Steering Control Research Articles

A review of research on tire burst and vehicle stability control.

Tire burst is an accidental occurrence that poses a serious threat to the driving stability and road safety of vehicles. Therefore, it is of great practical significance to investigate early warning systems for tire burst and develop stability and safety control measures after burst incidents. The development of an accurate model that can effectively represent the impact of tire burst on vehicle dynamics is crucial for the design of control systems and the development of stability control strategies. Most of the existing research on tire burst models is based on static tire tests, the effectiveness of these models still needs to be further verified. The main approach to studying the impact of burst tires on vehicle performance is to embed a burst tire model into a vehicle dynamics model. Understanding the impact of tire burst on vehicle performance is essential for identifying burst incidents and developing stability control strategies. The research on burst identification primarily focuses on early warning systems and estimating vehicle state parameters after burst incidents, while the current research on stability control strategies focuses on enabling vehicles to continue running safely after burst incidents through braking, active steering, and collaborative control. Currently, there is no comprehensive review of research on vehicle tire burst stability control. Therefore, this paper primarily reviews five aspects: (a) the causes and prevention of tire burst, (b) the impact of tire burst on vehicle performance, (c) burst identification, (d) stability control strategies for burst incidents, and (e) future prospects for tire burst research.

Formal modeling and verification method for Simulink-MDL requirement model

Abstract As complex safety-critical system software becomes more powerful, so does the complexity of its design requirements. Modeling and analyzing design requirements at an early stage has become an integral part of the entire development process for complex safety-critical system software. Simulink is a system modeling and simulation tool used in aviation and other fields. Its model is stored in the form of MDL files. ART (Avionics Requirement Tools) is a requirement modeling and analysis verification tool for the aviation field. It uses VRM (Variable Relation Model) as the theoretical model and can accept VRM and its extended subsets as input models and verify them in the tool. The work of this paper is oriented to the typical software requirements in the field of avionics systems and proposes a formal modeling and verification method for Simulink-MDL models. First, the composition form and structure of the MDL model are analyzed in the article. The functions and semantics of various elements in the model are given. Then a formal modeling method of the MDL model is given. Finally, a simplified version of the flight guidance control system is used for modeling and verification to demonstrate the usability and effectiveness of this method.

Outbreak of New Delhi Metallo-β-lactamase-producing Escherichia coli in a Neonatal Intensive Care Unit, New York State

Background: Outbreaks of carbapenemase-producing (CP) organisms (CPOs), including carbapenem-resistant Enterobacterales (CRE), in neonatal intensive care units (NICUs) are not well documented. The Centers for Disease Control and Prevention (CDC) identifies CP-CRE as an urgent threat to United States (US) healthcare facilities. Wadsworth Center, the New York State (NYS) Department of Health’s (NYSDOH’s) public health laboratory, participates in CDC’s Antimicrobial Resistance Laboratory Network to provide CPO identification, characterization, and surveillance. NYSDOH investigated an outbreak of CP-CRE Escherichia coli (E. coli) infections in NICU patients reported by one hospital. Method: Hospital A reported a CRE E. coli outbreak in their NICU to NYSDOH, as required by NYS Sanitary Code. In response, epidemiologists reviewed case data, conducted case finding, and provided infection control guidance to the hospital. Hospital A continued NICU clinical surveillance and conducted colonization screening to detect additional cases of CRE E. coli. The Wadsworth Center Antimicrobial Resistance Laboratory Network tested isolates from affected patients for CP genes and performed whole genome sequencing (WGS) to determine the CP gene variant, multilocus sequence type (MLST), and relatedness by mutation event (ME) analysis. NYSDOH epidemiologists assessed Hospital A’s infection control practices in affected areas and provided recommendations. Result: Hospital A identified two CRE E. coli infections in NICU patients with overlapping admissions in June-July 2023. Retrospective surveillance identified a third CRE E. coli case in an adult medical intensive care unit patient on admission to Hospital A in June 2023, with prior hospitalization April-May 2023. WGS analysis identified the blaNDM-5 gene in all three CRE E. coli patient isolates. The two NICU patients’ isolates had the same MLST (361/650) and differed by 9 MEs, indicating relatedness to each other and not the adult patient’s (MLST 167/2). NICU patient colonization screening identified no additional blaNDM-5 E. coli cases. NYSDOH’s NICU infection control assessment found that both cases were in adjacent isolettes within three feet of each other. Clean isolettes, equipment, and supplies for new admissions were stored in the clinical care space, not in a separate clean area. Conclusion: CP-CRE is an urgent threat to US healthcare facilities, including hospital NICUs. Though the incidence and prevalence of CP-CRE blaNDM-5 E. coli are not well-defined in NY, single healthcare-associated cases in NICU populations represent an outbreak. The Wadsworth Center Antimicrobial Resistance Laboratory Network’s contributions complement traditional epidemiologic surveillance and investigation methods to provide more specific, comprehensive infection

