Vehicle Control Research Articles

Adaptive quadrotor control using online dynamic mode decomposition

Precision control of Unmanned Aerial Vehicles (UAVs) is essential for deployment in a wide range of applications. However, real-world flight conditions often deviate from ideal operating scenarios, presenting uncertainties such as external disturbances and unmodeled dynamics. These can dramatically impact tracking accuracy and stability. This study proposes a novel adaptive control technique for quadrotors based on Windowed Dynamic Mode Decomposition (DMDc) techniques. This techniques efficiently identifies dynamic models directly from data, and updates this model in real-time, allowing the controller to compensate for changing conditions. To facilitate realistic validation, the proposed system is integrated within a Hardware-in-the-Loop (HiL) framework. In a series of simulated experiments, the adaptive controller demonstrates improvement in trajectory tracking under disturbances when compared to a conventional inverse dynamics approach. This research underscores the promise of DMDc-based techniques combined with adaptive control to enhance UAV operation, enabling safer and more robust performance in demanding scenarios.

Distributed deadband event-triggered observer-based containment control for unmanned surface vehicles with channel fading

This article investigates the distributed deadband event-triggered containment control problem for multiple underactuated surface vehicles (USV) systems whose communication networks are subject to channel fading. The first distributed deadband event-triggered observer (DDETO) was proposed to observe the target positions of the followers in the convex hulls formed by the leaders. It also manages the internal communication between the followers in the presence of channel fading. In addition, the deadband event-triggered mechanism (DETM) in DDETO guarantees a strictly positive minimum inter-event times (MIET), which can be accurately calculated and adjusted according to the design parameters. Afterward, an adaptive controller is designed by backstepping based on the desired position information observed by DDETO. It is worth noting that the containment control scheme proposed in this paper is based on relative position measurement only, which reduces the amount of information transfer compared to transmitting position and velocity information when wireless signals are fading in the channel, improves the control accuracy, and also reduces the system’s requirements for sensors. Theoretical analysis leads to the conclusion that the error signals are uniformly ultimately bounded (UUB). Finally, the effectiveness of the control scheme is verified by numerical simulation.

Modulation of regenerative responses by retinoic and ascorbic acids in human apical papilla cells

ObjectiveThis study investigated the bioactive effects of retinoic acid and ascorbic acid on hSCAPs in vitro. DesignCells were obtained from human third molars (n=4) and characterized for mesenchymal stem cell markers by flow cytometry. The experimental groups: control (α-MEM); vehicle control group (α-MEM + 0.17 % DMSO); retinoic acid 0.1, 1, and 10 µM; and ascorbic acid 3, 30, and 300 µM (n=8) were tested for cell viability (alamarBlue; 1, 3, and 7 days), total collagen synthesis (Sirius Red; 1 and 7 days), mineralized matrix formation (Alizarin red; 14 days), and the regulation of gene expression related to mineralization (ALPL and DSPP), cell migration (ITGAV and CXCL12) angiogenesis (VEGFA) and collagen synthesis (COL1A1 and COL3A1; RT-qPCR) on 1 and 7 days. ACTB and GAPDH were used as reference genes. Data were analyzed by ANOVA and complementary tests at a 5 % significance level. ResultsAscorbic acid 300 µM increased viability, and retinoic acid reduced it dose-dependently. Retinoic acid 0.1 µM and ascorbic acid 30 and 300 µM increased mineralized matrix formation and total collagen synthesis, and retinoic acid 10 µM decreased. On day 1, 0.1 µM retinoic acid upregulated the gene expression of COL1A1, COL3A1, VEGFA, CXCL12, ALPL, DSPP e ITGAV, and 300 µM ascorbic acid upregulated COL1A1, COL3A1 and DSPP. However, on day 7, retinoic acid downregulated ALPL, COL3A1, CXCL12, and VEGFA and downregulated ITGAV and VEGFA. ConclusionRetinoic acid 0.1 µM and ascorbic acid 300 µM biostimulated hSCAPs to differentiate into pro-regenerative phenotypes with potential application for REPs.

