Search Results (344)

This paper focuses on the issue of unmodeled dynamics and large-range parametric uncertainties in air-breathing hypersonic vehicles (AHV), proposing an adaptive dynamic surface control method based on radial basis function (RBF) neural networks. First, the hypersonic longitudinal model is transformed into a strict-feedback control system with model uncertainties. Then, based on backstepping control theory, adaptive dynamic surface controllers incorporating RBF neural networks are designed separately for the velocity and altitude channels. The proposed controller achieves three key functions: (1) preventing “differential explosion” through low-pass filter design; (2) approximating uncertain model components and unmodeled dynamics using RBF neural networks; (3) enabling real-time adjustment of controller parameters via adaptive methods to accomplish online estimation and compensation of system uncertainties. Finally, stability analysis proves that all closed-loop system signals are semi-globally uniformly bounded (SGUB), with tracking errors converging to an arbitrarily small residual set. The simulation results indicate that the proposed control method reduces steady-state error by approximately 20% compared to traditional controllers. Full article

A sliding mode predictive control (SMPC) scheme integrated with an extreme learning machine (ELM) disturbance observer is proposed for the trajectory tracking of a flexible air-breathing hypersonic vehicle (FAHV). To streamline the controller design, the longitudinal model is decoupled into a velocity subsystem and an altitude subsystem. For the velocity subsystem, a proportional-integral sliding mode surface is designed, and the control law is derived by minimizing a cost function that weights the predicted sliding mode surface and the control input. For the altitude subsystem, a backstepping control framework is adopted, with the SMPC strategy embedded in each step. Multi-source disturbances are modeled as composite additive disturbances, and an ELM-based neural network observer is constructed for their real-time estimation and compensation, thereby enhancing system robustness. The semi-globally uniformly ultimately bounded (SGUUB) stability of the closed-loop system is rigorously proven using Lyapunov stability theory. Simulation results demonstrate the comprehensive superiority of the proposed method: it achieves reductions in Root Mean Square Error (RMSE) of 99.60% and 99.22% for velocity and altitude tracking, respectively, compared to Prescribed Performance Control with Backstepping Control (PPCBSC), and reductions of 98.48% and 97.12% relative to Terminal Sliding Mode Control (TSMC). Under parameter uncertainties, the developed ELM observer outperforms RBF-based observer and Extended State Observer (ESO) by significantly reducing tracking errors. These findings validate the high precision and strong robustness of the proposed approach. Full article

A decentralized control problem for vehicular platoon systems with heterogeneous dynamic behaviors is investigated in this paper. To simplify the controller design, a longitudinal model is established as an interconnected form. On this basis, a series of decentralized state feedback controllers are designed to ensure the individual stability, string stability and connective stability of the vehicular platoon system. Then, a new scenario in which additional vehicles are added to the platoon is also considered by developing an expanding construction system (ECS) based on the proposed longitudinal model. As a result, a corresponding controller can be designed as a new one of the decentralized controllers without changing the original control laws of the interconnected system. The stability conditions are presented with rigorous analysis by virtue of linear matrix inequality (LMI) for the interconnected system and the ECS. Simulation results are carried out to demonstrate the effectiveness of the proposed decentralized tracking controllers. Full article

Recently, various forms and purposes of autonomous mobility have been widely developed and commercialized. To control the various iterations of shaped and purposeful mobility, control technology that can adapt to the dynamic characteristics of the mobility and environmental changes is essential. This study presents an adaptive proportional–integral–derivative (PID) controller for longitudinal velocity and yaw rate tracking in autonomous mobility, addressing the aforementioned issue. To design the adaptive PID controller, error dynamics have been designed using error and control input with two coefficients. It is designed that the two coefficients are estimated in real time by recursive least squares with multiple constraints and forgetting factors. The estimated coefficients are used to compute PI gains based on the Lyapunov direct method with constant derivative gain. Multiple constraints, such as value and rate limits, have been incorporated into the RLS algorithm to enhance the control stability. The performance evaluation is conducted through the co-simulation of MATLAB/Simulink and CarMaker under integrated control scenarios, such as longitudinal velocity and yaw rate tracking, for mobility. Full article

