P
Paulo Tabuada
Researcher at University of California, Los Angeles
Publications - 300
Citations - 25801
Paulo Tabuada is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Control system & Control theory. The author has an hindex of 60, co-authored 288 publications receiving 20444 citations. Previous affiliations of Paulo Tabuada include University of California, Berkeley & Instituto Superior Técnico.
Papers
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Journal ArticleDOI
Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks
TL;DR: This note investigates a simple event-triggered scheduler based on the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant and shows how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements.
Proceedings ArticleDOI
An introduction to event-triggered and self-triggered control
TL;DR: An introduction to event- and self-triggered control systems where sensing and actuation is performed when needed and how these control strategies can be implemented using existing wireless communication technology is shown.
Journal ArticleDOI
Secure Estimation and Control for Cyber-Physical Systems Under Adversarial Attacks
TL;DR: A new simple characterization of the maximum number of attacks that can be detected and corrected as a function of the pair (A,C) of the system is given and it is shown that it is impossible to accurately reconstruct the state of a system if more than half the sensors are attacked.
Journal ArticleDOI
Periodic event-triggered control for nonlinear systems
TL;DR: The PETC strategies developed in this paper apply to both static state-feedback and dynamical output-based controllers, as well as to both centralized and decentralized (periodic) event-triggering conditions.
Journal ArticleDOI
Control Barrier Function Based Quadratic Programs for Safety Critical Systems
TL;DR: This paper develops a methodology that allows safety conditions—expression as control barrier functions—to be unified with performance objectives—expressed as control Lyapunov functions—in the context of real-time optimization-based controllers.