Search Results (6)

Dysphagia is a serious complication of stroke, yet effective pharmacological treatments remain limited. This study investigated the effects of FAD012 (3,5-dimethyl-4-hydroxy cinnamic acid), a synthetic derivative of ferulic acid (FA), on cerebral damage and swallowing dysfunction in a rat model of bilateral common carotid artery occlusion (2VO). Sprague–Dawley rats were orally administered FAD012 (3 or 10 mg/kg), FA (10 mg/kg), or 0.5% carboxymethyl cellulose (CMC, suspension vehicle) starting one week before 2VO. Two weeks after 2VO surgery, which was performed under isoflurane anesthesia, reflex swallowing was assessed by electromyographic recordings of the mylohyoid muscle under urethane anesthesia. Two weeks after 2VO, cerebral blood flow (CBF) declined to approximately 40% of baseline, and the number of reflex swallowing responses was significantly reduced in the CMC group. Additionally, 2VO induced O₂⁻ production, apoptotic cell death in the striatum, and a reduction in tyrosine hydroxylase expression. Substance P (SP) levels in the laryngopharyngeal mucosa, positively regulated by dopaminergic signaling in the basal ganglia, also decreased. FAD012 (10 mg/kg) effectively prevented the 2VO-induced reduction in CBF, enhanced the reflex swallowing, and preserved the dopamine-SP system. Notably, FAD012 exerted significantly stronger effects than FA at the same dose. These findings suggest that FAD012 maintains CBF under cerebral hypoperfusion and enhances the swallowing reflex by maintaining neuronal function in the striatal and laryngopharyngeal regions of 2VO rats. Full article

Limiting the suspension stroke in vehicles holds critical and conceivable benefits. It is crucial for the safety, stability, ride comfort, and overall performance of the vehicle. Furthermore, it improves the reliability of suspension components and maintains consistent handling during regular and rough driving conditions. Hence, the design of a safety-critical controller to limit the suspension stroke for active suspension systems is of high importance. In this study, we employed a quarter-car model that incorporates a suspension spring with cubic nonlinearity. The proposed safety-critical controller is the control Lyapunov function–control barrier function–quadratic programming (CLF-CBF-QP). Initially, we designed the reference controller as a linear quadratic regulator (LQR) controller based on the linearized quarter-car model. The reference state-feedback LQR controller simplified the design of the control Lyapunov function. Consequently, from the nonlinear model, we construct a simple control Lyapunov function that relies only on the sprung mass velocity to have a relative degree of one. The CLF intends to improve the performance by considering the nonlinearity and via online optimization. We then formulate the control barrier function to restrict the suspension stroke from breaching its limits. To assess the effectiveness of the proposed controller, we present two challenging road inputs for the nonlinear quarter-car model when employing CLF-CBF-QP and LQR controllers. The CLF-CBF-QP findings surpassed the LQR controller in terms of safety and performance. This study highlights the immense potential of CLF-CBF-QP for suspension systems, improving the time-domain performance, limiting the suspension stroke, and guaranteeing safety. Full article

To enhance the dynamic performance of half-vehicle seat systems and reduce vibrations in both the vertical and pitching directions, a nonlinear energy sink inerter (NESI) can be introduced and aligned with lightweight design principles. A dynamic model of a half-vehicle seat system integrated with NESIs is constructed using Newton’s second law. The dynamic response of the system under pavement harmonic and random excitations is obtained using the pseudo-arc-length and harmonic balance methods and the numerical method, respectively. The dynamic behavior of the system is assessed using eight evaluation indexes. The optimal structural parameters of the NESIs are determined through the genetic algorithm. The results indicate that using NESIs attenuates resonance peaks and reduces root mean square (RMS) values for vehicle seat suspension strokes, front and rear suspension system strokes, and front and rear dynamic tire loads. However, the resonance peaks and RMS values for other performance indexes, which are vehicle seat vertical acceleration, the bodywork vertical, and pitching accelerations, exhibit an increase. When the structural parameters of the NESIs are optimized and contrasted with the original NESIs, the RMS values of the bodywork’s vertical and pitching acceleration, seat vertical acceleration, and seat suspension stroke will decrease by 23.97%, 27.48%, 23.59%, and 14.29%, respectively, and the other evaluation indexes will satisfy the limit conditions. Full article

