Innovative Control Strategies Research Articles

Insights into the Cell Division of Neospora caninum.

Neospora caninum is an apicomplexan protozoan parasite responsible for causing neosporosis in a range of animal species. It results in substantial economic losses in the livestock industry and poses significant health risks to companion and wild animals. Central to its survival and pathogenicity is the process of cell division, which remains poorly understood in this parasite. In this study, we explored the cell division of Neospora caninum using a combination of modern and classic imaging tools, emphasizing its pivotal role in perpetuating the parasite's life cycle and contributing to its ability to persist within host organisms. We described the intricacies of endodyogeny in Neospora caninum, detailing the dynamics of the cell assembly and the nuclear division by ultrastructure expansion microscopy and regular confocal microscopy. Furthermore, we explored the centrosome dynamics, the centrioles and the apicoplast through the advancement of the cell cycle. Our analysis described with unprecedented detail, the endodyogeny in this parasite. By advancing our understanding of these molecular mechanisms, we aimed to inspire innovative strategies for disease management and control, with the ultimate goal of mitigating the devastating impact of neosporosis on animal health and welfare.

Energy Optimization of Marine Drive Systems with Permanent Magnet Synchronous Motors

The International Maritime Organization are introducing more and more stringent requirements concerning increasing ships’ energy efficiency. They are becoming a huge challenge for design engineers. This article proposes a method to increase the energy efficiency of mechatronic drive systems in ship systems via the use of highly efficient electric permanent magnet synchronous motors (PMSMs). An innovative control strategy is suggested. It is based on the modification of the classic PMSM control and ensuring energy optimization through a reduction in reactive power in the Active Converter–PMSM system. Analytical and simulation studies using the Matlab–Simulink program are presented. They confirm the possibility of reducing reactive power in a PMSM drive system. A verification of the results of analytical and simulation examinations was conducted at a laboratory station with the use of the Speedgoat module operating in the Rapid Control Prototyping mode. Both the simulation and experimental research results indicate the effectiveness of the proposed PMSM control method. This method has good prospects for application in energy-saving marine drive systems.

Adaptive output-constrained finite-time formation control for multiple unmanned surface vessels with directed communication topology

This paper tackles the intricate task of leader-following formation control for multiple unmanned surface vessels (USVs) operating over a directed communication network. Our investigation takes into meticulous consideration several critical variables, including prescribed output constraints, the presence of enigmatic dynamics, and the pervasive influence of external disturbances on each individual USV. Our methodology commences with the introduction of an ingenious output transformation technique, which adeptly converts constrained output variables into their unconstrained counterparts. Subsequently, we craft a novel distributed tracking error metric, artfully harnessing the potential of the transformed output. We build an adaptive, non-singular finite-time formation controller, firmly rooted in the backstepping framework. This controller seamlessly integrates vital components such as virtual velocity control, command filters, neural networks, and parametric adaptive strategies, which is underpinned by our meticulous attention to maintaining C1 continuity within our proposed virtual control law. Furthermore, we introduce the concept of minimum parameter learning, a strategic inclusion aimed at streamlining the computational demands of our controller. Significantly, any potential output overshoot resulting from minimum parameter learning is adeptly managed through our innovative output-constrained control strategy. To substantiate the effectiveness and robustness of our approach, we provide an exhaustive stability analysis, which offers conclusive evidence of our controller’s performance under a diverse array of conditions.

Adaptive eco-cruising control for connected electric vehicles considering a dynamic preceding vehicle

Energy consumption and driving safety of a vehicle are greatly influenced by the driving behaviors of the vehicle in front (also termed the preceding vehicle). Inappropriate responses to unanticipated changes in the preceding vehicle can lead to decreased energy efficiency and an increased risk of rear-end collisions. To address this issue, this study proposes an innovative Adaptive Eco-cruising Control Strategy (AECS) for connected electric vehicles (CEVs) considering the dynamic behavior prediction of the preceding vehicle. The AECS, which is designed with a two-stage receding horizon control framework, can adapt to scenarios where the preceding vehicle cuts in or moves out in a safer and energy-efficient manner compared to traditional eco-cruising strategies, which merely focus on a constant preceding vehicle. In the first stage, a prediction model for characterizing the dynamic behavior of preceding vehicles is developed using the Bayesian network. This model is trained using real-world vehicle driving data, allowing it to anticipate the driving trajectories of vehicles changing lanes in front. In the second stage, an energy-saving, safety, and driving comfort-oriented optimization problem is formulated as a quadratic programming form. The eco-cruising speed is then optimized to adapt to the dynamic traffic environment, especially when the preceding vehicle changes over time. Finally, several simulations are conducted to validate the AECS. The results demonstrate that the AECS can improve the energy efficiency of CEVs by up to 11.80% and 19.53% on average compared to the existing cruise control strategies and ensure vehicle driving safety and comfort, without compromising travel time. Additionally, the vehicle cut-in position, the cut-in vehicle speed, and the ego vehicle speed affect the energy efficiency improvement performance of the AECS.

