Conventional Control Research Articles

CRISPR-Cas9 and Cas12a target site richness reflects genomic diversity in natural populations of Anopheles gambiae and Aedes aegypti mosquitoes

Due to limitations in conventional disease vector control strategies including the rise of insecticide resistance in natural populations of mosquitoes, genetic control strategies using CRISPR gene drive systems have been under serious consideration. The identification of CRISPR target sites in mosquito populations is a key aspect for developing efficient genetic vector control strategies. While genome-wide Cas9 target sites have been explored in mosquitoes, a precise evaluation of target sites focused on coding sequence (CDS) is lacking. Additionally, target site polymorphisms have not been characterized for other nucleases such as Cas12a, which require a different DNA recognition site (PAM) and would expand the accessibility of mosquito genomes for genetic engineering. We undertook a comprehensive analysis of potential target sites for both Cas9 and Cas12a nucleases within the genomes of natural populations of Anopheles gambiae and Aedes aegypti from multiple continents. We demonstrate that using two nucleases increases the number of targets per gene. Also, we identified differences in nucleotide diversity between North American and African Aedes populations, impacting the abundance of good target sites with a minimal degree of polymorphisms that can affect the binding of gRNA. Lastly, we screened for gRNAs targeting sex-determination genes that could be widely applicable for developing field genetic control strategies. Overall, this work highlights the utility of employing both Cas9 and Cas12a nucleases and underscores the importance of designing universal genetic strategies adaptable to diverse mosquito populations.

Sensorless control method of induction motors with new feedback gain matrix and speed adaptive law for low speed range

Abstract The conventional adaptive full-order observer-based speed sensorless control method for induction motor is prone to instability at low-speed region as improper feedback gain matrix and imprecise speed adaptive law are often used. To address these problems, a new feedback gain matrix design approach as well as a new speed adaptive law design technique are proposed in this paper. Firstly, considering that the d-axis current estimation error in the traditional feedback gain matrix design method has a great influence on the stability of the speed estimation algorithm, especially at low speeds, a new feedback gain matrix design method is proposed to minimize the d-axis current estimation error. Secondly, a new speed adaptive law design technique is studied based on the conventional method, which only requires the d-axis and q-axis current estimation error with a weight coefficient to be designed, simplifying the conventional speed adaptive law. Thirdly, the transfer function from the speed observation error to the proposed adaptive error is analyzed by Routh stability criterion theory, and the weight coefficient suitable for full range stable operation is determined by MATLAB software. Fourthly, the stability of the proposed method in this paper is analyzed using the poles distribution maps. Finally, the proposed method is experimentally verified based on a 2.2 kW induction motor experimental platform. The experimental results show that the proposed method can make the induction motor operate steadily at low-speed and zero-speed region with rated load. In addition, the proposed method has better anti-disturbance performance than the existing method.

Evasive invasives? Implications of neophobia for feral cat (Felis catus) control

AbstractNeophobia is an ecologically relevant personality trait that manifests as aversion to new or unfamiliar stimuli. Fear and subsequent avoidance of novel stimuli represents a challenge for pest management programs, as control tools that induce a neophobic response will reduce their effectiveness. Additionally, neophobia can be a plastic trait induced by exposure to high‐risk environments, and so can be exacerbated by repeated harassment, which often occurs in pest management programs that are conducted at high intensity. We investigated the propensity of feral cats (Felis catus) to exhibit neophobic behavior towards a novel control device. We also tested whether neophobia was altered by capture and radio‐collaring or changed over time. We found that there is significant potential for initial avoidance of control devices by some feral cats, and that capture and handling significantly increased the likelihood of avoidance. Neophobia generally declined over time suggesting that long‐term deployment may reduce the impact of neophobia. Avoidance of novel control tools could severely limit their effectiveness, especially if deployed to remove the last remaining cats from confined areas. Remaining cats may have avoided repeated attempts at conventional control techniques and so may be more neophobic. In such circumstances, control tool deployments should be lengthened considerably, to take advantage of waning neophobia over time, and, concealed effectively to hide them from neophobic cats. The increased neophobia recorded in cats that were handled and radio‐collared for monitoring suggests that results from experiments that test new control devices may not be indicative of the behavior of naïve cats. Changes to methodology such as minimizing capture and handling may be required to reduce neophobia and provide valid research results when testing novel control tools.

