Online parameter identification based predictive pressure control for train electro-pneumatic braking systems with thermal effect.

The electro-pneumatic braking system with ON/OFF solenoid valves has been widely used in trains due to its advantages and superiority. The undesirable impact of the thermal effect on the electro-pneumatic braking system leads to frequent valve switching, degradation of the pressure tracking performance and sometimes instability. This article presents an adaptive model predictive control approach to solve the pressure control problem under temperature uncertainty based on a switched unscented Kalman filter.

Implication of self-organizing map, stable isotopes combined with MixSIAR model for accurate nitrogen control in a well-protected reservoir.

Nitrogen pollution and eutrophication in reservoirs is a global environmental geochemical concern. Occasional algal blooms still exist in reservoirs that have undergone pollution treatment. The lack of quantitative evidence of nitrogen sources and fate limits long-term stable ecological safety management.

Enhancing Force Control of Prosthetic Controller for Hand Prosthesis by Mimicking Biological Properties.

Prosthetic hands are frequently rejected due to frustrations in daily uses. By adopting principles of human neuromuscular control, it could potentially achieve human-like compliance in hand functions, thereby improving functionality in prosthetic hand. Previous studies have confirmed the feasibility of real-time emulation of neuromuscular reflex for prosthetic control.

Review of the Flight Control Method of a Bird-like Flapping-Wing Air Vehicle.

The Bird-like Flapping-wing Air Vehicle (BFAV) is a robotic innovation that emulates the flight patterns of birds. In comparison to fixed-wing and rotary-wing air vehicles, the BFAV offers superior attributes such as stealth, enhanced maneuverability, strong adaptability, and low noise, which render the BFAV a promising prospect for numerous applications. Consequently, it represents a crucial direction of research in the field of air vehicles for the foreseeable future.

Evaporation dominates the loss of plateau lake in Southwest China using water isotope balance assessment.

The water balance budget in remote plateau lakes provides a fundamental information on the local climate-hydrological pattern. However, integrated investigation on the waters entering the lake, especially groundwater, was limited. To assess the current climate stress on Yunnan-Guizhou Plateau lakes, we collected rivers, groundwater, lake, and precipitation with varying isotopic compositions in the Chenghai Lake basin over four separate campaigns during a hydrological year.

Abnormal Road Surface Recognition Based on Smartphone Acceleration Sensor.

In order to identify the abnormal road surface condition efficiently and at low cost, a road surface condition recognition method is proposed based on the vibration acceleration generated by a smartphone when the vehicle passes through the abnormal road surface. The improved Gaussian background model is used to extract the features of the abnormal pavement, and the k-nearest neighbor (kNN) algorithm is used to distinguish the abnormal pavement types, including pothole and bump. Comparing with the existing works, the influence of vehicles with different suspension characteristics on the detection threshold is studied in this paper, and an adaptive adjustment mechanism based on vehicle speed is proposed.

Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment.

Most existing signal timing plans are optimized given vehicles' arrival time (i.e., the time for the upcoming vehicles to arrive at the stop line) as exogenous input.

Conditional Artificial Potential Field-Based Autonomous Vehicle Safety Control with Interference of Lane Changing in Mixed Traffic Scenario.

Car-following is an essential trajectory control strategy for the autonomous vehicle, which not only improves traffic efficiency, but also reduces fuel consumption and emissions. However, the prediction of lane change intentions in adjacent lanes is problematic, and will significantly affect the car-following control of the autonomous vehicle, especially when the vehicle changing lanes is only a connected unintelligent vehicle without expensive and accurate sensors. Autonomous vehicles suffer from adjacent vehicles' abrupt lane changes, which may reduce ride comfort and increase energy consumption, and even lead to a collision.

Connected Vehicle as a Mobile Sensor for Real Time Queue Length at Signalized Intersections.

With the development of intelligent transportation system (ITS) and vehicle to X (V2X), the connected vehicle is capable of sensing a great deal of useful traffic information, such as queue length at intersections. Aiming to solve the problem of existing models' complexity and information redundancy, this paper proposes a queue length sensing model based on V2X technology, which consists of two sub-models based on shockwave sensing and back propagation (BP) neural network sensing. First, the model obtains state information of the connected vehicles and analyzes the formation process of the queue, and then it calculates the velocity of the shockwave to predict the queue length of the subsequent unconnected vehicles.

Analyzing the uncertainty of simulation results in accident reconstruction with Response Surface Methodology.

This paper is focused on the uncertainty of simulation results in accident reconstruction. The Upper and Lower Bound Method (ULM) and the Finite Difference Method (FDM), which can be easily applied in this field, are introduced firstly; the Response Surface Methodology (RSM) is then introduced into this field as an alternative methodology. In RSM, a sample set is firstly generated via uniform design; secondly, experiments are conducted according to the sample set with the help of simulation methods; thirdly, a response surface model is determined through regression analysis; finally, the uncertainty of simulation results can be analyzed using a combination of the response surface model and existing uncertainty analysis methods.