Weighting factors design in model predictive direct torque control based on cascaded neural network

AbstractAn innovative control strategy is introduced in this paper for model predictive direct torque control (MPDTC) of a permanent magnet synchronous motor (PMSM) inverter, which is based on a cascaded neural network for the automatic selection and online tuning of weighting factors. Specifically, the lower network in the proposed two‐stage cascaded network is trained by utilizing the weighting factors and the corresponding converter parameters under a specific working condition to establish data substitution models under that working condition and determine the fitness function for obtaining the optimal weighting factors. The upper network of the cascaded network is trained using various working conditions and their corresponding optimal weighting factors calculated by the lower network, with the goal of achieving real‐time tuning of the weighting factors under variable working conditions. By employing a data‐driven method to design the weighting factors at each working condition offline, this method reduces online tuning to a single calculation in the upper network and minimizes the online calculation burden. This approach enables the weighting factors to be adjusted in real‐time according to changes in the working conditions, leading to enhanced accuracy of weighting factor optimization. Experimental results demonstrate that the proposed strategy improves the overall performance of the inverters.

A Model-Free Control Scheme for Rehabilitation Robots: Integrating Real-Time Observations with a Deep Neural Network for Enhanced Control and Reliability

Effective control of rehabilitation robots is of paramount importance and requires increased attention to achieve a fully reliable, automated system for practical applications. As the domain of robotic rehabilitation progresses rapidly, the imperative for precise and dependable control mechanisms grows. In this study, we present an innovative control scheme integrating state-of-the-art machine learning algorithms with traditional control techniques. Our approach offers enhanced adaptability to patient-specific needs while ensuring safety and effectiveness. We introduce a model-free feedback linearization control method underpinned by deep neural networks and online observation. While our controller is model-free, and system dynamics are learned during training phases, we employ an online observer to robustly estimate uncertainties that the systems may face in real-time, beyond their training. The proposed technique was tested through different simulations with varying initial conditions and step references, demonstrating the controller’s robustness and adaptability. These simulations, combined with Lyapunov’s stability verification, validate the efficacy of our proposed scheme in effectively controlling the system under diverse conditions.

Allo Beta Cell transplantation: specific features, unanswered questions, and immunological challenge.

Type 1 diabetes (T1D) presents a persistent medical challenge, demanding innovative strategies for sustained glycemic control and enhanced patient well-being. Beta cells are specialized cells in the pancreas that produce insulin, a hormone that regulates blood sugar levels. When beta cells are damaged or destroyed, insulin production decreases, which leads to T1D. Allo Beta Cell Transplantation has emerged as a promising therapeutic avenue, with the goal of reinstating glucose regulation and insulin production in T1D patients. However, the path to success in this approach is fraught with complex immunological hurdles that demand rigorous exploration and resolution for enduring therapeutic efficacy. This exploration focuses on the distinct immunological characteristics inherent to Allo Beta Cell Transplantation. An understanding of these unique challenges is pivotal for the development of effective therapeutic interventions. The critical role of glucose regulation and insulin in immune activation is emphasized, with an emphasis on the intricate interplay between beta cells and immune cells. The transplantation site, particularly the liver, is examined in depth, highlighting its relevance in the context of complex immunological issues. Scrutiny extends to recipient and donor matching, including the utilization of multiple islet donors, while also considering the potential risk of autoimmune recurrence. Moreover, unanswered questions and persistent gaps in knowledge within the field are identified. These include the absence of robust evidence supporting immunosuppression treatments, the need for reliable methods to assess rejection and treatment protocols, the lack of validated biomarkers for monitoring beta cell loss, and the imperative need for improved beta cell imaging techniques. In addition, attention is drawn to emerging directions and transformative strategies in the field. This encompasses alternative immunosuppressive regimens and calcineurin-free immunoprotocols, as well as a reevaluation of induction therapy and recipient preconditioning methods. Innovative approaches targeting autoimmune recurrence, such as CAR Tregs and TCR Tregs, are explored, along with the potential of stem stealth cells, tissue engineering, and encapsulation to overcome the risk of graft rejection. In summary, this review provides a comprehensive overview of the inherent immunological obstacles associated with Allo Beta Cell Transplantation. It offers valuable insights into emerging strategies and directions that hold great promise for advancing the field and ultimately improving outcomes for individuals living with diabetes.