Energy Transition and Resilient Control for Enhancing Power Availability in Microgrids Based on North African Countries: A Review

The ambition of making North Africa a hub for renewable energies and green hydrogen has prompted local governments and the private sector to work together towards boosting the growth of locally available, sustainable energy resources. Numerous climate and energy challenges can be addressed by microgrid technologies, which enable cost-effective incorporation of renewable energy resources and energy storage systems through smart management and control infrastructures. This paper discusses the ongoing energy transition in the countries of North Africa, highlighting the potential for renewable energy sources as well as regional obstacles and challenges. Additionally, it explores how robust and stable controls and advanced management strategies can improve microgrids’ performances. Special attention is given to assessing the advantages and disadvantages of conventional and advanced controllers, with an emphasis on resilience needed within the harsh North African environment.

Enhanced voltage source converter control strategy for improved grid resilience: A 2DOF-PI approach

This paper presents a control strategy for voltage source converters connected to weak grids. The proposed approach is based on slight modifications to the conventional vector current control strategy, including the use of two degrees of freedom proportional-integral controllers, with reference weighting factors, in the inner current loop and a proportional controller in the outer loop, resulting in the introduction of only three additional parameters. The paper analyses the effect of these additional design parameters on the robustness improvement and studies the limitations of the proposal, providing design steps to achieve given performance prescriptions such as speed response, noise amplification, delays and phase-locked loop bandwidth, and the ability to face weak grids. Simulations are conducted to evaluate the effectiveness of the proposed approach, which demonstrates that it is possible to achieve a more robust behaviour compared with the conventional vector current control strategy when facing weak grids.

Advancement Challenges in UAV Swarm Formation Control: A Comprehensive Review

This paper provides an in-depth analysis of the current research landscape in the field of UAV (Unmanned Aerial Vehicle) swarm formation control. This review examines both conventional control methods, including leader–follower, virtual structure, behavior-based, consensus-based, and artificial potential field, and advanced AI-based (Artificial Intelligence) methods, such as artificial neural networks and deep reinforcement learning. It highlights the distinct advantages and limitations of each approach, showcasing how conventional methods offer reliability and simplicity, while AI-based strategies provide adaptability and sophisticated optimization capabilities. This review underscores the critical need for innovative solutions and interdisciplinary approaches combining conventional and AI methods to overcome existing challenges and fully exploit the potential of UAV swarms in various applications.

Strong angular and spectral narrowing of electroluminescence in an integrated Tamm-plasmon-driven halide perovskite LED

Next-generation light-emitting applications such as displays and optical communications require judicious control over emitted light, including intensity and angular dispersion. To date, this remains a challenge as conventional methods require cumbersome optics. Here, we report highly directional and enhanced electroluminescence from a solution-processed quasi-2-dimensional halide perovskite light-emitting diode by building a device architecture to exploit hybrid plasmonic-photonic Tamm plasmon modes. By exploiting the processing and bandgap tunability of the halide perovskite device layers, we construct the device stack to optimise both optical and charge-injection properties, leading to narrow forward electroluminescence with an angular full-width half-maximum of 36.6° compared with the conventional isotropic control device of 143.9°, and narrow electroluminescence spectral full-width half-maximum of 12.1 nm. The device design is versatile and tunable to work with emission lines covering the visible spectrum with desired directionality, thus providing a promising route to modular, inexpensive, and directional operating light-emitting devices.