A lie group PMP approach for optimal stabilization and tracking control of autonomous underwater vehicles

AbstractIn this research, we explore a finite horizon optimal stabilization and tracking control scheme for the dynamical model of a 6‐DOF Autonomous Underwater Vehicle (AUV). Dynamical equations of the AUV are represented in a Lie group () framework, encompassing both translational and rotational motions. Utilizing a left Lie group action on , we define error function for velocities via a right transport map to effectively address optimal trajectory tracking. The optimal control objective is formulated as a trade‐off problem, aiming to minimize both errors and control effort simultaneously. Left action on yields the left trivialized Hamiltonian function from which the concomitant state and costate dynamical equations are derived using Pontryagin's Minimum Principle (PMP). Consequently, the resulting two‐point boundary value problem is solved to obtain optimal trajectories. We demonstrate the optimality of the resulting solution obtained from the derived control law. For ensuring boundedness in the presence of small disturbances, this study incorporates the effects of internal parametric uncertainties associated with added mass and inertia components, along with the influence of external disturbances induced by ocean currents. Through simulation validations, we confirm the alignment of our results with the theoretical developments, demonstrating that the proposed control law effectively mitigates both parametric uncertainties and ocean current disturbances.

5-Hydroxytryptamine 1F Receptor Agonist Lasmiditan Differentially Regulates Successful Repair and Failed Repair Genes in a Mouse Model of Acute Kidney Injury.

Increasing evidence substantiates the role of mitochondrial dysfunction, inflammation, fibrosis, and cell senescence in the onset and progression of acute kidney injury (AKI) to chronic kidney disease . The underlying governing cellular and transcriptional events, however, are not fully understood. Recently, the key factors that regulate successful and failed repair states in the proximal tubule have been identified at a single-cell resolution following bilateral ischemia-reperfusion (I/R) in a mouse model of AKI. Previously, our group showed that treatment with the FDA-approved selective 5-hydroxytryptamine receptor 1F agonist lasmiditan following AKI induces mitochondrial biogenesis , restores renal mitochondrial function, and increases renal and vascular recovery in vivo. Here, we assessed the effect of lasmiditan on transcriptional and translational changes that are responsible for successful repair, injury, and failed repair states in the renal cortex following I/R-induced AKI. Increased levels of successful repair genes such as acyl-coA synthase medium-chain family member 2a, low-density lipoprotein receptor-related protein 2, solute carrier family 5 member 12, and hepatocyte nuclear factor 4 alpha were observed with 6 and 12 days of lasmiditan treatment following AKI compared to vehicle control. While 6 days of lasmiditan treatment had no effect on failed repair genes, the administration of lasmiditan for 12 days decreased the levels of vascular cell adhesion protein 1, tumor necrosis factor α, and interleukin-1β, which drive maladaptive repair. These data reveal that lasmiditan treatment post-AKI differentially regulates successful and failed repair gene expression in the renal cortex, likely contributing to the restoration of renal function and providing a potential targeted therapeutic pathway for the treatment of AKI.

A novel, centrally acting mammalian aminosterol, ENT-03, induces weight loss in obese and lean rodents.

ENT-03, a spermine bile acid we recently discovered in the brain of newborn mice acts centrally to regulate energy and metabolism. Obese, diabetic (ob/ob) mice treated with five doses of ENT-03 over 2 weeks, demonstrated a rapid decrease in blood glucose levels into the range seen in non-obese animals, prior to any significant weight loss. Weight fell substantially thereafter as food intake decreased, and serum biochemical parameters normalized compared with both vehicle and pair-fed controls. To determine whether ENT-03 could be acting centrally, we injected a single dose of ENT-03 intracerebroventricularly to Sprague-Dawley rats. Weight fell significantly and remained below vehicle injected controls for an extended period. By autoradiography, ENT-03 localized to the arcuate nucleus of the hypothalamus, the choroid plexus and cerebrospinal fluid. Significant cFosactivation occurred in multiple anatomical regions within the hypothalamus and brainstem involved in appetite suppression, food-entrained circadian rhythmicity, autonomic function, and growth. These data support a role for ENT-03 in the treatment of type 2 diabetes and obesity. Phase 1 studies in subjects with obesity and diabetes are currently in progress.