Unveiling the global reach of African anthrax research: A bibliometric study

Anthrax is a zoonotic bacterial disease caused by Bacillus anthracis. It poses significant threat to humans through contact with infected animals or their by-products. Concerns arise from its long-lasting spore viability and lethality, fuelling its biowarfare potential. Recent anthrax outbreaks across multiple African nations prompted this bibliometric study. The aim of the study was to assess the contributions of African countries, institutions, authors, research funding, and collaborations, while identifying research trends and gaps. We conducted an extensive bibliometric analysis of anthrax-related research publications in Africa from 1923 to 2023, utilizing the Scopus database and VOSviewer. The study covered 364 publications from 32 African countries, accumulating 5,636 citations at an average of 15.5 citations per article, with research articles comprising 88.5% of the corpus. The publication growth rate from 1923 to 2023 was modest at 8.3%, indicating gradual advancement. Notably, there was a significant surge in publications between 2011 and 2023, accounting for 73.1% of total publications. The African research contributions, were categorized into five thematic focuses: ecological dynamics and host interactions, human–livestock anthrax interface, molecular insights into bacterial activity and treatment strategies, collaborative approaches for zoonotic disease prevention, and antibody response and vaccination strategies. Leading institutional contributors included the University of Pretoria and the University of KwaZulu-Natal. Collaborations extended globally to 35 non-African countries, with significant involvement from the United States, United Kingdom, and Germany. Strong African partnerships, especially between Kenya, Nigeria, and South Africa, emerged. The top 10 cited papers explored diverse aspects, including disease impact on wildlife and innovative control strategies, underscoring the importance of multidisciplinary approaches. South Africa played a prominent role, contributing 95 publications and securing funding from various sources, including the National Research Foundation. Collaborations with global institutions highlighted its commitment. This study unveils the dynamic landscape of anthrax research in Africa, emphasizing the pivotal role of collaboration, multidisciplinary One Health approaches, and global partnerships in enhancing research outcomes. Ongoing research and practical solutions for human and animal health remain imperative.

Event-triggered control design with varying gains for polynomial fuzzy systems against DoS attacks

This paper presents an innovative event-triggered control scheme for addressing the stabilization problem of polynomial fuzzy systems under the influence of Denial-of-Service (DoS) attacks. The proposed controller utilizes a sampling-based event-triggered mechanism to reduce communication resources and avoid Zeno behavior. Furthermore, a novel polynomial fuzzy model-based control system is developed to investigate the impact of periodic DoS attacks and the addressed event-triggered mechanism on system stability. To improve system performance, control gains are updated at each triggering instant. The exponential stability criteria are formulated in the form of sum-of-square constraints, supported by a triggering instant dependent piecewise Lyapunov-Krasovskii functional and an online asynchronous premise reconstruction approach. Finally, the efficiency and usefulness of the theoretical findings are validated through simulation examples.

