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.

Input-to-state stability of self-triggered control systems

Abstract: Event-triggered and self-triggered control have recently been proposed as an alternative to periodic implementations of feedback control laws over sensor/actuator networks. In event-triggered control, each sensing node continuously monitors the plant in order to determine if fresh information should be transmitted and if the feedback control law should be recomputed. In general, event-triggered control substantially reduces the number of exchanged messages when compared with periodic implementations. However, such energy savings must be contrasted with the energy required to perform local computations. In self-triggered control, computation of the feedback control law is followed by the computation of the next time instant at which fresh information should be sensed and transmitted. Since this time instant is computed as a function of the current state and plant dynamics, it is still much larger than the sampling period used in periodic implementations. Moreover, no energy is spent in local computations at the sensors. However, the plant operates in open-loop between updates of the feedback control law and robustness is a natural concern. We analyze the robustness to disturbances of a self-triggered implementation recently introduced by the authors for linear control systems. We show that such implementation is exponentially input-to-state stable with respect to disturbances.

Decentralized event-triggered control over wireless sensor/actuator networks

Abstract: In recent years we have witnessed a move of the major industrial automation providers into the wireless domain. While most of these companies already offer wireless products for measurement and monitoring purposes, the ultimate goal is to be able to close feedback loops over wireless networks interconnecting sensors, computation devices, and actuators. In this paper we present a decentralized event-triggered implementation, over sensor/actuator networks, of centralized nonlinear controllers. Event-triggered control has been recently proposed as an alternative to the more traditional periodic execution of control tasks. In a typical event-triggered implementation, the control signals are kept constant until the violation of a condition on the state of the plant triggers the re-computation of the control signals. The possibility of reducing the number of re-computations, and thus of transmissions, while guaranteeing desired levels of performance makes event-triggered control very appealing in the context of sensor/actuator networks. In these systems the communication network is a shared resource and event-triggered implementations of control laws offer a flexible way to reduce network utilization. Moreover reducing the number of times that a feedback control law is executed implies a reduction in transmissions and thus a reduction in energy expenditures of battery powered wireless sensor nodes.

Adaptive cruise control: Experimental validation of advanced controllers on scale-model cars

Abstract: Recent advances in automotive technology, such as, sensing and onboard computation, have resulted in the development of adaptive cruise control (ACC) algorithms that improve both comfort and safety. With a view towards developing advanced controllers for ACC, this paper presents an experimental platform for validation and demonstration of an online optimization based controller. Going beyond traditional PID based controllers for ACC that lack proof of safety, we construct a control framework that gives formal guarantees of correctness. In particular, safety constraints—maintaining a valid following distance from a lead car—are represented by control barrier functions (CBFs), and control objectives— achieving a desired speed—are encoded through control Lyapunov functions (CLFs). These different objectives can be unified through a quadtraic program (QP), with constraints dictated by CBFs and CLFs, that balances safety and the control objectives in an optimal fashion. This methodology is demonstrated on scale-model cars, for which the CBF-CLF based controller is implemented online, with the end result being the experimental validation of an advanced adaptive cruise controller.

On the stability of zeno equilibria

Abstract: Zeno behaviors are one of the (perhaps unintended) features of many hybrid models of physical systems. They have no counterpart in traditional dynamical systems or automata theory and yet they have remained relatively unexplored over the years. In this paper we address the stability properties of a class of Zeno equilibria, and we introduce a necessary paradigm shift in the study of hybrid stability. Motivated by the peculiarities of Zeno equilibria, we consider a form of asymptotic stability that is global in the continuous state, but local in the discrete state. We provide sufficient conditions for stability of these equilibria, resulting in sufficient conditions for the existence of Zeno behavior.

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.