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We study the use of the System Optimum (SO) Dynamic Traffic Assignment (DTA) problem to design optimal traffic flow controls for freeway networks as modeled by the Cell Transmission Model, using variable speed limit, ramp metering, and routing. We consider two optimal control problems: the DTA problem, where turning ratios are part of the control inputs, and the Freeway Network Control (FNC), wher
Distributed averaging is one of the simplest and most widely studied network dynamics. Its applications range from cooperative inference in sensor networks, to robot formation, to opinion dynamics. A number of fundamental results and examples scattered through the literature are gathered here and some original approaches and generalizations are presented, emphasizing the deep interplay between the
We study System Optimum Dynamic Traffic Assignment (SO-DTA) for realistic traffic dynamics controlled by variable speed limits, ramp metering, and routing controls. We consider continuous-time cell-based Dynamic Network Loading models that include as special cases the Cell Transmission Model (CTM) with FIFO rule at the diverge junctions as well as non-FIFO diverge rules. While a straightforward co
Many notions of network centrality can be formulated in terms of invariant probability vectors of suitably defined stochastic matrices encoding the network structure. Analogously, invariant probability vectors of stochastic matrices allow one to characterize the asymptotic behavior of many linear network dynamics, e.g., arising in opinion dynamics in social networks as well as in distributed avera
Several strategic interactions over social networks display both negative and positive externalities at the same time. E.g., participation to a social media website with limited resources is more appealing the more of your friends participate, while a large total number of participants may slow down the website (because of congestion effects) thus making it less appealing. Similarly, while there a
Many linear dynamics over networks can be related by duality to the evolution of a Markov chain with state space coinciding with the node set of the network. Examples include opinion dynamics over social networks as well as distributed averaging algorithms for estimation or control. When the transition probability matrix P associated to the Markov chain is irreducible, a key quantity is its invari
This paper designs distributed dynamic traffic signal control policies for urban traffic networks. Vehicles at the end of an approach to an intersection queue up in separate lanes corresponding to different possible turn maneuvers at the upcoming intersection, according to fixed turn ratios. The departure rate of vehicles from the queue is governed by traffic signal control at the intersections. W
We propose a dynamical model for cascading failures in single-commodity network flows. In the proposed model, the network state consists of flows and activation status of the links. Network dynamics is determined by a, possibly state-dependent and adversarial, disturbance process that reduces flow capacity on the links, and routing policies at the nodes that have access to the network state, but a
Operation and maintenance (O&M) is highly important to fight unplanned downtime, which is a costly consequence of the increasing automation enabled by digitalization. We will discuss O&M to enable seamless exchange of information in a hierarchical multi-vendor system, while ensuring individual vendors controlling what know-how to share.
Providing information security is crucial for the Internet of Things (IoT) devices, platforms in which the available power budget is very limited. This paper tackles this challenge and presents a cryptographic processor compliant with the security algorithms specified by the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) NarrowBand IoT (NB-IoT) standard. The proposed processor
High-energy linear particle accelerators enable exploration of the microscopic structure of pharmaceuticals, solar cells, fuel cells, high-temperature superconductors, and the universe itself. These accelerators accelerate charged particles using oscillating magnetic fields that are confined in metal cavities. The amplitudes and phases of the electromagnetic fields need to be accurately controlled
The proliferation of connected embedded devices, or the Internet of Things (IoT), together with recent advances in machine intelligence, will change the profile of future cloud services and introduce a variety of new research problems centered around empowering resource-limited edge devices to exhibit intelligent behavior, both in sensing and control. Cloud services will enable learning from data,
A method to decompose a motion-planning problem into several segments is presented. It is based on a modification of the original problem, such that certain variables at the splitting points are considered to be precomputed and thus fixed and the remaining variables are obtained by performing Lagrange relaxation. The resulting dual problem is split into several subproblems, allowing parallel compu
A simplified combined-slip model that only considers the extreme case at the friction limit is suggested and used in a closed-loop controller for autonomous vehicle handling in at-the-limit maneuvers. In the development of the controller it is assumed that the front wheels are individually steered, but it is demonstrated in a left-hand turn scenario that with a simple adaptation, the method is sti
This paper presents a real-time hand gesture recognition system by accelerating a convolutional neural network (CNN) using FPGA platform. More specifically, ZynqNet is adopted and modified to fulfill the classification task of recognizing the Swedish manual alphabet, which is used by sign language users for spelling purposes, also known as fingerspelling. Data augmentation and transfer learning te
This paper presents a continuous-time ΔΣ ADC in a 28nm-FDSOI CMOS technology. The ADC is clocked at 5GHz with a signal bandwidth of 250 MHz, for an oversampling ratio (OSR) of only 10. The conversion from high-level model to circuit-level implementation requires multiple high-speed design methodologies and a careful layout. A 4th order loop filter is adopted to enhance quantization noise shaping i
In this paper, we study event-based PID control from an optimal stochastic control perspective. The purpose is to better understand what implementation features are critical for achieving good event-based PID performance. For this end, we formulate an LQG control design problem for a double integrator process with an integral disturbance, where the solution is an ideal PID controller. We then cons
Signals are physical variables or quantities measured at various parts of a system, which when processed yield the desired information. A wide variety of signals are often encountered in describing many practical systems. Electrical signal, in form of current and voltage, is the most easily measured quantity, hence the need to use sensors and transducers to transform other non-electrical quantity
The ac frequency in electrical power systems is conventionally regulated by synchronous machines. The gradual replacement of these machines by asynchronous renewable-based generation, which provides little or no frequency control, increases system uncertainty and the risk of instability. This imposes hard limits on the proportion of renewables that can be integrated into the system. In this paper,
