoy type point absorber wave energy converter in heave. Two fundamental linear control strategies (the passive loading and optimum control) have been studied and their impacts on the sizing of generator were investigated. For the designed incident wave, a gearbox is needed to reach the rated speed of the generator. The generator is connected to the grid through a back-to-back converter which controls the electrical torque. Vector control technique is implemented to control the electric torque of the generator, by setting the direct axis current to zero. The results show that the current needed to control the electrical torque is too high for optimum control strategy. A method has been presented to reduce the power ratio significantly, but also with a decrease in average extracted power.

Artificial intelligence based supply chain management strategy during COVID-19 situation

ABSTRACT The COVID-19 pandemic has brought about unprecedented challenges, such as constantly changing consumer demands and disruptions in the supply chain. This study aims to reduce the cost of inventory units in the COVID-19 scenario by using a mathematical model to develop fundamental inventory control formulations. However, conventional analytical methods often struggle to identify and analyse the complex patterns and rapidly shifting trends that characterise COVID-19. To address this issue, this study employs ANN techniques to determine the total variable cost of essential items in the COVID-19 scenario, using current demand, discount rate, and advanced payments as input variables. The study creates an optimal ANN model for real-life situations by combining different solvers and activation functions. Among the various combinations, the study observes that the combination of the relu activation function and lbfgs solvers offers the lowest RMSE value of 0.03382 and the highest R2 value of 0.9858 for the optimum total variable cost. The study affirms that ANN techniques excel in analyzing the EPQ model during COVID-19 by managing complexity, adapting to changes, and assessing diverse data. This real-time analysis aids supply chains, ensuring timely key item availability in high-demand or disruptive scenarios.