Control strategy and verification of reducing battery polarization characteristics to improve unmanned aerial vehicles endurance

This study focuses on extending the duration of unmanned aerial vehicles (UAVs) by improving their power systems and introduces an extended endurance system (EES) for UAVs using a combination of lithium-ion batteries (LiBs) and lithium-ion capacitors (LiCs). Subsequently, a novel control strategy is proposed within the EES to enhance the UAV's endurance by improving the LiB's utilization. The EES control strategy incorporates the Lic's utilization to supplement the load with additional energy once the LiB is depleted. This implementation extends the flight duration and surpasses the duration extension resulting from reducing the LiB concentration polarization phenomenon due to the LiC. The hardware experiment and the simulation verify the proposed EES. The results indicate that the extension of UAV's endurance brought about by LiC is limited. Notably, the extension in endurance is primarily attributed to the innovative control strategy implemented within the proposed EES. Due to the LiC, this strategy significantly enhances the LiB's utilization by mitigating the concentration polarization phenomenon associated with it. As a result, the LiB's energy (utilization%) experiences substantial increments of 16.0 %, 25.5 %, and 22.7 % during hovering, altitude variation, and loaded hovering scenarios, respectively.

Fungsi Anggaran Sebagai Alat Perencanaan Dan Pengendalian Pada Birorena Polda Sumut

In this journal the author analyzes the crucial role of the budget as the main tool in planning and control at the North Sumatra Regional Police Bureau (North Sumatra). This research covers budget allocation, budget integration in the planning process, as well as implemented budget control strategies. The research results show that the North Sumatra Regional Police Bureau effectively uses the budget as a guide for the smooth running of activities, programs and projects that support the North Sumatra Regional Police's strategic objectives. The budget also functions as a control instrument that allows monitoring of expenditure and identifying deviations for taking corrective action. Good coordination between the Bureaurena and other units in the North Sumatra Regional Police strengthens the effectiveness of budget use. In its discussion, this journal provides recommendations for improvement, including increasing the efficiency of the planning process, strengthening coordination between units, and implementing more innovative budget control strategies. The conclusion highlights the importance of viewing the budget not just as an administrative tool, but also as a catalyst for achieving overall organizational goals. This journal provides practical insights for similar organizations in improving their management budgets to achieve more optimal performance.

Non-quantum chirality and periodic islands in the driven double pendulum system

The paper presents a systematic investigation of the dynamic complexities exhibited by a driven double pendulum system. By utilizing isospike diagrams in the frequency–amplitude control parameter space, a wide range of novel dynamical behaviors are explored. In addition to the well-known shrimp-shaped period island, the study uncovers various unique self-organizations, including the quint point where five distinct stable oscillatory phases coalesce, the eye of chaos characterized by a nested ring structure resulting from forward and reverse cascades, and innovative non-quantum chiral structures. The observed chiral structures in the double pendulum system exist in more diverse and generalized structure, challenging the notion that ring structures are necessary for their emergence. Furthermore, the study reports the experimental observation of a newly generated parabolic phase near the quint point, validating the phenomena observed through numerical calculations in experiments. These findings not only advance our understanding of the control parameter space topology for driven double pendulums but also lay the foundation for the exploration of innovative control strategies.

International Coordination of Research on Infectious Animal Diseases (ICRAD) First Call: Editorial and Abstracts

The ICRAD ERA-NET launched its first call in 2020, with funding partners from twenty European countries. The aim was to foster a collaborative and interdisciplinary approach towards developing innovative instruments for the control and prevention of animal infectious diseases. Particularly, with a focus on creating vaccine and diagnostic technology platforms to enhance preparedness for major epidemic threats such as African swine fever and animal influenza. The first ICRAD call received significant support, totaling €17.4 million from partner countries alongside an additional €6.7 million top-up from the European Commission (EC). These funds were allocated to nineteen research project consortiums, consisting of researchers from across Europe. Through their collective efforts, these consortia have made remarkable progress in addressing various infectious disease risks faced by European animal health and the livestock industry. The following text encapsulates abstracts from eleven out of the nineteen projects that received funding through the first ICRAD research call. It’s noteworthy to observe that several of these projects are addressing pressing issues related to ongoing animal health outbreaks. For instance, three of these funded projects are dedicated to enhancing our comprehension of the African swine fever virus (ASFV) and fostering the development of a potential vaccine. Another project is honing its focus on avian influenza, with the objective of deciphering the factors contributing to increased virulence in low pathogenic avian influenza (LPAI) viruses. This could potentially enable us to better predict the severity of emerging avian influenza virus (AIV) strains. In addition, there are several other projects that align seamlessly with the overarching goals of ICRAD. These include but are not limited to, the development of innovative DNA vaccine technologies and the creation of diagnostic tools for a spectrum of pig diseases. Overall, we have funded a range of projects that align excellently with the overall goals of ICRAD, supporting innovative, cross-cutting research on animal health and welfare, with associated benefits for the environment and the economy. These projects represent significant strides in improving animal health, welfare, and food production throughout Europe. By fostering collaboration between partner institutes and bringing together experts from various countries and disciplines, these joint efforts can effectively combine knowledge, resources, and expertise to address complex challenges and threats. This coordination is crucial for identifying, preventing, and responding to emerging animal diseases that could not only endanger animal health but also have direct or indirect implications for human well-being. Moreover, this cross-border cooperation can yield more comprehensive research outcomes while developing innovative solutions and strategies for disease prevention and control. Ultimately, international scientific coordination on animal health showcased in the following abstracts demonstrates a strong commitment to cooperation while providing robust evidence to safeguard the health of animals, humans, and the environment. ICRAD, which organized this call and allocated grants to these projects is an ERA-NET, a co-funded project under the European Union’s Horizon 2020 Research and Innovation program.

