## About

561

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January 2002 - present

January 2002 - present

September 1999 - December 2001

## Publications

Publications (561)

We address the problem of finding a local solution to a nonconvex-nonconcave minmax optimization using Newton type methods, including interior-point ones. We modify the Hessian matrix of these methods such that, at each step, the modified Newton update direction can be seen as the solution to a quadratic program that locally approximates the minmax...

This paper proposes a state-dependent switching control for a class of switched nonlinear systems, whose model describes a permanent magnet synchronous machine (PMSM) fed by a three-phase voltage source inverter. Due to its high torque density, high efficiency and wide velocity range, this electrical drive is widely used for traction and several ap...

We describe the toolbox $$\mathtt {Tenscalc}$$ Tenscalc that generates specialized C-code to solve nonlinear constrained optimizations and to compute Nash equilibria. $$\mathtt {Tenscalc}$$ Tenscalc is aimed at scenarios where one needs to solve very fast a large number of optimizations that are structurally similar. This is common in applications...

This work makes explicit the degrees of freedom involved in modeling the dynamics of a network, or some other first-order property of a network, such as a measurement function. Currently, the concept of an admissible function is defined through a very high-level description, with the shortcoming of being difficult to verify or design such a functio...

We address the model identification and the computation of optimal vaccination policies for the coronavirus disease 2019 (COVID-19). We consider a stochastic Susceptible–Infected–Removed (SIR) model that captures the effect of multiple vaccine treatments, each requiring a different number of doses and providing different levels of protection agains...

We tackle the problem of having multiple transmitters cooperating to be desynchronized using a distributed algorithm. Although this problem can also be found in surveillance, it has the most impact in achieving a fair access to a wireless shared communication medium at the Medium Access Control (MAC) layer in the context of Wireless Sensor Networks...

We introduce a performance-guaranteed limbic system-inspired control (LISIC) strategy for nonlinear multi-agent systems (MASs) with uncertain high-order dynamics and external perturbations, where each agent in the MAS incorporates a LISIC structure to support the consensus controller. This novel approach, which we call double integrator LISIC (DILI...

An adaptive learning approach is proposed for solving two-player Stackelberg games with incomplete information. Specifically, the follower’s cost is unknown to the leader, who knows only that the follower’s response to its own action belongs to some parametric family of functions, but not the actual parameter value. The proposed approach is capable...

This chapter addresses the problem of making decisions based on sensor measurements that may have been manipulated by an adversary. For concreteness, we focus our attention on making binary decisions that, in the context of cybersecurity, could correspond to denying access to a sensitive resource, flagging a computer as compromised, deauthorizing a...

This paper presents a framework based on matrices of monoids for the study of coupled cell networks. We formally prove within the proposed framework, that the set of results about invariant synchrony patterns for unweighted networks also holds for the weighted case. Moreover, the approach described allows us to reason about any multiedge and multie...

This paper presents a framework based on matrices of monoids for the study of coupled cell networks. We formally prove within the proposed framework, that the set of results about invariant synchrony patterns for unweighted networks also holds for the weighted case. Moreover, the approach described allows us to reason about any multiedge and multie...

This paper studies topological entropy of switched nonlinear systems. We construct a general upper bound for the topological entropy in terms of an average of the asymptotic suprema of the measures of Jacobian matrices of individual modes, weighted by the corresponding active rates. A general lower bound is also established in terms of an active-ra...

We address the prediction of the number of new cases and deaths for the coronavirus disease 2019 (COVID-19) over a future horizon from historical data (forecasting). We use a model-based approach based on a stochastic Susceptible-Infections-Removed (SIR) model with time-varying parameters, which capture the evolution of the disease dynamics in resp...

This article addresses theoretical and practical challenges associated with a commercially available and ready-to-fly small-scale unmanned aircraft system (UAS) developed by Parrot SA: the Mambo quad rotorcraft. The dynamic model and the structure of the controller running onboard the UAS autopilot are not disclosed by its manufacturers. For this r...

This paper studies a notion of topological entropy for switched systems, formulated in terms of the minimal number of trajectories needed to approximate all trajectories with a finite precision. For general switched linear systems, we prove that the topological entropy is independent of the set of initial states. We construct an upper bound for the...

The state estimation of continuous-time nonlinear systems in which a subset of sensor outputs can be maliciously controlled through injecting a potentially unbounded additive signal is considered in this paper. Analogous to our earlier work for continuous-time linear systems in \cite{chong2015observability}, we term the convergence of the estimates...