Background/Objectives: Cardiovascular diseases are the most important cause of mortality in chronic obstructive pulmonary disease (COPD). Speckle-tracking echocardiography (2D-STE) can be used for assessing atrial and ventricular function, and its role in COPD is underexplored. The main objective of this study was to investigate prognostic associations in patients with COPD using 2D-STE echocardiography and laboratory biomarkers. Methods: The study included 70 participants, divided into two groups: 55 patients diagnosed with COPD and 15 healthy controls. All four cardiac chambers were analyzed with standard ultrasound and 2D-STE techniques. We measured NT-proBNP and several oxidative stress biomarkers: reduced glutathione (GSH), the GSH/GSSG ratio, malondialdehyde (MDA), and Caspase-3. Results: An NT-proBNP level above 325 pg/mL independently predicts advanced COPD stages (GOLD grades 3 and 4), with statistically significant results at a 95% confidence interval (CI) (p = 0.001). Additionally, 2D-STE identified reduced right ventricular (RV) and left ventricular (LV) strain in COPD patients before changes in LV ejection fraction. RV and LV strain measurements (RV4CLS < −16.15%, RVFWSL < −18.6%, LV GLS < −19.45%) along with PASP > 37.5 mmHg are independent predictors of advanced COPD stages, demonstrating significance at a 95% CI (p = 0.001). A positive correlation was observed between NT-proBNP, ultrasound parameters assessing RV systolic function, LV longitudinal strain impairment, and PASP. Conclusions: NT-proBNP serves as an independent biomarker of pulmonary hypertension and secondary right heart overload and independently predicts advanced COPD stages (GOLD grades 3 and 4) alongside RV and LV strain measurements. Full article

This paper presents a dual-objective Model Predictive Control (MPC) framework for fixed-wing unmanned aerial vehicles (UAVs). The framework was designed with two goals in mind: improving longitudinal motion control and optimizing the flight trajectory when connectivity and no-fly zone constraints are present. A multi-input–multi-output model derived from NASA’s Generic Transport Model (T-2) was used and linearized for controller design. We compared the MPC controller with a Linear Quadratic Regulator (LQR) in MATLAB simulations. The results showed that MPC reached the reference values faster, with less overshoot and phase error, particularly under sinusoidal reference inputs. These differences became even more evident when the UAV had to fly in windy conditions. Trajectory optimization was carried out using the CasADi framework, which allowed us to evaluate paths that balance two competing requirements: reaching the target quickly and maintaining cellular connectivity. We observed that changing the weights of the cost function had a strong influence on the trade-off between direct flight and reliable communication, especially when multiple base stations and no-fly zones were included. Although the study was limited to simulations at constant altitude, the results suggest that MPC can serve as a practical tool for UAV missions that demand both accurate flight control and robust connectivity. Future work will extend the framework to more complete models and experimental validation. Full article

Cooperative longitudinal–lateral trajectory optimization is essential for unmanned ground vehicle (UGV) platoons to improve safety, capacity, and efficiency. However, existing approaches often face unstable formation under low penetration rates and rely on fragmented control strategies. This study develops a cooperative longitudinal–lateral trajectory tracking framework tailored for UGV platooning, embedded in a hierarchical control architecture. Dual-stage multi-objective Model Predictive Control (MPC) is proposed, decomposing trajectory planning into pursuit and platooning phases. Each stage employs adaptive weighting to balance platoon efficiency and traffic performance across varying operating conditions. Furthermore, a traffic-aware organizational module is designed to enable the dynamic opening of UGV-dedicated lanes, ensuring that platoon formation remains compatible with overall traffic flow. Simulation results demonstrate that the adaptive weighting strategy reduces the platoon formation time by 41.6% with only a 1.29% reduction in the average traffic speed. In addition, the dynamic lane management mechanism yields longer and more stable UGV platoons under different penetration levels, particularly in high-flow environments. The proposed cooperative framework provides a scalable solution for advancing UGV platoon control and demonstrates the potential of unmanned systems in future intelligent transportation applications. Full article

Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe post-infectious complication of SARS-CoV-2, often with cardiac involvement. Myocardial strain imaging may detect dysfunction missed by conventional echocardiography. The objectives of this study are to characterize cardiac manifestations of MIS-C and assess the value of strain imaging in children with preserved and reduced left ventricular ejection fraction (LV-EF). Methods: We retrospectively analyzed 22 MIS-C patients admitted between September 2020 and January 2024, all with cardiac involvement. Clinical, laboratory, and echocardiographic data—including 2D and speckle-tracking strain—were collected at the day of worst dysfunction (DWD) and discharge (DD) and compared with 22 matched controls. Results: Median age was 4.65 years; 59% male; 45% overweight/obese. LV systolic dysfunction (LV-EF < 50%) occurred in 54.5%, coronary abnormalities in 36.4%, and pericardial effusion in 95.5%. LV global longitudinal strain (LVGLS) was significantly lower than controls at the DWD (−15.45 ± 4.76%, p < 0.0001) and DD (−20.63 ± 4.66%, p = 0.014). Strain abnormalities persisted despite LV-EF recovery, and even patients with preserved LV-EF showed significant segmental strain reduction. LVGLS and apical infero-septal strain were strongest predictors of reduced LV-EF. Conclusions: MIS-C often causes systolic dysfunction and coronary changes, but strain imaging reveals persistent subclinical myocardial injury. Long-term cardiac monitoring is warranted. Full article

