Paulo Tabuada

Bio: 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.

Open maps, alternating simulations and control synthesis

Abstract: Control synthesis is slowly transcending its traditional application domain within engineering to find interesting and useful applications in computer science. Synthesis of interfaces, distributed network monitors or reactive programs are some examples that benefit from this design paradigm. In this paper we shed new light on the interplay between the fundamental notion of bisimulation and the control synthesis problem. We first revisit the notion of alternating simulation introduced by Alur and co-workers as it naturally captures important ingredients of the control synthesis problem. We then show that existence of controllers enforcing specifications through bisimulation, alternating simulation or simulation can be characterized by the existence of certain alternating simulations and bisimulations between the specification and the system to be controlled. These results highlight and unify the role of simulations and bisimulations in the control synthesis setting for a wide range of concurrency models. This is achieved by developing our study within the framework of open maps. We illustrate our results on transition systems and timed transition systems.

To beam or not to beam? Beamforming with submodularity-inspired group sparsity

Abstract: In this paper, we address the beamforming problem, which asks to choose the best subset of antennas and their corresponding amplitudes and phases to match a given beam pattern. To solve this problem, we propose an optimization formulation that can efficiently solve large scale problems, and is versatile in its ability to express a variety of meaningful subset selection scenarios. Focusing on the case of antennas with fixed positions, without assuming any geometric structure, we show how to cast the beamforming problem as a regularized least squares problem. Drawing inspiration from subset selection problems in submodular optimization, we select meaningful submodular set functions and use their Lovasz extensions as convex regularizers promoting antenna selection in a useful manner, as demonstrated in a number of presented scenarios.

Controller synthesis for bisimulation equivalence

Abstract: The objective of this paper is to solve the controller synthesis problem for bisimulation equivalence in a wide variety of scenarios including discrete-event systems, nonlinear control systems, behavioral systems, hybrid systems and many others. This will be accomplished by showing that the arguments underlying proofs of existence and methods for the construction of controllers are extraneous to the particular class of systems being considered and thus can be presented in greater generality.

Self-Triggered Control: trading actuation for computation

Abstract: Nowadays control systems are mostly implemented on digital platforms and, increasingly, over shared communication networks. Reducing resources (processor utilization, network bandwidth, etc.) in such implementations increases the potential to run more applications over the same hardware. We present a self-triggered implementation of linear controllers for control systems that reduces the amount of controller updates necessary to retain stability of the closed loop system. Furthermore, we show that the proposed self-triggered implementation is robust against additive disturbances and provide explicit guarantees of performance. The proposed technique exhibits an inherent trade-off between computation and potential savings on actuation.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Information flow and cooperative control of vehicle formations

Abstract: We consider the problem of cooperation among a collection of vehicles performing a shared task using intervehicle communication to coordinate their actions. Tools from algebraic graph theory prove useful in modeling the communication network and relating its topology to formation stability. We prove a Nyquist criterion that uses the eigenvalues of the graph Laplacian matrix to determine the effect of the communication topology on formation stability. We also propose a method for decentralized information exchange between vehicles. This approach realizes a dynamical system that supplies each vehicle with a common reference to be used for cooperative motion. We prove a separation principle that decomposes formation stability into two components: Stability of this is achieved information flow for the given graph and stability of an individual vehicle for the given controller. The information flow can thus be rendered highly robust to changes in the graph, enabling tight formation control despite limitations in intervehicle communication capability.

Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks

Abstract: In this note, we revisit the problem of scheduling stabilizing control tasks on embedded processors. We start from the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant. This controller has for objective guaranteeing that (control unrelated) software tasks meet their deadlines and that stabilizing control tasks asymptotically stabilize the plant. We investigate a simple event-triggered scheduler based on this feedback paradigm and show how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements.

Coverage control for mobile sensing networks

Abstract: This paper describes decentralized control laws for the coordination of multiple vehicles performing spatially distributed tasks. The control laws are based on a gradient descent scheme applied to a class of decentralized utility functions that encode optimal coverage and sensing policies. These utility functions are studied in geographical optimization problems and they arise naturally in vector quantization and in sensor allocation tasks. The approach exploits the computational geometry of spatial structures such as Voronoi diagrams.

Coverage control for mobile sensing networks

Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.