This article investigates a political party or an association social network where members share a common set of beliefs. In modeling it as a distributed iterative algorithm with network dynamics mimicking the interactions between people, the problem of interest becomes that of determining: 1) the conditions when convergence happens in finite time...

Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low computational cost. In this paper, the objective is to establish performance-guaranteed emotional learning-inspired control (ELIC) strate...

Watch video: https://www.youtube.com/watch?v=Njlyf1SfgP0
Imperfect weather forecasts complicate robot planning. A conservative motion planning algorithm is developed to address uncertainty in autonomous boat missions. Dynamic Programming generates an optimal action for every location and game theory strategically handles uncertainty. Experimental...

In recent years diverse computational models of emotional learning observed in the mammalian brain have inspired a number of self-learning control approaches. These architectures are promising in terms of their learning ability and low computational cost. However, the lack of rigorous stability analysis and mathematical proofs of stability and perf...

In Wireless Sensor Networks (WSNs), equally spaced timing for Medium Access Control (MAC) is fundamental to guarantee throughput maximization from all nodes. This motivated the so called desynchronization problem and its solution based on the fast Nesterov method. In this paper, we tackle the problem of constructing centralized and distributed vers...

Submodular maximization problems are a relevant model set for many real-world applications. Since these problems are generally NP-Hard, many methods have been developed to approximate the optimal solution in polynomial time. One such approach uses an agent-based greedy algorithm, where the goal is for each agent to choose an action from its action...

Imperfect weather forecasts complicate robot planning. A conservative motion planning algorithm is developed to address uncertainty in autonomous boat missions. Dynamic Programming generates an optimal action for every location and game theory strategically handles uncertainty. Experimental results using Massachusetts Bay forecasts show the robot i...

We present a method for optimal coordination of multiple vehicle teams when multiple endpoint configurations are equally desirable, such as seen in the autonomous assembly of formation flight. The individual vehicles' positions in the formation are not assigned a priori and a key challenge is to find the optimal configuration assignment along with...

We consider a two-player zero-sum network routing game in which a router wants to maximize the amount of legitimate traffic that flows from a given source node to a destination node and an attacker wants to block as much legitimate traffic as possible by flooding the network with malicious traffic. We address scenarios with asymmetric information,...

Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low computational cost. In this paper, the objective is to establish performance–guaranteed emotional learning–inspired control (ELIC) strate...

Resorting to Reachability Sets, it is possible to compute polytopes defining all possible values of the state. Through a projection on the correct dimensions, it is possible to identify which inputs cause the most change to the state/output.

We consider a supervisory control problem for discrete-event systems, in which an attacker corrupts the symbols that are observed by the supervisor. We show that existence of a supervisor enforcing a specification language, in the presence of attacks, is completely characterized by controllability (in the usual sense) and observability of the speci...

We study a two-player Stackelberg game in which the follower’s strategy depends on a parameter vector that is unknown to the leader. An adaptive learning algorithm is designed to simultaneously estimate the unknown parameter and minimize the leader’s cost, based on adaptive control techniques and hysteresis switching. The algorithm guarantees that...

We study a scenario where a group of agents, each with multiple heterogeneous sensors are collecting measurements of a vehicle and the measurements are transmitted over a communication channel to a centralized node for processing. The communication channel presents an information-transfer bottleneck as the sensors collect measurements at a much hig...

We develop a Finite Horizon Maximum Likelihood Estimator (FHMLE) that fuses Inertial Measurement Unit (IMU) and radio frequency (RF) measurements over a sliding window of finite length for three‐dimensional navigation. Available RF data includes pseudo–ranges, angles of transmission (AoT), and Doppler shift measurements. The navigation estimates ar...

We propose a distributed output-feedback model predictive control approach for achieving consensus among multiple agents. Each agent computes a distributed control action based on an output-feedback measurement of a local neighborhood tracking error and communicates information only to its neighbors, according to a communication network modeled as...

We consider the output feedback event‐triggered control of an off‐grid voltage source inverter (VSI) with unknown inductance‐capacitance (L − C) filter dynamics and connected load in the presence of an input disturbance acting at the inverter. Due to uncertain dynamics and unmodeled parameters in the L − C filter connected to the VSI, we use an ada...

This paper studies topological entropy and stability properties of switched linear systems. First, we show that the exponential growth rates of solutions of a switched linear system are essentially upper bounded by its topological entropy. Second, we estimate the topological entropy of a switched linear system by decomposing it into a part that is...