Data-Driven-Method-Based Guidance Law for Impact Time and Angle Constraints

To increase the hit efficiency and lethality of a flight vehicle, it is necessary to consider the vehicle’s guidance law concerning both impact time and angle constraints. In this study, a novel and straightforward impact time and angle control guidance law that is independent of time-to-go and small angle approximations is proposed with two stages using a data-driven method and proportional navigation guidance. First, a proportional navigation guidance-based impact angle control guidance law is designed for the second stage. Second, from various initial conditions on the impact angle control guidance simulation with various initial conditions, the input and output datasets are obtained to build a mapping network. Using the neural network technique, a mapping network model that can output the ideal flight path angle in flight is constructed for impact time control in the first stage. The proposed impact time and angle control guidance law reduces to the proportional navigation guidance law when the flight path angle error converges to zero. The simulation results show that the proposed guidance law delivers excellent performance under various conditions (including cooperative attack) and features better acceleration performance and less control energy than does the comparative impact time and angle control guidance law. The results of this research are expected to supplement those exploring various paradigms to solve the impact time and angle control guidance problem, as concluded in the current literature.

Radar Defense and Active Interception of Kamikaze Drones

The modern combat environment is marked by the active use of kamikaze drones, posing a serious threat to lightly armored vehicles. The development of radar technologies combined with microcontroller-based control systems allows for the effective detection and neutralization of these threats. This paper examines a complex of technical means for detecting and countering kamikaze drones, utilizing radar detection and active interception methods. An analysis of existing solutions in this field is conducted, highlighting their advantages and disadvantages, and technical proposals for constructing a radar control system, guidance unit, and countermeasure device are provided. Special attention is given to the integration of systems to enhance efficiency and automate processes. The presented results confirm the feasibility and effectiveness of the proposed solutions in real combat conditions, as evidenced by their application during Russia's war against Ukraine.

Sizing energy storage in electricity grids containing flexible loads

Flexible loads such as EV chargers and heat pumps have the potential to reduce the amount of energy storage required to handle local power imbalances. However, when sizing energy storage these loads are often neglected. Thereby it is unclear how intelligently controlled flexible loads influence energy storage sizing. Therefore, this paper presents an empirical study into the effect of controlling four different classes of flexible loads on energy storage sizing, under which fall existing technologies such as EV chargers, heat pumps and white-goods. We use a Profile Steering control strategy to minimize the power imbalance over the considered period. Furthermore, we use parameter sweeps to investigate the influences of load availability and load demand on the energy storage sizing, and visualize the energy storage reduction with heat maps. The results show that significant energy storage sizing reductions are possible if flexible loads are considered, including a reduction in capacity of more than 60%. Furthermore, if flexible loads can also supply their buffered power to the local microgrid (such as with V2G applications), the need for energy storage is almost completely removed. We conclude that it is important to consider local flexible devices when sizing storage in order to avoid over-dimensioning.

Pengembangan Modul Pelatihan Bagi Orang Tua Dalam Pendampingan Belajar Siswa Dari Rumah Pascapandemi Covid-19

This study aims to describe the role of parents in accompanying students during and after the COVID-19 pandemic at SMP Negeri 13 Ambon and SMP Negeri 20 Ambon. It explores the challenges, disadvantages, and strengths of parental involvement in home-based learning during and after the pandemic, and presents a training module for parents to assist students learning post-pandemic. This research employs a research and development (RnD) approach with a qualitative descriptive method, focusing on product creation. Data were collected through document studies, observations, and in-depth interviews, and validated using source and technique triangulation. Data analysis followed the Miles and Huberman Model. The findings are: During the COVID-19 pandemic, parents at SMP Negeri 13 Ambon and SMP Negeri 20 Ambon provided some assistance for home-based learning, but it was not fully effective due to varying conditions and parents' limited understanding of the online learning process, compounded by some parents' technological illiteracy. Post-pandemic, parental assistance returned to normal, with some parents struggling to motivate their children, who preferred in-person learning and social interactions at school. The primary obstacles faced by parents included poor internet connectivity, high data costs, and frequent power outages, while the strengths included increased attention, encouragement, guidance, and direct control over children's learning at home. A training module for parents was developed, comprising a module book with guides for learning activities that can be implemented by teachers, parents, and students.