Strong angular and spectral narrowing of electroluminescence in an integrated Tamm-plasmon-driven halide perovskite LED

Next-generation light-emitting applications such as displays and optical communications require judicious control over emitted light, including intensity and angular dispersion. To date, this remains a challenge as conventional methods require cumbersome optics. Here, we report highly directional and enhanced electroluminescence from a solution-processed quasi-2-dimensional halide perovskite light-emitting diode by building a device architecture to exploit hybrid plasmonic-photonic Tamm plasmon modes. By exploiting the processing and bandgap tunability of the halide perovskite device layers, we construct the device stack to optimise both optical and charge-injection properties, leading to narrow forward electroluminescence with an angular full-width half-maximum of 36.6° compared with the conventional isotropic control device of 143.9°, and narrow electroluminescence spectral full-width half-maximum of 12.1 nm. The device design is versatile and tunable to work with emission lines covering the visible spectrum with desired directionality, thus providing a promising route to modular, inexpensive, and directional operating light-emitting devices.

Augmented Two-Stage Hierarchical Controller for Distributed Power Generation System Powered by Renewable Energy: Development and Performance Analysis

The sustainable development of an area is highly reliant on a reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller’s performance is evaluated in a MATLAB environment, and simulation results show the proposed scheme’s superiority under different operating conditions. The frequency is stable at 50 Hz after a 50 KW load is added.

A hierarchical framework for minimising emissions in hybrid gas-renewable energy systems under forecast uncertainty

Developing and deploying renewables in existing energy systems are pivotal in Europe’s transition to net-zero emissions. In this transition, gas turbines (GTs) will be central for balancing purposes. However, a significant hurdle in minimising emissions of GTs operating in combination with intermittent renewables arises from the reliance on unreliable meteorological forecasts. Here, we propose a hierarchical framework for decoupling this operational problem into a balancing and emissions minimisation problem. Balancing is ensured with a high-level stochastic balancing filter (SBF) based on data-driven stochastic grey-box models for the uncertain intermittent renewable. The filter utilises probabilistic forecasting and less conservative chance constraints to compute safe bounds, within which a proposed low-level economic predictive controller further minimises emissions of the GTs during operations. As GTs exhibit semi-continuous operating regions, complementarity constraints are utilised to fully exploit each GT’s allowed operational range. The proposed method is validated in simulation for a gas-balanced hybrid renewable system with batteries, three GTs with varying capacities, and a wind farm. Using real historical operational wind data, our simulation shows that the proposed framework balances the energy demand and minimises emissions with up to 4.35% compared with other conventional control strategies in simulation by minimising the GT emissions directly with complementarity constraints in the low-level controller and indirectly with less conservative chance constraints in the high-level filter. The simulations show that the computational cost of the proposed framework is well within requirements for real-time applications. Thus, the proposed operational framework enables increased renewable share in hybrid energy systems with GTs and renewable energy and subsequently contributes to de-carbonising these types of isolated or grid-connected systems onshore and offshore.

A smooth method for primary frequency of wind turbine based on variable power point tracking and energy storage cooperative control

AbstractThe conventional deloading control has certain problems, such as low power generation efficiency and a small speed adjustment range. To improve the system's frequency quality and enhance the power grid's stability, this study comprehensively considers the effect of random source‐load power fluctuations on the system frequency. Moreover, this study proposes a smooth primary frequency control strategy for wind turbine based on the coordinated control of the variable power point tracking and supercapacitor energy storage. The impact of wind power fluctuations on the system frequency at different timescales for wind turbine is studied based on the historical data of wind power fluctuations in a strong wind meteorological cycle of a wind farm. The method determines the capacity of the energy storage device required for frequency smoothing at the optimal timescale. In combination with the required capacity of the wind turbine to participate in the system's primary frequency regulation, the supercapacitor energy storage device is optimally configured, and a set of supercapacitor energy storage device with the lowest cost under the highest charging/discharging efficiency is designed. Simulation and experimental results show that the primary frequency adjustment capability of the control strategy proposed in this study is significantly improved compared with the conventional primary frequency modulation control.