In this study, we investigate a robust $H_{\infty }$ controller for a quarter-car model of an active inerter-based suspension system under parameter uncertainties and road disturbance. Its main objective is to improve the inherent compromises between ride quality, handling performance, suspension stroke, and energy consumption. Inerters have been extensively used to suppress unwanted vibrations from various kinds of mechanical structures. The advantage of inerter is that the realized ratio of equivalent mass (inertance relative to the mass of the primary structure) is greater than its actual mass ratio, resulting in higher performance for the same effective mass. First, the dynamics and state space of the active inerter-based suspension system were achieved for the quarter-car model with parameter uncertainties. In order to attain the defined objectives, and ensure that the closed-loop system achieves the prescribed disturbance attenuation level, the Lyapunov stability function, and linear matrix inequality (LMI) techniques have been utilized to satisfy the robust $H_{\infty }$ criterion. Furthermore, to limit the gain of the controller, some LMIs have been added. In the case of feasibility, sufficient LMI conditions by solving a convex optimization problem afford the stabilizing gain of the robust state-feedback controller. According to numerical simulations, the active inerter-based suspension system in the presence of parameter uncertainties and external disturbance performs much better than both a passive suspension with inerter and active suspension without inerter. Full article

The control algorithm could greatly help the suspension system improve the comprehensive performance of the vehicle. Existing control methods need to obtain the intermediate states, which are difficult to obtain directly or accurately when estimated by filters or observers. Thus, this paper proposed a new practical finite state LQR control method to deal with this problem. By combining with the output state of the finite sensor of the vehicle suspension system and weakening the unknown state as the goal, an optimization model is established with the design variables as the LQR weight coefficients. Then, the direct relationship between the current control input and the finite sensor output is obtained, and the finite state LQR control is realized. Taking the quarter-car suspension model as an example, the corresponding noise is added considering sensor accuracy, and the control performance of the four control methods is studied considering the uncertainties of suspension system parameters. In addition, the acceleration of sprung mass and the dynamic travel coefficient of suspension have been separately calculated by methods of finite state LQR control, LQR control, and PID control. The results show that there is not much difference between them under shock excitation or random excitation. However, the finite state LQR control method has the best comprehensive control performance in that its dynamic tire load coefficient is better than other methods; it could take into account the suspension work stroke coefficient, dynamic tire load coefficient, and sprung mass’ acceleration of the vehicle suspension system at the same time. In order to realize the optimal control effect with limited sensor arrangement, the finite state LQR control method only needs to obtain the current sensor output and the current control input, without estimating the unknown intermediate state. By this means, the proposed control method greatly simplifies the design of the control system and has great advantages on practical value. Full article

Suspension is an important part of intelligent and safe transportation; it is the balance point between the comfort and handling stability of a vehicle under intelligent traffic conditions. In this study, a control method of left-right symmetry of air suspension based on H∞ theory was proposed, which was verified under intelligent traffic conditions. First, the control stability caused by the active suspension control system running on uneven roads needs to be ensured. To address this issue, a 1/4 vehicle active suspension model was established, and the vertical acceleration of the vehicle body was applied as the main index of ride comfort. H∞ performance constraint output indicators of the controller contained the tire dynamic load, suspension dynamic stroke, and actuator control force limit. Based on the Lyapunov stability theory, an output feedback control law with H∞-guaranteed performance was proposed to constrain multiple targets. This way, the control problem was transformed into a solution to the Riccati equation. The simulation results showed that when dealing with general road disturbances, the proposed control strategy can reduce the vehicle body acceleration by about 20% and meet the requirements of an ultimate suspension dynamic deflection of 0.08 m and a dynamic tire load of 1500 N. Using this symmetrical control method can significantly improve the ride comfort and driving stability of a vehicle under intelligent traffic conditions. Full article