Exploring the implementation of COVID‐19 infection control guidance in congregate living settings supporting those with intellectual and developmental disabilities

Exploring the implementation of <scp>COVID</scp>‐19 infection control guidance in congregate living settings supporting those with intellectual and developmental disabilities

Design and comparison of particle swarm optimization tuned Kalman filter based linear quadratic Gaussian controller and linear quadratic regulator for surface to air missile guidance system

AbstractThe study of missile guidance systems is a well‐known nonlinear control engineering area of research. To enhance the control performance of a missle guidance system, several technologies have been proposed in existing works. To resolve the weighting matrix selection issue of a linear quadratic Gaussian (LQG) controller for the surface‐to‐air missile guidance control system, this study utilizes the particle swarm optimization (PSO) technique. Selecting the best state (Q) and input (R) weighting matrices is a significant difficulty in the design of the LQG controller for real‐time applications since it affects the controller's performance and optimality. The weighting matrices are often chosen by a trial‐and‐error method that not only complicates the design but also does not yield optimal outcomes. Therefore, in this paper, a PSO method is developed and used in the design of the linear quadratic regulator (LQR) and LQG controllers for the surface‐to‐air missile control system to choose the elements of the Q and R matrices in the best possible way. Finally, a comparative analysis between the designed controllers was presented. The results shows that a good performance was achieved by using the proposed PSO‐tuned design process. The LQG and LQR are designed by manually adjusting the weighting matrices and utilizing an intelligent procedure, PSO algorithm which achieved optimal results. Further results indicate that the designed controllers, the PSO tuned LQR and LQG achieved a better performance over the manually adjusted LQR and LQG controllers.

Genetically modified live vaccine offers protective immunity against wild-type Anaplasma marginale tick-transmission challenge

Anaplasma marginale is a tick-borne pathogen of cattle that causes bovine anaplasmosis in tropical and subtropical regions throughout the world. Killed vaccines derived from infected erythrocytes have been used for control of this disease with limited success. Recently, we described a targeted deletion mutation in the phage head-to-tail connector protein gene of A. marginale which caused bacterial attenuation in vivo and provided protection as a modified live vaccine (MLAV). Following intravenous injection of susceptible steers, the MLAV induced protective immunity against disease progression. In the current study, we demonstrated that the immunity resulting from MLAV in cattle prevents the disease progression resulting from virulent A. marginale intrastadial transmission from infected Dermacentor variabilis male ticks. The nonimmunized control steers receiving the infection from ticks developed fever, lethargy, and inappetence for several days post tick exposure with significant decreases in the packed cell volume and increases in bacteremia. In contrast, the MLAV immunized steers remained healthy after being challenged with infected ticks and this group of animals had a significant reduction in bacteremia as compared with the controls. This study demonstrated that the A. marginale MLAV provided protection against acute tick-transmitted anaplasmosis, in addition to protection documented in steers challenge-exposed with infected blood as reported previously.

Safe Autonomous Docking of Spacecraft: A RRT-combined Output-constrained Recursive Control Method

In addressing the challenges of short-range spacecraft docking in the presence of obstacles and disturbances, it is critical to integrate guidance and motion control to ensure autonomous and reliable operation. Traditional methods that separate these two layers often struggle with accurately tracking predefined paths, increasing the risk of collisions. In light of this, a proposed scheme integrating guidance and control in an organic manner has been put forth. This scheme employs the rapidly-exploring random trees (RRT) algorithm within the guidance layer to generate a collision-avoidance trajectory for the control layer, efficiently navigating the spacecraft towards its target. Then the control layer implements a second-order output-constrained controller by adding a power integrator and a novel barrier Lyapunov function (BLF) together, to guarantee that the tracking error of the predefined trajectory remains bounded and the system asymptotically converges to the target. To account for tracking errors, obstacle radii are expanded during path planning through a dilation constant. Based on theoretical derivation and simulation experiments, the effectiveness and advancement of the proposed method are validated.

Preliminary Virtual Constraint-Based Control Evaluation on a Pediatric Lower-Limb Exoskeleton.

