Flight control of a hexa-rotor airship: Uncertainty quantification for a range of temperature and pressure conditions

The present paper is concerned with the dynamic modeling and design of control laws for a small non-rigid multi-rotor airship constituted of an oblate-spheroid helium balloon coupled with an electric-powered hexa-rotor airframe. The vehicle is assumed to operate in windless and low-speed conditions. A six-degree-of-freedom nonlinear dynamic model is derived for it using the Newton–Euler approach and considering, among other efforts, a restoring torque due to the displacement of the balloon’s center of buoyancy above the vehicle’s center of mass and the added-mass effect resulting from the air–structure interaction. Using the derived model and assuming a time-scale separation between the translational and rotational dynamics, the attitude and position control laws are designed separately from each other. Both laws are formulated using feedback linearization combined with control input saturation within appropriate parallelepipedal sets, which are carefully chosen to respect pre-defined bounds on the control torque, control force and maximum inclination angle. The effect of temperature and pressure fluctuations is taken into account through a parametric probabilistic approach, where Maximum Entropy Principle is used to construct a physically consistent stochastic model and Monte Carlo method is used as the stochastic solver to propagate the uncertainties through the system. Extensive simulation results show the effectiveness of the proposed control system and quantify the uncertainty of its performance over a wide range of local temperature and pressure.     

汽车电磁式主动悬架技术综述

电磁式主动悬架兼具控制精确、系统响应快和节能高效等优点,对悬架运动的控制能力强,可以显著提升车辆的舒适性和操稳性。随着新能源汽车、电控系统以及悬架减振技术的发展,电磁式作动器在汽车悬架系统上的应用开始受到关注。文中对汽车电磁式主动悬架技术的研究和应用现状进行回顾和分析,并对其应用前景进行展望。     

A case study of socio-cultural and technical factors in automobile design: Discourses between designers and potential users on a new electric vehicle in Africa

Technological artifacts emerge and develop within social contexts, inextricably interconnecting technology and society. This article addresses this interconnection empirically, analyzing the implementation of an electric vehicle designed and built by students of automotive engineering at the Technical University of Munich (TUM) in Germany. The students created this vehicle to address problems of mobility for rural populations in Africa, aiming to provide local residents with better access to necessities of life such as healthcare, education, and transportation. The article examines African perceptions of and responses to the vehicle, as well as specific suggestions for future improvement. It discusses not only African reactions to the vehicle and its potential social impact on African societies, but also the concepts and ideas of the designers behind this automotive construction. It also acknowledges the ways in which the engineers based their work on assumptions about African needs rather than on substantial ethnographic research, which diminished their ability to succeed.     

Experience-Based Cognition for Driving Behavioral Fingerprint Extraction

Abstract

With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and safer car controls. In this paper, we propose a novel approach to extract the driver’s driving behavioral fingerprints based on our conceptual framework Experience-Oriented Intelligent Things (EOIT). EOIT is a learning system that has the potential to enable Internet of Cognitive Things (IoCT) where knowledge can be extracted from experience, stored, evolved, shared, and reused aiming for cognition and thus intelligent functionality of things. By catching driving data, this approach helps cars to collect the driver’s pedal and steering operations and store them as experience; eventually, it uses obtained experience for the driver’s driving behavioral fingerprint extraction. The initial experimental implementation is presented in the paper to demonstrate our idea, and the test results show that it outperforms the Deep Learning approaches (i.e., deep fully connected neural networks and recurrent neural networks/Long Short-Term Memory networks).     

