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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
Control Barrier Function-Based Quadratic Programs Introduce Undesirable Asymptotically Stable Equilibria
TL;DR: In this article, an extension to the QP-based controller unifies control Lyapunov functions and control barrier functions such that the resulting system trajectories avoid the undesirable equilibria problem on the boundary of the safe set.
Journal ArticleDOI
Securing state reconstruction under sensor and actuator attacks: Theory and design
TL;DR: The notion of sparse strong observability is introduced and it is shown that is a necessary and sufficient condition for correctly reconstructing the state despite the considered attacks and an observer is proposed to harness the complexity of this intrinsically combinatorial problem by leveraging satisfiability modulo theory solving.
Proceedings ArticleDOI
First steps toward formal controller synthesis for bipedal robots
Aaron D. Ames,Paulo Tabuada,Bastian Schürmann,Wen-Loong Ma,Shishir Kolathaya,Matthias Rungger,Jessy W. Grizzle +6 more
TL;DR: A two step approach to formally synthesize control software for bipedal robots so as to enforce specifications by design and thereby generate physically realizable stable walking to mitigate the curse of dimensionality that hampers the applicability of formal synthesis techniques to complex CPS.
Posted Content
Symmetries and isomorphisms for privacy in control over the cloud
TL;DR: This article proposes several transformation-based methods for enforcing data privacy and addresses three different scenarios: the cloud has no knowledge about the system being controlled, the cloud knows what sensors and actuators the system employs but not the system dynamics, and theCloud knows the system Dynamics, its sensors, and actuator.
Journal ArticleDOI
A theory of robust omega-regular software synthesis
TL;DR: A formal definition of robustness as well as algorithmic tools for the design of optimally robust controllers for ω-regular properties on discrete transition systems and an application of the theory to the designs of controllers that tolerate infinitely many transient errors provided they occur infrequently enough are shown.