Research on The Influence of Continous Damping Control Shock Absorber on Frequency Response Function of Spindle Coupled Road Simulation Test Bench

When the semi-active suspension is tested based on the 6-DOF spindle coupled road simulation test bench, the traditional test method is no longer applicable, because the continous damping control shock absorber of the original vehicle controller cannot be used and the overall nonlinear of the system is stronger. At present, there are few related engineering applications in the industry. This paper introduces the current reproduction technology of semi-active suspension on the 6-DOF spindle coupled road simulation bench and researches the difference of the system frequency response function by excitation of continous damping control shock absorber with different control current.

An Automatic Vehicle Navigation System Based on Filters Integrating Inertial Navigation and Global Positioning Systems

The key technologies for advanced autonomous vehicles include those relating to perception, decision making, and execution. Path-tracking control in autonomous vehicles is heavily dependent on their positioning system. Therefore, the development of low-cost and reliable positioning systems is crucial to improving perception and decision-making technologies for autonomous vehicles. Although the accuracy of the global positioning system (GPS) is extremely high, it is vulnerable to interference. Further, despite the low positioning accuracy of inertial navigation systems (INSs), their robustness is notably high. Therefore, an integrated navigation information method based on the Adaptive Particle Filter and the Iterative Kalman Filter (APF-IKF) was developed in this study. Firstly, an integrated navigation system model was established. Then, the IKF was adopted to estimate the speed, latitude and longitude errors of the INS. Thirdly, the newest estimated error results were introduced into the APF to optimize the distribution function, and the particle quality was improved. In this process, the APF can filter non-Gaussian noise, preliminarily estimate the error, optimize the result with the IKF and correct the output information of the INS with the final estimated error. Finally, by using differential GPS positioning as the benchmark, we built a real-vehicle test platform with a low-cost and low-precision GPS and inertial units and carried out a series of real-vehicle tests. The experimental results show that compared with the traditional KF method, APF-IKF can significantly improve the positioning accuracy and robustness of the system.

Autophagy unrelated transcriptional mechanisms of hydroxychloroquine resistance revealed by integrated multi-omics of evolved cancer cells

ABSTRACT Hydroxychloroquine (HCQ) and chloroquine are repurposed drugs known to disrupt autophagy, a molecular recycling pathway essential for tumor cell survival, chemotherapeutic resistance, and stemness. We pursued a multi-omic strategy in OVCAR3 ovarian cancer and CCL218 colorectal cancer cells. Two genome-scale screens were performed. In the forward genetic screen, cell populations were passaged for 15 drug pulse-chases with HCQ or vehicle control. Evolved cells were collected and processed for bulk RNA-seq, exome-seq, and single-cell RNA-seq (scRNA-seq). In the reverse genetic screen, a pooled CRISPR-Cas9 library was used in cells over three pulse-chases of HCQ or vehicle control treatments. HCQ evolved cells displayed remarkably few mutational differences, but substantial transcriptional differences. Transcriptomes revealed multiple pathways associated with resistance to HCQ, including upregulation of glycolysis, exocytosis, and chromosome condensation/segregation, or downregulation of translation and apoptosis. The Cas9 screen identified only one autophagy gene. Chromosome condensation and segregation were confirmed to be disrupted by HCQ in live cells and organelle-free in vitro extracts. Transcriptional plasticity was the primary mechanism by which cells evolved resistance to HCQ. Neither autophagy nor the lysosome were substantive hits. Our analysis may serve as a model for how to better position repurposed drugs in oncology.

Design of a Path-Following Controller for Autonomous Vehicles Using an Optimized Deep Deterministic Policy Gradient Method

The need for a safe and reliable transportation system has made the advancement of autonomous vehicles (Avs) increasingly significant. To achieve Level 5 autonomy, as defined by the Society of Automotive Engineers, AVs must be capable of navigating complex and unconventional traffic environments. Path-following is a crucial task in autonomous driving, requiring precise and safe navigation along a defined path. Traditional path-tracking methods often rely on parameter tuning or rule-based approaches, which may not be suitable for dynamic and complex environments. Reinforcement learning has emerged as a powerful technique for developing effective control strategies through agent-environment interactions. This study investigates the efficiency of an optimized Deep Deterministic Policy Gradient (DDPG) method for controlling acceleration and steering in the path-following of autonomous vehicles. The algorithm demonstrates rapid convergence, enabling stable and efficient path tracking. Additionally, the trained agent achieves smooth control without extreme actions. The performance of the optimized DDPG is compared with the standard DDPG algorithm, with results confirming the improved efficiency of the optimized approach. This advancement could significantly contribute to the development of autonomous driving technology.