This paper studies a notion of topological entropy for switched systems, formulated in terms of the minimal number of trajectories needed to approximate all trajectories with a finite precision. For general switched linear systems, we prove that the topological entropy is independent of the set of initial states, and construct an upper bound in ter...

The maximization of submodular functions is an NP-Hard problem for certain subclasses of functions, for which a simple greedy algorithm has been shown to guarantee a solution whose quality is within 1/2 of the optimal. When this algorithm is implemented in a distributed way, agents sequentially make decisions based on the decisions of all previous...

By, in effect, rendering pharmacokinetics an experimentally adjustable parameter, the ability to perform feedback-controlled dosing informed by high-frequency in-vivo drug measurements would prove a powerful tool for both pharmacological research and clinical practice. Efforts to this end, however, have historically been thwarted by an inability to...

We study a notion of topological entropy for switched systems, formulated in terms of the minimal number of initial states needed to approximate all initial states within a finite precision. This paper focuses on the topological entropy of switched linear systems with pairwise commuting matrices. First, we prove there exists a simultaneous change o...

In this paper, a novel method for the design of a robust estimator for a class of switched linear systems subject to unknown inputs is presented. To consider a more general case compared to the literature, the switching sequence is assumed to be minimum average-dwell time but not available for measurement. To deal with this issue, the proposed esti...

The maximization of submodular functions an NP-Hard problem for certain subclasses of functions, for which a simple greedy algorithm has been shown to guarantee a solution whose quality is within 1/2 of that of the optimal. When this algorithm is implemented in a distributed way, agents sequentially make decisions based on the decisions of all prev...

In this presentation, we develop the application of set-based fault detection and isolation to the case of Cyber-physical systems.

By reformulating the PageRank problem from finding an eigenvector to solving a linear equation, it is possible to speed up its computation.

The problem of fault detection and isolation in cyber-physical systems is growing in importance following the trend to have an ubiquitous presence of sensors and actuators with network capabilities in power networks and other areas. In this context, attacks to power systems or other vital components providing basic needs might either present a seri...

This paper studies the Coremelt attack, a link-flooding Distributed Denial of Service attack that exhausts the bandwidth at a core network link using low-intensity traffic flows between subverted machines. A dynamical system model is formulated for analyzing the effect of Coremelt attack on a single-link Transmission Control Protocol (TCP) network...

We address the problem of a set of agents reaching consensus by computing the average of their initial states. We propose two randomized algorithms over a directed communication graph where either a random node broadcast its value or a randomly selected pair of nodes communicate in a distributed fashion. The proposed algorithms guarantee convergenc...

We solve a linear quadratic optimal control problem for sampled-data systems with stochastic delays. The delays are stochastically determined by the last few delays. The proposed optimal controller can be efficiently computed by iteratively solving a Riccati difference equation, provided that a discrete-time Markov jump system equivalent to the sam...

The tight coupling of information technology with physical
sensing and actuation in Cyber-Physical Systems (CPS) has
given rise to new security vulnerabilities and attacks with
potentially life-threatening consequences. These sensor attacks, primarily executed by compromising the sensors or
the communication links, are designed to transmit the phys...

This work proposes a game-theory-based technique for guaranteeing consensus in unreliable networks by satisfying local objectives. This multi-agent problem is addressed under a distributed framework, in which every agent has to find the best controller against a worst-case adversary so that agreement is reached among the agents in the networked tea...

Phasor measurement units (PMUs) are playing an increasingly important role in wide-area monitoring and the control of power systems. PMUs allow synchronous real-time measurements of voltage, phase angle, and frequency from multiple remote locations in the grid, enabled by their ability to align to global positioning system (GPS) clocks. Given that...

There is growing evidence regarding the importance of spike timing in neural information processing, with even a small number of spikes carrying information, but computational models lag significantly behind those for rate coding. Experimental evidence on neuronal behavior is consistent with the dynamical and state dependent behavior provided by re...

In this paper, we consider a problem motivated by search-and-rescue applications, where an unmanned aerial vehicle (UAV) seeks to approach the vicinity of a distant quasi-stationary radio frequency (RF) emitter surrounded by local scatterers. The UAV employs only measurements of the Doppler frequency of the received RF signal, along with its own be...

Time awareness is critical to a broad range of emerging applications -- in Cyber-Physical Systems and Internet of Things -- running on commodity platforms and operating systems. Traditionally, time is synchronized across devices through a best-effort background service whose performance is neither observable nor controllable, thus consuming system...