To improve the adaptability of 4WID electric vehicles under various operating conditions, this study introduces a model predictive control approach utilizing a neural network for adaptive weight parameter prediction, which integrates four-wheel steering and longitudinal driving force control. To address the difficulty in adjusting the MPC weight parameters, the neural network undergoes offline training, and the Snake Optimization method is used to iteratively optimize the controller parameters under diverse driving conditions. To further enhance vehicle stability, the real-time stability state of the vehicle is assessed using the $\beta -\dot{\beta }$ phase plane method. The influence of vehicle speed and road adhesion on the instability boundary of the phase plane is comprehensively considered to design a stability controller based on different instability degree zones. This includes an integral sliding mode controller that accounts for both vehicle tracking capability and stability, as well as a PID controller, which calculates the additional yaw moment based on the degree of instability. Finally, an optimal distribution control algorithm coordinates the longitudinal driving torque and direct yaw moment while also considering the vehicle’s understeering characteristics in determining the torque distribution for each wheel. The simulation results show that under various operating conditions, the proposed control strategy achieves smaller tracking errors and more concentrated phase trajectories compared to traditional controllers, thereby improving path tracking precision, vehicle stability, and adaptability to varying conditions. Full article

This study proposes a hierarchical drive control system to ensure speed stability in dual-motor tracked vehicles operating under complex terrain and heavy-load conditions. The system adopts a two-layer structure. At the upper level, the sliding mode controller is designed for both longitudinal speed regulation and yaw rate control, thereby stabilizing straight line motion and the steering maneuvers. At the lower level, a synchronization mechanism aligns the velocities of the two motors, enhancing the vehicle’s robustness against speed fluctuations. Simulation results demonstrate that, across both heavy load and light load bulldozing scenarios, the deviation between the controller output and the reference command remains within 5$\%$. These findings confirm the accuracy of the control implementation and validate the effectiveness of the proposed framework. Full article

Background: Anthracycline-based chemotherapy, while highly effective for breast cancer, poses a significant risk for chemotherapy-related cardiac dysfunction (CTRCD), mainly determined by left ventricular ejection fraction (LVEF) reduction. Objectives: We aimed to evaluate the diagnostic utility of speckle tracking analysis (STA) and Diastolic Stress Test Echocardiography (DSTE) for the early detection of cardiac dysfunction either CTRCD or heart failure with preserved ejection fraction (HFpEF) in women undergoing chemotherapy for breast cancer and developed exertional dyspnea and/or fatigue during follow-up. Methods: In this prospective case–control study, 133 women receiving anthracycline-based chemotherapy (with or without anti-HER2 therapy) (chemotherapy group-CTG) and 65 age-matched healthy women as the control group (CG) underwent resting echocardiographic assessment, including LVEF, global longitudinal strain (GLS), myocardial work indices, biomarkers assay (NT-proBNP, troponin, galectin-3) and DSTE at baseline. That assessment was repeated after 12 months in CTG. Results: In this prospective case—control study, 133 women receiving anthracycline-based chemotherapy (with or without anti-HER2 therapy) were included. Based on the presence of CTRCD, they were further subdivided into a CTRCD subgroup (n = 37) and a CTRCD-free subgroup (n = 88). At the end of this study, CTG showed worse values of LVEF, GLS, myocardial work indices than baseline and CG (p < 0.05). Subgroup comparison (CTRCD vs. CTRCD-free) showed significant impairment in LVEF (53.60% vs. 62.60%, p < 0.001), GLS (–16.68% vs. −20.31%, p < 0.001), DSTE-derived tricuspid regurgitation maximum velocity (TRVmax) (3.05 vs. 2.31 m/s, p < 0.001) and elevated biomarkers (NT-proBNP: 200.06 vs. 61.49 pg/mL; troponin: 12.42 vs. 3.95 ng/L, p < 0.001) in the former subgroup. Regression analysis identified GLS, NT-proBNP, troponin, and TRVmax as independent predictors of CTRCD. Notably, a subgroup of CTRCD-free patients (n = 16) showed a high probability for HFpEF based on the HFA-PEFF score, with elevated GLS, NT-proBNP and DSTE-derived TRVmax compared to the rest of CTRCD-free patients and the CG (p < 0.001). Conclusions: STA and DSTE significantly outperform conventional LVEF in detecting subclinical cardiac dysfunction among women with breast cancer receiving chemotherapy. The combination of novel echocardiographic techniques and biomarkers may enable the detection of early CTRCD, including the under-estimated presence of HFpEF among breast cancer women with HF symptoms. Full article