水下循迹航行器水动力学性能数值研究

为了研究低速水下循迹监测航行器的水动力学性能数值计算问题,采用FLUENT软件和SST剪切应力输运模型,通过雷诺时均N-S方程分析流速一定的情况下,取不同攻角、不同水平舵角作为来流条件,研究未安装推进器以及安装推进器且其安装位置不同时,航行器的升力系数、俯仰力矩系数、表面压力分布和流场速度的变化规律。结果表明:在未安装推进器以及推进器的安装位置不同时,随着攻角的变化,升力系数呈线性变化,俯仰力矩系数呈非线性变化;随着水平舵角的变化,升力系数和俯仰力矩系数呈线性变化。当推进器安装在航行器头部时,对航行器流场压力和流场速度变化影响最大;当安装在航行器尾部时,对二者影响最小。对于低速航行器,应尽量将推进器安装在中间靠后位置,以提高航行器的水动力性能。升力系数的试验结果与数值仿真结果之间最大相差7. 51%,阻力系数的试验结果与数值仿真结果最大相差5. 84%,均吻合较好。研究结果可以为低速水下循迹航行器的优化设计和发展提供理论参考。     

Two‐sided matching framework for optimal user association in 5G multi‐RAT UDNs

Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs.     

Automation fears: Drivers and solutions

New technologies offer employers the ability to replace tasks done by human labour with those done by machines. There are challenges for both employers and employees, as employers look for strategies for the implementation of automation technologies and employees may have concerns about their employment being threatened by automation technologies. In this research, we analyse data of over 500 Bulgarians to learn about how they perceive the automation of their jobs. The analysis finds that there are segments of the population defined by demographics and attitudes that are more fearful of the automation of their jobs than others. Additionally, we see that attitudes towards the dehumanizing effects of automation, peer-pressure, job automatability, and a person's self-perception of professionalism are the main drivers of the fear of automation. Finally, the paper evaluates respondents' attitudes towards various individual, corporate and social solutions to automation fears.     

两种多层穿梭车系统的性能比较分析

物流配送中心订单响应速度的加快,对订单拣选系统提出了更高的要求。多层穿梭车系统因其柔性强、效率高等特点,近年来得到了广泛应用。多层穿梭车系统具有两种形式--基于转载车和基于环形输送线,二者均可实现货物的快速拣选,但在系统吞吐量和订单完成周期方面存在差异,致使企业决策者难以进行系统选择。基于上述原因,本文比较两种多层穿梭车系统的性能差异。建立两个系统的开环排队网络模型,然后求解系统吞吐量、订单完成周期,通过仿真验证了排队论模型的准确性,通过试验对两种系统的性能进行对比分析。结果表明,系统吞吐量与层数、巷道数相关,层数越多,巷道数越少,转载车系统相对于环线系统优势越显著;订单完成周期与层数、订单到达率相关,层数越多,订单到达率越低,转载车系统相对于环线系统越具优势。     

考虑行走弹性影响下的车辆换挡过程分析

为研究行走弹性对工程车辆行走换挡过程的影响，建立了考虑驱动轮轮胎变形引起的车辆行走弹性影响的整车行走动力学模型，该模型适用于换挡过程分析。计算与分析了典型装载机动力换挡过程，将考虑或不考虑行走弹性时计算得到的整车加速度和瞬时冲击度的变化过程分别进行了对比，利用实车试验对单一换挡过程进行了验证；并将考虑行走弹性时升挡过程中变速箱输入输出转速变化过程、离合器滑摩功率特性的计算结果与不考虑行走弹性时换挡过程的计算结果进行了对比。研究结果表明：与不考虑行走弹性的情况相比，行走弹性变形使得换挡过程中整车加速度的变化更加平缓；换入挡离合器有两次滑摩过程，冲击度更小，换挡时间更长；离合器接合时的冲击度与其接入时间有关；滑摩功更小。     

Consumers’ willingness to pay for upcycled foods

Research on food waste reduction suggests that solutions aimed at reducing waste early in the consumption cycle are the most impactful. Based on this premise, food research labs and food manufacturers have started creating and selling foods made from food ingredients that are generally discarded. Such foods, termed upcycled foods, are safe for human consumption and provide a promising solution to reduce food waste. However, the commercial success of this new category of foods will depend on consumers’ acceptance. This research examines a key indicator of acceptance – consumers’ willingness to pay. We find that although consumers are willing to pay less for upcycled foods compared to conventional alternatives, messaging increases consumers’ willingness to pay. Specifically, we find that rational messaging is more effective than emotional messaging. Overall, our findings suggest that upcycled foods may command good acceptance among consumers.