Dual Random Noise Suppression Strategy for Permanent Magnet Synchronous Motor Based on Random Pulse Width Modulation and Random High-frequency Injection Method

This study proposes an innovative dual control strategy to tackle the challenge of electromagnetic noise in the sensorless low-speed operation of Permanent Magnet Synchronous Motors (PMSM). The strategy combines random Pulse Width Modulation (PWM) technology with a stochastic high-frequency injection approach. By incorporating two distinct randomized frequency switching techniques into the high-frequency injection circuit, the method integrates two-state Markov chains into both PWM technology and the random high-frequency injection method. Subsequently, a mathematical model for signal processing is developed, and extensive simulation and experimental verification are conducted. The experimental findings affirm the effectiveness of this approach in effectively mitigating electromagnetic noise while ensuring accurate location estimation within an acceptable range.

Fuzzy nonsingular fast terminal sliding mode controller for a robotic system

This study introduces an innovative control strategy utilizing a nonsingular fast sliding mode technique tailored for robotic systems. The core of this approach lies in the development of a type-2 fuzzy logic-based nominal model, meticulously designed to accurately approximate the dynamics of the real system while adeptly handling the variability in system parameters. This method marks a departure from conventional approaches by inferring the switch signal for type-2 adaptive fuzzy systems, a critical step in achieving superior tracking performance without the necessity for extensive knowledge of the system's upper bounds in uncertainties and external disturbances. The efficacy of the proposed control law is rigorously validated through a series of simulations, encompassing a variety of initial conditions and reference signals, thereby demonstrating its robust performance capabilities.

Salt tide affecting algae-laden micropolluted surface water treatment and membrane performance based on BDD electro-oxidation coupled with ceramic membrane process

Harmful algal blooms pose an emerging threat to freshwater ecological security and human health, necessitating further study in offshore areas. In this work, boron-doped diamond electro-oxidation (BDD/EO) coupled with a ceramic membrane filtration was employed aiming to assess the salt tide affecting algae-laden water treatment involving with various natural organic matters (e.g., HA, SA, and BSA). The results have demonstrated that BDD/EO remove chlorophyll from the algae-laden water effectively due to the inactivation of algal cells. Moreover, considering the influence of salt tide, NH3–N would be mainly oxidized through the in-situ generated active chlorine at the electrode-liquid interface. In addition, in three kinds of salt tide affecting algae-laden water, TOC content in BSA group was decreasing remarkably after BDD/EO with TOC removal efficiency above 80%; while those in HA and SA groups had no obvious reducing due to the more algae cells breakage synchronous with HA and SA removal. Based on the fluorescent characteristics and particle size distribution, the generated small molecular organics after electro-oxidation might raise the pore blockage probability and the hydrophobic organic and fluorescent substances were preferentially oxidized in BDD/EO process being beneficial to reducing membrane fouling. Besides, the membrane special flux in three groups were decreasing significantly and the irreversible fouling resistance in SA group accounted for a larger proportion of the total resistance than those of HA and BSA. At last, in BDD/EO-CM process, macromolecular substances degradation rate was greater than that of small molecules based on the molecular weight distribution in three groups of salt tide affected algae-laden water treatment. In a word, this work provides effective and innovative strategies for the harmful algal bloom control and contributes interesting insights of membrane fouling performance of electrochemical coupled ultrafiltration membrane process.

