Decentralized optimal control of a vehicle platoon with guaranteed string stability

International audienceThis paper presents new decentralized optimal strategies for Cooperative Adaptive Cruise Control (CACC) of a car platoon under string-stability constraints. Two related scenarios are explored in the article: in the first one, a linear-quadratic regulator in the presence of measurable disturbances is synthesized, and the string-stability of the platoon is enforced over the controller's feedback and feedforward gains. In the second scenario, H2- and Hinf-performance criteria, respectively accounting for the desired group behavior and the string-stability of the platoon, are simultaneously achieved using the recently-proposed compensator blending method. An analytical study of the impact of actuation/communication delays and uncertain model parameters on the stability of the multi-vehicle system, is also conducted. The theory is illustrated via numerical simulations

Cascading Failures in the Global Financial System: A Dynamical Model

In this paper, we propose a dynamical model to capture cascading failures among interconnected organizations in the global financial system. Failures can take the form of bankruptcies, defaults, and other insolvencies. The network that underpins the financial interdependencies between different organizations constitutes the backbone of the financial system. A failure in one or more of these organizations can lead the propagation of the financial collapse onto other organizations in a domino effect. Paramount importance is therefore given to the mitigation of these failures. Motivated by the relevance of this problem and recent prominent events connected to it, we develop a framework that allows us to investigate under what conditions organizations remain healthy or are involved in the propagation of the failures in the network. The contribution of this paper is the following: i) we develop a dynamical model that describes the equity values of financial organizations and their evolution over time given an initial condition; ii) we characterize the equilibria for this model by proving the existence and uniqueness of these equilibria, and by providing an explicit expression for them; and iii) we provide a computational method via sign-space iteration to analyze the propagation of failures and the attractive equilibrium point

Switching nonlinear model predictive control of collaborative railway vehicles in catenary grids

This article contributes to the railway control field by proposing a novel approach capable of making trains collaborate, while also minimizing both traction energy and power line losses in catenary grids. The train dynamics are captured by a combination of four operating modes, so that the formulation of a switched control problem naturally applies. This model is interfaced with that of the catenary grid, consisting of the electrical substations and transmission lines over the track. Relying on these models, an eco-drive control system is proposed based on an original switching nonlinear model predictive control (SNMPC). Being collaborative-conceived, the new SNMPC is compared and evaluated against a noncollaborative version of the controller by means of simulation case studies relying on real-world test data, a validated train model, and measured track topology. We obtain that the proposed SNMPC outperforms the noncollaborative counterpart both in terms of traction energy and energy losses on the train rheostats and over the electrical lines. Thus, we demonstrate that the proposed SNMPC for collaborative eco-drive, based on the energy exchange between trains, has a potential positive impact on railway systems in catenary grids

The Role of Asymptomatic Individuals in the COVID-19 Pandemic via Complex Networks

Recent seroprevalence studies have tried to estimate the real number of asymptomatic cases affected by COVID-19. It is of paramount importance to understand the impact of these infections in order to prevent a second wave. This study aims to model the interactions in the population by means of a complex network and to shed some light on the effectiveness of localised control measures in Italy in relation to the school opening in mid-September. The formulation of an epidemiological predictive model is given: the advantage of using this model lies in that it discriminates between asymptomatic and symptomatic cases of COVID-19 as the interactions with these two categories of infected individuals are captured separately, allowing for a study on the impact of asymptomatic cases. This model is then extended to a structured nonhomogeneous version by means of the Watts-Strogatz complex network, which is adopted widely to model societal interactions as it holds the small world property. Finally, a case study on the situation in Italy is given: first the homogeneous model is used to compare the official data with the data of the recent seroprevalence study from Istat; second, in view of the return to school in mid-September, a study at regional level is conducted. The results of this study highlight the importance of coordinating the deployment of appropriate control measures that take into account the role of asymptomatic infections, especially in younger individuals, and inter-regional connectivity in Italy.Comment: 38 pages, journa

State dependent switching control of affine linear systems with dwell time: application to power converters

This paper addresses a state dependent switching law for the stabilization of continuous-time, switched affine linear systems satisfying dwell time constraints. Such a law is based on the solution of Lyapunov-Metzler inequalities from which stability conditions are derived. The key point of this law is that the switching rule calculation depends on the evolution forward by the dwell time of quadratic Lyapunov functions assigned to each subsystem. As such, the proposed law is readily applicable to power converters showing that it is an interesting alternative to other switching control techniques

On the preservation of co-positive Lyapunov functions under Padé discretization for positive systems

In this paper the discretization of switched and non-switched linear positive systems using Padé approximations is considered. We show: 1) first order diagonal Padé approximation preserves both linear and quadratic co-positive Lyapunov functions, higher order transformations need an additional condition on the sampling time1; 2) positivity need not be preserved even for arbitrarily small sampling time for certain Padé approximations. Sufficient conditions on the Padé approximations are given to preserve positivity of the discrete-time system. Finally, some examples are given to illustrate the efficacy of our results

Decentralized optimal control of a vehicle platoon with guaranteed string stability

International audienceThis paper presents new decentralized optimal strategies for Cooperative Adaptive Cruise Control (CACC) of a car platoon under string-stability constraints. Two related scenarios are explored in the article: in the first one, a linear-quadratic regulator in the presence of measurable disturbances is synthesized, and the string-stability of the platoon is enforced over the controller's feedback and feedforward gains. In the second scenario, H2- and Hinf-performance criteria, respectively accounting for the desired group behavior and the string-stability of the platoon, are simultaneously achieved using the recently-proposed compensator blending method. An analytical study of the impact of actuation/communication delays and uncertain model parameters on the stability of the multi-vehicle system, is also conducted. The theory is illustrated via numerical simulations

Model predictive control of battery-powered trains for catenary-free operation

Rail transportation is recently making a comeback with stunning results from technological viewpoint. While the efficiency of trains is well known, many aspects related to energy management still need to be tackled, including sustainability and optimization issues. These issues are central to the control community, and in this context model predictive control (MPC) is a powerful control approach for its capability of guaranteeing constraints satisfaction, while minimizing a predefined cost function. In this article, we exploit these advantages to provide more efficient control of the electric equipment inside railway vehicles. More precisely, the proposed MPC approach is capable of addressing the challenging scenario of partially catenary-free tracks for trains. These are equipped with batteries, which have to supply traction motors and parallel-connected auxiliary loads in an efficient manner, while reducing the amount of losses over the electric lines. Simulation results, based on real data provided by the industrial partner Alstom rail transport, show the effectiveness of the proposal