Urban Traffic Eco-driving: A Macroscopic Steady-State Analysis

International audienceThe problem of traveling at maximum energy efficiency (Eco-Driving) is addressed for urban traffic networks at macroscopic level. The scope of this paper is the analysis of the steady-state behavior of the system, given certain boundary flows conditions fixed by traffic lights timings, and in presence of a traffic control policy based on variable speed limits. The formal study is carried out on a two-cells variable length model adapted to the urban setup from previous works on highway traffic. Informative traffic metrics, aimed at assessing traffic and vehicles performance in terms of traveling time, infrastructure utilization and energy consumption, are then defined and adapted to the new macroscopic traffic model. If congestion in a road section does not spill back or vanish, the system is stable and many different equilibrium points can be reached via variable speed limits. Efficient operation points and traffic conditions are identified as a trade-off between optimization of global traffic energy consumption, traveling time and infrastructure utilization

The INOVE ANR 2010 Blan 0308 project: Integrated approach for observation and control of vehicle dynamics

International audienceThis paper presents the INOVE "Integrated approach for observation and control of vehicle dynamics" project. The aim and organization of the project are described and we present some recent results on the proposed integrated approach to design new methodologies for the improvement of the vehicle dynamical behaviour

Vibration suppression in multi-body systems by means of disturbance filter design methods

This paper addresses the problem of interaction in mechanical multi-body systems and shows that subsystem interaction can be considerably minimized while increasing performance if an efficient disturbance model is used. In order to illustrate the advantage of the proposed intelligent disturbance filter, two linear model based techniques are considered: IMC and the model based predictive (MPC) approach. As an illustrative example, multivariable mass-spring-damper and quarter car systems are presented. An adaptation mechanism is introduced to account for linear parameter varying LPV conditions. In this paper we show that, even if the IMC control strategy was not designed for MIMO systems, if a proper filter is used, IMC can successfully deal with disturbance rejection in a multivariable system, and the results obtained are comparable with those obtained by a MIMO predictive control approach. The results suggest that both methods perform equally well, with similar numerical complexity and implementation effort

Two-Dimensional Positioning with Machine Learning in Virtual and Real Environments

In this paper, a ball-on-plate control system driven only by a neural network agent is presented. Apart from reinforcement learning, no other control solution or support was applied. The implemented device, driven by two servo motors, learned by itself through thousands of iterations how to keep the ball in the center of the resistive sensor. We compared the real-world performance of agents trained in both a real-world and in a virtual environment. We also examined the efficacy of a virtually pre-trained agent fine-tuned in the real environment. The obtained results were evaluated and compared to see which approach makes a good basis for the implementation of a control task implemented purely with a neural network

Adaptive control of a boost-buck converter for thermoelectric generators

Thermoelectric generators (TEGs) are used to recover waste heat of the exhaust gas and convert it into electric energy in automotive applications. The temperature of the waste heat influences the voltage and internal resistor of a TEG. For the electric linking of TEGs to the on-board power supply, a DC-DC converter may be used. The control of the DC-DC converter must be robust against dynamic changes and additionally has to track the maximum power point (MPP) of the TEG. This paper presents a digital cascade controller for a boost-buck converter to charge a vehicle battery and to supply the load. To track the MPP, a hill climbing (HC) algorithm is implemented, which is also used for photovoltaics. The conversion time of the HC is minimized with an adaptive step size. Width variations of electric parameters of TEG influence the dynamic and stability of the controllers. With a closed loop identification, the parameter variation is estimated, and the control parameters can be redesigned. An experimental result show the efficiency of the adaptive control.BMBF, 03X3553E, Thermoelektrische Generatoren 202

Engineering Emergence: A Survey on Control in the World of Complex Networks

Complex networks make an enticing research topic that has been increasingly attracting researchers from control systems and various other domains over the last two decades. The aim of this paper was to survey the interest in control related to complex networks research over time since 2000 and to identify recent trends that may generate new research directions. The survey was performed for Web of Science, Scopus, and IEEEXplore publications related to complex networks. Based on our findings, we raised several questions and highlighted ongoing interests in the control of complex networks.publishedVersio

Twelve-year mortality in HIV-infected patients receiving antiretroviral therapy (ART): the role of social vulnerability. The ANRS CO8 APROCO-COPILOTE cohort