Pediatric gait rehabilitation and guidance strategies using robotic exoskeletons require a controller that encourages user volitional control and participation while guiding the wearer towards a stable gait cycle. Virtual constraint-based controllers have created stable gait cycles in bipedal robotic systems and have seen recent use in assistive exoskeletons. This paper evaluates a virtual constraint-based controller for pediatric gait guidance through comparison with a traditional time-dependent position tracking controller on a newly developed exoskeleton system. Walking experiments were performed with a healthy child subject wearing the exoskeleton under proportional-derivative control, virtual constraint-based control, and while unpowered. The participant questionnaires assessed the perceived exertion and controller usability measures, while sensors provided kinematic, control torque, and muscle activation data. The virtual constraint-based controller resulted in a gait similar to the proportional-derivative controlled gait but reduced the variability in the gait kinematics by 36.72% and 16.28% relative to unassisted gait in the hips and knees, respectively. The virtual constraint-based controller also used 35.89% and 4.44% less rms torque per gait cycle in the hips and knees, respectively. The user feedback indicated that the virtual constraint-based controller was intuitive and easy to utilize relative to the proportional-derivative controller. These results indicate that virtual constraint-based control has favorable characteristics for robot-assisted gait guidance.

Combination of H∞ perimeter control and route guidance for heterogeneous urban road networks

Due to the effects of capacity differences and other factors, congestion may occur at local nodes of a network. This situation reduces the reliability of the network and leads to regional deadlock. To improve system stability and reduce the influence of local road network heterogeneity on traffic efficiency, a macroscopic fundamental diagram (MFD) model of a nonuniform density road network is proposed. Second, based on the MFD model, a two-level strategy for H∞ perimeter control and traffic flow regulation is proposed. The upper layer uses an H∞ controller to adjust the inflow at the boundary of congested region. The lower layer uses a traffic density regulator (TDR) inside the region. Finally,a simulation is conducted to compare with traditional H∞ control, bang-bang-TDR, PI-TDR and MPC-TDR strategy. The results show that the H∞-TDR strategy proposed in this paper can improve operation efficiency and reduce delay in network.

Research on Risk Prevention and Resolution Strategies of College Network Ideology in the Context of the Internet

With the rapid development of the Internet, the network ideology of colleges and universities is facing severe challenges. This paper deeply analyzes the root of the risk of network ideology and makes a specific investigation of the status quo of network public opinion in colleges and universities. On this basis, the study explores and puts forward a series of targeted risk prevention and resolution strategies, aiming at providing a systematic solution for the network ideology security of colleges and universities. In this paper, with the combination of theory and practice as the path, we verify the effectiveness and applicability of the proposed strategy through the analysis of the implementation effect of the strategy. This study also provides theoretical support and practical guidance for the prevention and control of ideological risks and public opinion guidance in universities under the network environment, which has important practical significance. With the continuous progress of network technology, the threats to the network ideology of colleges and universities are increasing. For example, the spread of false information has become a serious problem affecting the security of college network ideology.

Convex-Optimization-Based Model Predictive Control for Space Debris Removal Mission Guidance

A convex-optimization-based model predictive control (MPC) algorithm for the guidance of active debris removal missions is proposed in this work. A high-accuracy reference for the convex optimization is obtained through a split-Edelbaum approach that takes the effects of J2, drag, and eclipses into account. When the spacecraft deviates significantly from the reference trajectory, a new reference is calculated through the same method to reach the target debris. When required, phasing is integrated into the transfer. During the mission, the phase of the spacecraft is adjusted to match that of the target debris at the end of the transfer by introducing intermediate waiting times. The robustness of the guidance scheme is tested in a high-fidelity dynamic model that includes thrust errors and misthrust events. The guidance algorithm performs well without requiring successive convex iterations. Monte Carlo simulations are conducted to analyze the impact of these thrust uncertainties on the guidance. Simulation results show that the proposed convex-MPC approach can ensure that the spacecraft can reach its target despite significant uncertainties and long-duration misthrust events.

Investigation of far-wake models coupled with yaw-induction control for power optimization