Stable Walking Feedback Control for a Self-Balanced Lower Limb Exoskeleton for Paraplegics

Self-Balanced lower limb exoskeleton (SBLLE) is designed for rehabilitation and walking assistance for dyskinesia persons with spinal or lower limb muscle injury to regain the locomotion ability in daily activities. In this paper, an innovative feedback control strategy for a fully actuated SBLLE is presented, which helps users to walk stably without crutches or other assistive devices. Exoskeleton is approximated as a simplified center of mass (CoM) model. Based on this simplified dynamic model, the trajectory generation and walking feedback control strategy, which enhances the locomotion stability, is introduced. The proposed strategy is implemented on our exoskeleton, AutoLEE-II, and its stability and dynamic performance are demonstrated in the stable walking simulations and experiments for exoskeleton with a female subject.

Torque Vectoring Control Strategies Comparison for Hybrid Vehicles with Two Rear Electric Motors

In today’s automotive industry, electrification is a major trend. In-wheel electric motors are among the most promising technologies yet to be fully developed. Indeed, the presence of multiple in-wheel motors acting as independent actuators allows for the implementation of innovative active systems and control strategies. This paper analyzes different design possibilities for a torque vectoring system applied to an originally compact front-wheel drive hybrid electric vehicle with one internal combustion engine for the front axle and two added electric motors integrated in the wheels of the rear axle. A 14 degrees of freedom vehicle model is present o accurately reproduce the nonlinearities of vehicle dynamic phenomena and exploited to obtain high-fidelity numerical simulation results. Different control methods are compared, a PID, an LQR, and four different sliding mode control strategies. All controllers achieve sufficiently good results in terms of lateral dynamics compared with the basic hybrid version. The various aspects and features of the different strategies are analyzed and discussed. Chattering reduction strategies are developed to improve the performance of sliding mode controllers. For a complete overview, control systems are compared using a performance factor that weighs control accuracy and effort in different driving maneuvers, i.e., ramp and step steering maneuvers performed under quite different conditions ranging up to the limits.

Trajectory Tracking Control of Unmanned Surface Vehicles Based on a Fixed-Time Disturbance Observer

In ocean environments with unknown complex disturbances, the control accuracy for an unmanned surface vehicle (USV) is severely challenged with an increase in task complexity. As the foundation for executing complex tasks, it is particularly important to control a USV to navigate along a safe trajectory that has been set. In order to effectively handle the trajectory tracking problem, an innovative USV tracking control strategy with high accuracy is proposed by combining the integral sliding-mode and disturbance observer technologies, and these are effectively extended to a scenario with the cooperative trajectory tracking of multiple USVs in this study. Specifically, unknown disturbances are treated as lumped uncertainties, and a novel fixed-time stable-convergence disturbance observer (FT-DO) is proposed to effectively observe and approximate the lumped uncertainties. Then, in order to quickly reach and steadily navigate along the desired trajectory, an effective fixed-time stable-convergence fast integral sliding mode is modified, and on this basis, an accurate trajectory tracking controller (FTFISM-TTC) for a single USV and a cooperative trajectory tracking controller for multiple USVs are meaningfully proposed. Finally, the stability of FT-DO and FTFISM-TTC was rigorously proven by using the Lyapunov approach, and a comprehensive simulation of current advanced tracking control methods was conducted by using Matlab, which proved the reliability of the proposed trajectory tracking control strategy and further eliminated the impact of the initial state on the tracking accuracy.

CMC Strategies and Advanced Technologies for Vaccine Development to Boost Acceleration and Pandemic Preparedness.

This review reports on an overview of key enablers of acceleration/pandemic and preparedness, covering CMC strategies as well as technical innovations in vaccine development. Considerations are shared on implementation hurdles and opportunities to drive sustained acceleration for vaccine development and considers learnings from the COVID pandemic and direct experience in addressing unmet medical needs. These reflections focus on (i) the importance of a cross-disciplinary framework of technical expectations ranging from target antigen identification to launch and life-cycle management; (ii) the use of prior platform knowledge across similar or products/vaccine types; (iii) the implementation of innovation and digital tools for fast development and innovative control strategies.