Linear Parameter Varying and Reinforcement Learning Approaches for Trajectory Tracking Controller of Autonomous Vehicles

This research focuses on controlling the motion trajectory of autonomous vehicles by using a combination of two high-performance control methods: Linear Parameter Varying (LPV) and Reinforcement Learning (RL). First, a single-track motion model is researched and developed with coordinate systems to determine the car's motion trajectory through signals from GPS. Then, the LPV control method is used to design a controller to control the car's motion trajectory. Reinforcement learning method with detailed training procedures is used to combine with the advantages of LPV controller. Finally, the simulation results are evaluated in the time domain through the use of specialized CarSim software, which clearly demonstrates the superiority of the research method.

Recovery control of autonomous underwater vehicles based on modified delay-product-type functional

This paper focuses on the recovery process of autonomous underwater vehicles, emphasizing a hierarchical framework in which autonomous underwater vehicles are categorized into a mothership and sub-vessels. In the recovery phase, following the completion of an underwater mission, sub-vessels navigate towards a location designated by the mothership. The crux of the recovery hinges on the design of the controller for adapting communication delays induced by environmental in underwater communication transmissions. The mothership and sub-vessels constitute a collaborative multi-autonomous underwater vehicles network equipped with these controllers, making them operate through the synchronized adjustment of their states represented in error terms. A delay-dependent controller condition criterion is proposed based on the modified delay-product-type Lyapunov-Krasovskii functional. The controller with the gain obtained from the criterion manages the system effectively and ensures successful recovery. The effectiveness of the proposed approach is demonstrated through a case study involving a network comprising one leading and four following autonomous underwater vehicles.

Integrated Chassis Control for Multi-Axle Vehicles: A Comprehensive Review

Multi-axle vehicles (MAVs) are used to transport heavy loads, navigate challenging terrain, and perform specific tasks. However, designing vehicle control systems for such vehicles is challenging. MAVs, such as trucks, buses, military vehicles, and multi-purpose vehicles, require sophisticated control techniques to increase the stability and ride comfort of such vehicles. This paper provides a comprehensive review of standalone control systems and integrated control systems (ICSs) for the steering, driving/braking, and suspension systems of MAVs, with a particular focus on the optimal tyre force distribution (TFD) in ICSs for MAVs. It also discusses various objective functions and optimisation methods used for the TFD. The findings indicate that optimising TFD significantly improves the stability of MAVs. As such, future studies may consider examining optimising three-axis TFD for MAVs to further improve vehicle stability.

Modeling impacts of different data transmission delays on traffic jam, fuel consumption and emissions on curved road

Under the intelligent transportation system, the use of autonomous vehicles can ease traffic jam, and reduce fuel consumption and emissions. The effects of different data transmission delays on traffic jam, fuel consumption and emissions on curved road are studied by constructing an extended multi-vehicle curve following model considering different data transmission delays to describe the curve following behavior of multiple autonomous vehicles. Subsequently, the stability of the novel model is derived by using linear stability theory. And then, numerical simulation is executed. Finally, some influence factors including curvature radius, backward looking effect, position signal time delay, and velocity signal time delay are discussed. Numerical simulation results show that reducing curvature radius and increasing backward looking effect can reduce fuel consumption and emissions, decrease density fluctuations, thereby gradually eliminating traffic jam. In addition, as difference between position signal time delay and velocity signal time delay decreases, the improvement degree in fuel consumption and emissions is limited. Meanwhile, it also makes density fluctuation decreases gradually, enhances traffic stream stability, and alleviates traffic jam, which is keeping with theoretical analysis. The finding has theoretical implications for designing autonomous vehicle control algorithms to reduce the negative effects of data transmission delays in traffic flow.