A smooth method for primary frequency of wind turbine based on variable power point tracking and energy storage cooperative control

AbstractThe conventional deloading control has certain problems, such as low power generation efficiency and a small speed adjustment range. To improve the system's frequency quality and enhance the power grid's stability, this study comprehensively considers the effect of random source‐load power fluctuations on the system frequency. Moreover, this study proposes a smooth primary frequency control strategy for wind turbine based on the coordinated control of the variable power point tracking and supercapacitor energy storage. The impact of wind power fluctuations on the system frequency at different timescales for wind turbine is studied based on the historical data of wind power fluctuations in a strong wind meteorological cycle of a wind farm. The method determines the capacity of the energy storage device required for frequency smoothing at the optimal timescale. In combination with the required capacity of the wind turbine to participate in the system's primary frequency regulation, the supercapacitor energy storage device is optimally configured, and a set of supercapacitor energy storage device with the lowest cost under the highest charging/discharging efficiency is designed. Simulation and experimental results show that the primary frequency adjustment capability of the control strategy proposed in this study is significantly improved compared with the conventional primary frequency modulation control.

A Mathematical Framework for Simultaneous Voltage and Frequency Regulation in Distributed Generator (DG) Grid-Interfaced Systems

Recent advancements in distributed generation (DG) systems interfaced with microgrids necessitate robust regulatory mechanisms to manage inherent power fluctuations, particularly from renewable sources like photovoltaics. These fluctuations can significantly impact the stability and efficiency of microgrids. This paper introduces a novel mathematical framework for simultaneous voltage and frequency regulation, aimed at addressing power quality and stability challenges in DG-grid interfaced systems. Utilizing a combination of algebraic topology and dynamical systems theory, we develop a model that incorporates an adaptive virtual frequency-impedance control loop. This mathematical approach allows for the analytical examination of the stability properties of the system and the design of control strategies that guarantee optimal operational thresholds. We extend the conventional droop control mechanisms with a rigorously defined Simultaneous Voltage and Frequency Correction Scheme (SVFCS), providing a theoretical underpinning that supports experimental observations. The efficacy of the proposed model is validated through numerical simulations that demonstrate adherence to the IEEE 519 standard, ensuring reduced harmonic distortion and enhanced system reliability. Our results highlight the potential for these mathematical methods to provide foundational insights into the control and optimization of microgrid operations.

A Mathematical Framework for Simultaneous Voltage and Frequency Regulation in Distributed Generator (DG) Grid-Interfaced Systems

Recent advancements in distributed generation (DG) systems interfaced with microgrids necessitate robust regulatory mechanisms to manage inherent power fluctuations, particularly from renewable sources like photovoltaics. These fluctuations can significantly impact the stability and efficiency of microgrids. This paper introduces a novel mathematical framework for simultaneous voltage and frequency regulation, aimed at addressing power quality and stability challenges in DG-grid interfaced systems. Utilizing a combination of algebraic topology and dynamical systems theory, we develop a model that incorporates an adaptive virtual frequency-impedance control loop. This mathematical approach allows for the analytical examination of the stability properties of the system and the design of control strategies that guarantee optimal operational thresholds. We extend the conventional droop control mechanisms with a rigorously defined Simultaneous Voltage and Frequency Correction Scheme (SVFCS), providing a theoretical underpinning that supports experimental observations. The efficacy of the proposed model is validated through numerical simulations that demonstrate adherence to the IEEE 519 standard, ensuring reduced harmonic distortion and enhanced system reliability. Our results highlight the potential for these mathematical methods to provide foundational insights into the control and optimization of microgrid operations.

Heterogeneous Integration of Acoustic Microextraction with an Optoelectronic Sensor on Glass for Nucleic Acid Testing.