International audienceBackground: Although the role of clinical/biological factors associated with mortality has already been explored in HIV-infected patients on antiretroviral therapy (ART), to date little attention has been given to the potential role of social vulnerability. This study aimed to construct an appropriate measure of social vulnerability and to evaluate whether this measure is predictive of increased mortality risk in ART-treated patients followed up in the ANRS CO8 APROCO-COPILOTE cohort.Methods: The cohort enrolled 1,281 patients initiating a protease inhibitor-based regimen in 1997–1999. Clinical/laboratory data were collected every 4 months. Self-administered questionnaires collected psycho-social/behavioural characteristics at enrolment (month [M] 0), M4 and every 8–12 months thereafter. A multiple correspondence analysis using education, employment and housing indicators helped construct a composite indicator measuring social vulnerability. The outcome studied was all-cause deaths occurring after M4. The relationship between social vulnerability and mortality, after adjustment for other predictors, was studied using a shared-frailty Cox model, taking into account informative study dropout.Results: Over a median (IQR) follow-up of 7.9 (3.0–11.2) years, 121 deaths occurred among 1,057 eligible patients, corresponding to a mortality rate (95% CI) of 1.64 (1.37, 1.96)/100 person-years. Leading causes of death were non-AIDS defining cancers (n=26), AIDS (n=23) and cardiovascular diseases (n=12). Social vulnerability (HR [95% CI] =1.2 [1.0, 1.5]) was associated with increased mortality risk, after adjustment for other known behavioural and bio-medical predictors.Conclusions: Social vulnerability remains a major mortality predictor in ART-treated patients. A real need exists for innovative interventions targeting individuals cumulating several sources of social vulnerability, to ensure that social inequalities do not continue to lead to higher mortality

A Comparative Study of Stochastic Model Predictive Controllers

[EN] A comparative study of two state-of-the-art stochastic model predictive controllers for linear systems with parametric and additive uncertainties is presented. On the one hand, Stochastic Model Predictive Control (SMPC) is based on analytical methods and solves an optimal control problem (OCP) similar to a classic Model Predictive Control (MPC) with constraints. SMPC defines probabilistic constraints on the states, which are transformed into equivalent deterministic ones. On the other hand, Scenario-based Model Predictive Control (SCMPC) solves an OCP for a specified number of random realizations of uncertainties, also called scenarios. In this paper, Classic MPC, SMPC and SCMPC are compared through two numerical examples. Thanks to several Monte-Carlo simulations, performances of classic MPC, SMPC and SCMPC are compared using several criteria, such as number of successful runs, number of times the constraints are violated, integral absolute error and computational cost. Moreover, a Stochastic Model Predictive Control Toolbox was developed by the authors, available on MATLAB Central, in which it is possible to simulate a SMPC or a SCMPC to control multivariable linear systems with additive disturbances. This software was used to carry out part of the simulations of the numerical examples in this article and it can be used for results reproduction.Gonzalez, E.; Sanchís Saez, J.; Garcia-Nieto, S.; Salcedo-Romero-De-Ávila, J. (2020). A Comparative Study of Stochastic Model Predictive Controllers. Electronics. 9(12):1-22. https://doi.org/10.3390/electronics9122078S12291

Continuous second order sliding mode based finite time tracking of a fully actuated biped robot

International audienceA second order sliding mode controller is modified to form a continuous homogeneous controller. Uniform finite time stability is proved by extending the homogeneity principle of discontinuous systems to the continuous case with uniformly decaying piece-wise continuous nonhomogeneous disturbances. The modified controller is then utilised to track reference trajectories for all the joints of a fully actuated biped robot where the joint torque is modeled as the control input. The modified controller ensures the attainment of a finite settling time between two successive impacts. The main contribution of the paper is to provide straightforward and realizable engineering guidelines for reference trajectory generation and for tuning a robust finite time controller in order to achieve stable gait of a biped in the presence of an external force disturbance. Such a disturbance has destabilising effects in both continuous and impact phases. Numerical simulations of a biped robot are shown to support the theoretical results

An Ethical Discussion About the Responsibility for Protection of Minors in the Digital Environment: A State-of-the-art review

Many ethical questions have been raised regarding the use of social media and the internet, mainly related to the protection of young people in the digital environment. In order to critically address the research question who is responsible for ethically protecting minors in the digital environment? , this paper will review the main literature available to understand the role of parents, the government, and companies in protecting young people within the digital environment. We employed a holistic process that covers a state-of-the-art review and desk research. The article is divided into four sessions; (1) Government Policies from the European Union (EU) Perspective; (2) Parental Control; (3) An Overview of Companies and the Private and Self-Regulation Sectors; and (4) the Ethical Dilemma. Throughout, we reviewed specific topics regarding the potentially harmful content for young people within the digital environment, questioned how ethical concerns shape content and interactions online and discussed how internet parenting styles impact risks and opportunities for young people in the digital world. Finally, we analysed the research question contrasting it with the main findings in this review and offered recommendations