Extensive immunophenotypic sub-population analysis of StemRegenin1 expanded haematopoietic stem/progenitor cells

BackgroundEx vivo haematopoietic stem/progenitor cell (HSPCs) expansion constitutes an important area of research, and has the potential to improve access to umbilical cord blood (UCB) as a source of stem cells for haematopoietic stem cell transplantation (HSCT). The ability to improve stem cell dose and thereby reduce delayed engraftment times, which has plagued the use of UCB as a stem cell source since inception, is a recognised advantage. The extent to which cluster of differentiation (CD)34 sub-populations are affected by expansion with StemRegenin1 (SR1), and whether a particular subtype may account for better engraftment than others, is currently unknown. The purpose of this study was to determine the impact of SR1-induced HSPC expansion on CD34+ immunophenotypic subsets and gene expression profiles.MethodsUCB-derived CD34+ HSPCs were characterised before (D0) and after expansion (D7) with SR1 using an extensive immunophenotypic panel. In addition, gene expression was assessed and differentially expressed genes were categorised into biological processes.ResultsA dose-dependent increase in the number of CD34+ HSPCs was observed with SR1 treatment, and unbiased and extensive HSPC immunophenotyping proved to be a powerful tool in identifying unique sub-populations within the HSPC repertoire. In this regard, we found that SR1 promotes the emergence of HSPC subsets which may aid engraftment post expansion. In addition, we observed that SR1 has a minimal effect on the transcriptome of 7-day expanded CD34+ HSPCs when compared to cells expanded without SR1, with only two genes being downregulated in the former.ConclusionThis study revealed that SR1 selects for potentially novel immunophenotypic HSPC subsets post expansion and has a minimal effect on the transcriptome of 7-day expanded HSPCs when compared to vehicle controls. Whether these distinct immunophenotypic sub-populations possess greater engraftment capacity remains to be tested in animal models.

Coordinated Control of Differential Drive-Assist Steering and Direct Yaw Moment Control for Distributed-Drive Electric Vehicles

Direct yaw moment control (DYC) and differential drive-assist steering (DDAS) for distributed-drive vehicles are both realized by allocating the in-wheel motor torque. To address the interference caused by overlapping control objectives, this paper proposes a multilayer control strategy that integrates DYC and DDAS, consisting of an upper controller, a coordinated decision layer, and a torque distribution layer. The upper controller, designed based on the vehicle’s dynamic characteristics, incorporates an adaptive fuzzy control DYC system and a dual PID control DDAS system. The coordinated decision layer is developed utilizing a phase-plane dynamic weighting method, delineating region boundaries by applying the double-line and limit cycle methods. The torque distribution strategy is formulated considering motor peak torque and road adhesion conditions. Multi-condition joint simulation experiments indicate that the proposed multilayer control strategy, integrating the advantages of DYC and DDAS, reduces peak steering wheel torque by approximately 10%, peak yaw rate by around 25%, peak sideslip angle by roughly 29%, and peak sideslip angle rate by about 19%, significantly improving driving stability and maneuvering flexibility.

Chrysin mitigates neuronal apoptosis and impaired hippocampal neurogenesis in male rats subjected to D-galactose-induced brain aging

Oxidative stress-induced neuronal apoptosis is primarily involved in brain aging and impaired hippocampal neurogenesis. Long-term D-galactose administration increases oxidative stress related to brain aging. Chrysin, a subtype of flavonoids, exhibits neuroprotective effects, particularly its antioxidant properties. To elucidate the neuroprotection of chrysin on neuronal apoptosis and an impaired hippocampal neurogenesis relevant to oxidative damage in D-galactose-induced brain aging, male Sprague Dawley rats were allocated into vehicle control, D-galactose, chrysin, and cotreated rats. The rats received their respective treatments daily for 8 weeks. The reactions of scavenging enzymes, protein regulating endogenous antioxidant defense, and anti-apoptotic protein expression were significantly reduced in the hippocampus and prefrontal cortex of the animals receiving D-galactose. Conversely, product of oxidative damage and apoptotic protein expressions were significantly elevated in both cortical areas of the D-galactose group. In hippocampal neurogenesis, significant upregulation of cell cycle arrest and decrease in differentiated protein expression were detected after D-galactose administration. Nevertheless, chrysin supplementation significantly mitigated all negative effects in animals receiving D-galactose. This study demonstrates that chrysin likely attenuates brain aging induced by D-galactose by enhancing scavenging enzyme activities and reducing oxidative stress, neuronal apoptosis, and the impaired hippocampal neurogenesis.

