Andrew Teel

About

Andrew Teel is a Distinguished Professor in the Department of Electrical and Computer Engineering at UC Santa Barbara. His research interests focus on the development of feedback control algorithms for nonlinear and hybrid dynamical systems. He is associated with the Control and Computation Research Lab and is involved in advancing control theory and its applications. For contact, he can be reached by phone at +1 805-893-3616 or via email at teel@ece.ucsb.edu. His office is located in Harold Frank Hall, Room 5119A.

Research topics

• Computer Science
• Artificial Intelligence
• Mathematics
• Engineering
• Machine Learning
• Control engineering
• Mathematical optimization
• Algorithm
• Pure mathematics
• Law

Selected publications

• Distributed robust Nash equilibrium seeking for aggregative games under persistent attacks: A hybrid systems approach

  Automatica · 2020 · 79 citations

  DOI

• Model-Based Dynamic Event-Triggered Control for Systems With Uncertainty: A Hybrid System Approach

  IEEE Transactions on Automatic Control · 2020 · 74 citations

  In this article, the event-triggered control problem for linear systems with uncertainties is addressed. A model-based dynamic event-triggered transmission strategy is proposed for linear systems, and for systems that can be decomposed into interconnected subsystems, a distributed model-based dynamic event-triggered transmission strategy is also proposed with transmission delays and transmission protocols in the networks. The whole systems are modeled into a hybrid system framework by introducin…

  DOI

• Robust Coordinated Hybrid Source Seeking With Obstacle Avoidance in Multivehicle Autonomous Systems

  IEEE Transactions on Automatic Control · 2021 · 45 citations

  In multivehicle autonomous systems that operate under unknown or adversarial environments, it is a challenging task to simultaneously achieve source seeking and obstacle avoidance. Indeed, even for single-vehicle systems, smooth time-invariant feedback controllers based on navigation or barrier functions have been shown to be highly susceptible to arbitrarily small jamming signals that can induce instability in the closed-loop system, or that are able to stabilize spurious equilibria in the oper…

  DOI

• $\mathcal {L}_2$-Gain Analysis of Periodic Event-Triggered Control and Self-Triggered Control Using Lifting

  IEEE Transactions on Automatic Control · 2020 · 22 citations

  We analyze the stability, and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -gain properties of a class of hybrid systems that exhibit time-varying linear flow dynamics, periodic time-triggered jumps, and arbitrary nonlinear jump maps. This class of hybrid systems encompasses periodic event-triggered control, self-triggered control, and netwo…

  DOI

• A Stochastic Hybrid Framework for Event-Triggered Nonlinear Control Systems With Stochastic Denial of Service Attacks

  IEEE Transactions on Automatic Control · 2023-05-03 · 11 citations

  article

  In this article, the stability problem for event-triggered nonlinear control systems is addressed in the presence of stochastic denial of service attacks on the communication network. Dynamic event-triggered control and periodic event-triggered control are considered under the stochastic attacks. The stochastic attacks are modeled by a stochastic hybrid timer and a logic variable which is used to identify whether the network is attacked or not. Then, the entire closed-loop system can be modeled…

  PublisherDOI

Recent grants

• NIH Grant R21AI057071

  NIH · $390k · 2006

• Uncertain Hybrid Systems

  NSF · $240k · 2006–2009

• Further advances in stability analysis for hybrid adversarial Markov decision processes

  NSF · $376k · 2012–2015

Frequent coauthors

• Dragan Nešić

  767 shared

• Warren E. Dixon

  University of Florida

  697 shared

• P Khargonekar

  Office of International Affairs

  688 shared

• Maria Prandini

  688 shared

• Marco Lovera

  Politecnico di Milano

  688 shared

• John Lygeros

  ETH Zurich

  688 shared

• Robert R. Bitmead

  University of California, San Diego

  688 shared

• James Farrell

  University of Arizona

  688 shared

Labs

• Andrew Teel's LabPI

  Not provided

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