Lab-on-a-chip systems (LOCs), characterized by their high sensitivity, low sample consumption, and portability, have significantly advanced the field of on-site testing. Despite the evolution of integrated LOCs from qualitative to quantitative analyses, on-chip full integration of sample preparation, purification, and multiplexed detection remains a challenge. Here, we propose a strategy for the heterogeneous integration of a set of complementary metal oxide semiconductor-compatible devices including acoustic resonator, thin-film resistors, and temperature/photosensors as a new type of LOC for nucleic acid testing (NAT). Programmed acoustic streaming-based particles and fluid manipulations largely simplify the nucleic acid extraction process including cell lysis, nucleic acid capture, and elution. The design of the acoustic microextraction module and extraction process was thoroughly studied. Benefitted by the microelectromechanical system approach, the conventional mechanical actions and complex flow control are avoided, which enables a compact hand-held NAT instrument without complicated peripherals. Validation experiments conducted on plasma-harboring mutations in the epidermal growth factor receptor (EGFR) gene confirmed the robustness of the system, achieving an impressive nucleic acid (NA) extraction efficiency of approximately 90% within 5 min and a limit of detection of the target NA in the plasma of 1 copy/μL.

From Teleportation to Climbing: A Review of Locomotion Techniques in the Most Used Commercial Virtual Reality Applications

Exploration of virtual reality locomotion has a rich history, including in the creation of taxonomies categorising individual techniques. However, most existing research collects data from academic sources only, with both historic industry practitioner exploration and a state-of-the-art understanding of locomotion in commercial applications comparatively underexplored. This systematic software-level review of the complete locomotion options in 330 of the most used virtual reality applications released between 2016 and 2023 on the Steam, Meta, Oculus, Viveport, and SideQuest platforms highlights the trends and gaps that exist between industry and academic exploration. Results suggest a decline in the usage of teleportation, with the prevalence of titles containing at least one teleportation technique decreasing from 48% of those released in 2016 to 18% in 2023. Arm-tracked grabbing locomotion techniques such as climbing meanwhile are being increasingly adopted by practitioners, from almost unused in 3% of applications released in 2016 to over 30% in each year between 2020 and 2023. Additionally, although the tracking capabilities afforded by consumer-level head-mounted display hardware has resulted in a high exploration of room-scale tracking, the large academic focus on walking-based locomotion appears to not be shared by practitioners, where room-scale tracking instead is most often paired with conventional controller joystick sliding locomotion. Finally, temporal analysis results showing the growing number of locomotion techniques offered in an average application signifies the need for further accessibility-related locomotion research, particularly in areas beyond visual sickness mitigation. Our findings highlight the continuing evolution of locomotion in commercial virtual reality applications, with industry practitioner locomotion technique adoption rates displaying the divergent interests between industry and academia, in turn adding rigour to future locomotion selections across both domains.

From Teleportation to Climbing: A Review of Locomotion Techniques in the Most Used Commercial Virtual Reality Applications

Exploration of virtual reality locomotion has a rich history, including in the creation of taxonomies categorising individual techniques. However, most existing research collects data from academic sources only, with both historic industry practitioner exploration and a state-of-the-art understanding of locomotion in commercial applications comparatively underexplored. This systematic software-level review of the complete locomotion options in 330 of the most used virtual reality applications released between 2016 and 2023 on the Steam, Meta, Oculus, Viveport, and SideQuest platforms highlights the trends and gaps that exist between industry and academic exploration. Results suggest a decline in the usage of teleportation, with the prevalence of titles containing at least one teleportation technique decreasing from 48% of those released in 2016 to 18% in 2023. Arm-tracked grabbing locomotion techniques such as climbing meanwhile are being increasingly adopted by practitioners, from almost unused in 3% of applications released in 2016 to over 30% in each year between 2020 and 2023. Additionally, although the tracking capabilities afforded by consumer-level head-mounted display hardware has resulted in a high exploration of room-scale tracking, the large academic focus on walking-based locomotion appears to not be shared by practitioners, where room-scale tracking instead is most often paired with conventional controller joystick sliding locomotion. Finally, temporal analysis results showing the growing number of locomotion techniques offered in an average application signifies the need for further accessibility-related locomotion research, particularly in areas beyond visual sickness mitigation. Our findings highlight the continuing evolution of locomotion in commercial virtual reality applications, with industry practitioner locomotion technique adoption rates displaying the divergent interests between industry and academia, in turn adding rigour to future locomotion selections across both domains.