Design and Application of Driving Resistance Test Device for Aircraft Tire and Soil Pavement

In view of the lack of soil bins for studying the surface interaction between aircraft wheels and soil, this study designed an indoor test bench for aircraft wheels and soil, including a soil container, loading vehicle, and intelligent measurement and control system, to test key parameters such as tire speed and wheel frictional resistance. The test system is capable of achieving speed regulation ranging from 0 to 30 km/h. The vertical load adjustment range with an adjustment interval of 10 kg spans from 90 to 140 kg. The soil type, compaction degree, and other conditions can be modified as per requirements to vary multiple test conditions, thereby enabling us to explore their influence on the driving resistance of the wheels. Moreover, the test data can be collected and processed in real time. A performance test of a wheel–soil table was carried out. The results show that the wheel–soil table test system is stable and reliable and can determine the relationship between the tire and soil, and the structural design of the test system meets the use requirements. In addition, it achieves the target test speed, data acquisition frequency, and stability. In terms of functionality and operational difficulty, the data acquisition of the entire test process is automated, and the test system achieves better informationization than previous methods. The overall operation of the wheel–soil platform is stable and powerful; thus, the model test platform design goal is achieved, and the testing requirements are met.

Patuletin Ameliorates Inflammation and Letrozole-Induced Polycystic Ovarian Syndrome in Rats.

Concerns about inflammation-related issues affecting female reproductive health are growing. Chronic low-grade inflammation in women with polycystic ovarian syndrome (PCOS) affects follicular growth, ovulation, and androgen production. The present investigation aimed to elucidate the efficacy of flavonoid patuletin in ameliorating the letrozole-induced PCOS and associated inflammation in rats. Female Wistar rats (32 days old) were divided into five groups (n = 12): Group I, control; Group II, vehicle control; Group III, letrozole oral (1 mg/kg) for 28 days; Group IV and Group V treatment groups, patuletin i.p. (25 mg/kg) and clomiphene citrate + metformin i.p. (50 mg/kg + 300 mg/kg), respectively. Leterozole-induced PCOS and ovarian inflammation were ameliorated by patuletin, as reflected in the improved histopathology, prevention of cyst formation, significant upregulation of growth factors such as growth differentiation factor 9 (GDF-9) and bone morphogenetic protein-15 (BMP-15) expression, and a decrease in the pro-inflammatory cytokines TNF-α, IL-6, and COX-2. Additionally, the plasma levels of reproductive hormones were restored. Upregulation of FSH-R, PR, and CYP19a1, along with downregulation of ERα, LHR, CYP17a1, CYP11a1 and HSDβ17a1, showed the regulation of gonadotropin receptors and steroid biosynthesis genes in ovarian tissues. Patuletin demonstrated a promising protective approach against the biological model of PCOS by increasing the inflammation in ovarian tissues with consequent regulation of growth factors, enzymes, and hormones, and might be used as adjuvant therapy in the treatment of problems related to female reproductive health.

Nonlinear scenario‐based model predictive control for quadrotors with bidirectional thrust

AbstractThe control of quadrotor vehicles under state and parameter uncertainty is a well studied problem that is vitally important to the deployment of these systems under real world conditions. In this article, we propose a linearization‐based extension to nonlinear systems of the existing scenario model predictive control (MPC) framework, which quantifies the impact of uncertainty on the vehicle dynamics through repeated sampling of the uncertainty space. Given the computational costs of such an approach, we also propose two simplifications of the scenario MPC algorithm that are significantly more tractable. In order to evaluate the performance of the algorithms, the specific problem of the control of a bidirectionally actuated quadrotor vehicle is considered. Simulations are carried out for each scenario MPC scheme as well as for a reference deterministic MPC scheme. When a sufficiently large sample count is considered, each of the scenario MPC algorithms achieves safer performance than the deterministic formulation without sacrificing any optimality. Additionally, the approximate solution techniques conclusively outperform the original nonlinear scenario MPC formulation for the same computational cost.