Combined wake steering and induction control is a promising strategy for increasing collective wind farm power production over standard turbine control. However, computationally efficient models for predicting optimal control set points still need to be tested against high-fidelity simulations, particularly in regimes of high rotor thrust. In this study, large eddy simulations (LES) are used to investigate a two-turbine array using actuator disk modeling in conventionally neutral atmospheric conditions. The thrust coefficient and yaw-misalignment angle are independently prescribed to the upwind turbine in each simulation while downwind turbine operation is fixed. Analyzing the LES velocity fields shows that near-wake length decreases and wake recovery rate increases with increasing thrust. We model the wake behavior with a physics-based near-wake and induction model coupled with a Gaussian far-wake model. The near-wake model predicts the turbine thrust and power depending on the wake steering and induction control set point. The initial wake velocities predicted by the near-wake model are validated against LES data, and a calibrated far-wake model is used to estimate the power maximizing control set point and power gain. Both model-predicted and LES optimal set points exhibit increases in yaw angle and thrust coefficient for the leading turbine relative to standard control. The model-optimal set point predicts a power gain of 18.1% while the LES optimal set point results in a power gain of 20.7%. In contrast, using a tuned cosine model for the power-yaw relationship results in a set point with a lower magnitude of yaw, a thrust coefficient lower than in standard control, and predicts a power gain of 13.7%. Using the physics-based, model-predicted set points in LES results in a power within 1.5% of optimal, showing potential for joint yaw-induction control as a method for predictably increasing wind farm power output.

Comparison of helix and wake steering control for varying turbine spacing and wind direction

A variety of wind farm control strategies exist in order to reduce unfavorable wake effects in large wind farms. While strategies like wake steering already reached a high maturity level, it is interesting to compare them to more recently proposed strategies. Such a comparison can form the basis for the development of a symbiotic wind farm control toolbox, from which a control strategy is chosen and activated depending on the operating conditions. The present study compares wake steering with helix control across a wide range of turbine spacings and wind directions using large-eddy simulation (LES). The size of the search space is made computationally tractable for LES by adopting a setup based on one physical upstream turbine and a distribution of virtual downstream turbines which do not exert any thrust force. It is found that helix control is beneficial for full wake overlap and turbine spacing of less than six rotor diameters whereas wake steering proves to be optimal further downstream and for partial wake overlap. Furthermore, the results show that the helix control setpoint in the proximity of full wake overlap scenarios is less susceptible to wind direction variations. This finding indicates that the combination of wake steering and helix control has potential for the design of a wind farm controller which is more robust in full wake overlap scenarios and can reduce the need for large yaw offset adjustments.

How do wind farm blockage and axial induction control interact?

Wake losses significantly reduce wind farm output, but wind farm flow control (WFFC) can substantially reduce these losses, using wake steering (yawing upstream turbines) and/or axial induction control (reducing turbine power and thrust to weaken their wakes). Previous work shows that ignoring wind farm blockage in traditional wake models represents a prediction bias of similar order to the gains achievable with WFFC. Axial induction control works by changing turbine thrust, which is also the cause of blockage; this raises the question of how the two effects interact. Induction control can more than compensate for any loss due to blockage, but here we investigate the relationship further. Induction control reduces turbine thrust coefficients to reduce wake losses, but this should also reduce blockage, suggesting that induction control might achieve higher gains in practice than predicted with blockage effects ignored. An engineering model for blockage effects was added to the wind farm code LongSim, and steady-state gains calculated for a well-known offshore wind farm, with and without blockage. The results confirm that the power gains are indeed higher if blockage is modelled. These results are corroborated by comparisons against RANS (Reynolds-Averaged Navier Stokes) simulations, in which blockage effects are implicitly modelled.

A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines

This paper presents a novel approach to constructing a load surrogate model. The surrogate estimates the damage equivalent loads (DELs) of a wind turbine of a given type regardless of its position within a wind farm, and under various farm control actions. The model relies solely on local inflow quantities (sector-averaged wind speeds and turbulence intensities) and local control parameters (rotor speed, pitch angle, and yaw misalignment). Despite its highly simplified representation of the complex behavior of the turbulent wind field, wake effects, and controller dynamics, these quantities prove sufficient to characterize DELs. The paper demonstrates the training of this load model within a simulation environment. Validation results using a different wind farm configuration indicate that the surrogate can accurately predict fatigue loads for both unwaked and waked turbines, encompassing scenarios of wake steering and induction control.

Validation of induction/steering reserve-boosting active power control by a wind tunnel experiment with dynamic wind direction changes

This paper presents an experimental validation of an active power control methodology that combines induction control and wake steering to maximize the power reserve of the wind turbines in a farm. The experiments are carried out on a cluster of three scaled wind turbines in a boundary-layer wind tunnel, by dynamically varying the wind direction, and by considering a time-varying power tracking signal that mimics secondary frequency control of the grid. The methodology is compared with three active power control algorithms sourced from the literature. Results indicate that the instantaneous power reserves are indeed improved by an appropriate handling of wake effects, achieving a more accurate tracking of the power signal.