Information control model of distributed energy resources

Currently, there is a constant growth of distributed energy resources, it became necessary to integrate them into the power grid. However, the integration process must consider not only the control parameters of the distributed energy resource but also the parallel operation of several such resources, the parameters of the power system as a whole. At the highest level of control, it is also necessary to consider the economic indicators formed by the energy market. Special devices – controlled inverters – can be effectively used for integration. The most difficult task is choosing a control system for controlled inverters. There are many different control systems such as Proportional-Integral, Deadbeat controllers, etc. The purpose of this paper is to build an information model for controlling distributed power resources. The current control method was used to control active and reactive power. The advantage of current control is resistance to variations in the parameters of the inverter and the external grid, excellent dynamic performance, and higher control accuracy. The proposed approach for building an automatic control system using the Internal model control strategy and taking into account restrictions on the control variable. The advantages of a system with an Internal model control controller compared to a conventional Proportional-Integral controller are the use of a powerful control method based on the object model, the ability to influence the roughness of the system with a separate setting parameter, increased speed with almost complete absence of over-regulation, simplified setup procedure. Such a system is proposed for use in facilities with strict requirements to minimize over-regulation and the speed of working out disturbances and tasks. The PSCAD software app was used to model the work results.

Information control model of distributed energy resources

Currently, there is a constant growth of distributed energy resources, it became necessary to integrate them into the power grid. However, the integration process must consider not only the control parameters of the distributed energy resource but also the parallel operation of several such resources, the parameters of the power system as a whole. At the highest level of control, it is also necessary to consider the economic indicators formed by the energy market. Special devices – controlled inverters – can be effectively used for integration. The most difficult task is choosing a control system for controlled inverters. There are many different control systems such as Proportional-Integral, Deadbeat controllers, etc. The purpose of this paper is to build an information model for controlling distributed power resources. The current control method was used to control active and reactive power. The advantage of current control is resistance to variations in the parameters of the inverter and the external grid, excellent dynamic performance, and higher control accuracy. The proposed approach for building an automatic control system using the Internal model control strategy and taking into account restrictions on the control variable. The advantages of a system with an Internal model control controller compared to a conventional Proportional-Integral controller are the use of a powerful control method based on the object model, the ability to influence the roughness of the system with a separate setting parameter, increased speed with almost complete absence of over-regulation, simplified setup procedure. Such a system is proposed for use in facilities with strict requirements to minimize over-regulation and the speed of working out disturbances and tasks. The PSCAD software app was used to model the work results.

Study on methane degradation by microbial agents based on chelating wetting agent carriers

Due to the low permeability characteristics of the deep gas-containing coal seam, the conventional prevention and control measures that cannot solve the problems of gas outbursts are unsatisfactory for the prevention and control of the coal and gas outbursts disaster. Therefore, in this study, a strain of methane-oxidizing bacteria M07 with high-pressure resistance, strong resistance, and high methane degradation rate was selected from coal mines. The growth and degradation abilities of M07 in chelating wetting agent solutions to assess its adaptability and find the optimal agent-to-M07 ratio. It provides a new method for integrating the reduction of impact tendency and gas pressure in deep coal mines. The experimental results show that M07 is a Gram-positive bacterium of the genus Bacillus, which has strong resistance and adaptability to high-pressure water injection. By degrading 70 mol of methane, M07 produces 1 mol of carbon dioxide, which can reduce gas pressure and reduce the risk of gas outbursts in coal mines. As the experiment proves, the best effect was achieved when the M07 concentration of the chelating wetting agent was 0.05%. The methane-oxidizing bacteria based on the chelating wetting agent as carriers prove a new prevention and control method for the integrated prevention and control of coal and gas outbursts in coal mines and also provide a new idea for microbial application in coal mine disaster control.