This paper addresses the path tracking problem of underactuated unmanned surface vessels (USVs) in the presence of unknown external disturbances. A fixed-time adaptive integral sliding mode control (AISMC) method, incorporating a nonlinear disturbance observer (NDO), is proposed. Initially, a three-degree-of-freedom dynamic model of the USV is developed, accounting for external disturbances and model uncertainties. Based on the vessel’s longitudinal and transverse dynamic position errors, a virtual control law is designed to ensure fixed-time convergence, thereby enhancing the position error convergence speed. Next, a fixed-time NDO is introduced to estimate real-time external perturbations, such as wind, waves, and currents. The observed disturbances are fed back into the control system for compensation, thereby improving the system’s disturbance rejection capability. Furthermore, a sliding mode surface is designed using a symbolic function to address the issue of sliding mode surface parameter selection, leading to the development of the adaptive integral sliding mode control strategy. Finally, compared with traditional SMC and PID, the proposed AISMC-NDO offers higher accuracy, faster convergence, and improved robustness in complex marine environments. Full article

Considering the importance of maritime cybersecurity, this study provides a solution based on a nonlinear finite-time extended state observer (NFTESO) for unmanned surface vessels (USVs) equipped with rotatable thrusters under false data injection attacks (FDIAs). First, to complete the control design for USVs in a network environment and ensure optimal tracking performance within limits, an event triggering mechanism with finite-time constraints and a concise control optimization framework are employed. Then, command filtered technology is applied to obtain the derivative of the virtual control quantity generated using a backstepping design, optimizing the information interaction process in the kinematic and dynamic loops. The design based on the NFTESO estimates the composite uncertain dynamics in the system, including FDIAs, reducing the adverse effects of cyber attacks on the system. Finally, simulation outcomes confirmed the efficacy of the proposed control strategy. The simulation results showed that, compared with two other control schemes, the control scheme designed in this paper improved lateral tracking accuracy by approximately $77.1\%$ and $94.7\%$, and longitudinal tracking accuracy by approximately $95\%$ and $98\%$, respectively. Communication frequency was reduced by approximately $98.82\%$ and $82.48\%$, respectively. Full article

In the current literature, few motion control studies have considered the disturbances caused by road profile, model uncertainty, and actuator delay in regard to low-speed autonomous vehicles. In addition, motion controller designs usually rely on motor/brake torque control, which is not always available. This study outlines an integrated disturbance estimation and non-singular terminal sliding mode controller (NS-TSMC) to overcome disturbances in low-speed scenarios through traction/brake pedal position control. First, a longitudinal dynamic model that considers a detailed brake-by-wire hydraulic braking system model and a motor actuator model is proposed. Road disturbances, model uncertainty, and actuator delays are also considered in vehicle modelling. This vehicle model was verified through experimental data from a low-speed autonomous sightseeing vehicle. Then, based on the proposed vehicle model, the disturbance and uncertain parameter estimator was designed and integrated with NS-TSMC to achieve longitudinal motion control through throttle/brake pedal control. Experimental results from the experimental sightseeing vehicle and simulation results demonstrated the improvement of the longitudinal motion tracking performance and motion comfort compared with a benchmark proportional–integral–derivative (PID) longitudinal motion controller. Full article

This paper addresses the spatial path tracking problem of the X-rudder autonomous underwater vehicle (AUV) under random sea current disturbances. An adaptive line-of-sight guidance-linear quadratic regulator (ALOS-LQR) control strategy with roll constraints is proposed to enhance the tracking control accuracy and stability of the X-rudder AUV in such environments. First, to mitigate the roll-instability-induced depth and heading coupling deviations caused by unknown environmental disturbances, a roll-constrained linear quadratic regulator (LQR) heading-pitch control strategy is designed. Second, to handle random disturbances and model uncertainties, a nonlinear extended state observer (ESO) is employed to estimate dynamic disturbances. At the kinematic level, an adaptive line-of-sight guidance method (ALOS) is utilized to transform the path tracking problem into a heading and pitch tracking problem, while compensating in real time for kinematic deviations caused by time-varying sea currents. Finally, the effectiveness of the proposed control scheme is validated through simulation experiments and lake trials. The results confirm the effectiveness of the proposed method. Specifically, the roll-constrained ESO-LQR reduces lateral and longitudinal errors by 77.73% and 80.61%, respectively, compared to the roll-constrained LQR. ALOS navigation reduced lateral and longitudinal errors by 85.89% and 94.87%, respectively, compared to LOS control, while exhibiting faster convergence than ILOS. In physical experiences, roll control reduced roll angle by 50.52% and depth error by 33.3%. Results demonstrate that the proposed control strategy significantly improves the control accuracy and interference resistance of the X-rudder AUV, exhibiting excellent accuracy and stability. Full article