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.

Dynamic Scheduling and Control-Quality Optimization of Self-Triggered Control Applications

Abstract: Time-triggered periodic control implementations are over provisioned for many execution scenarios in which the states of the controlled plants are close to equilibrium. To address this inefficient use of computation resources, researchers have proposed self-triggered control approaches in which the control task computes its execution deadline at runtime based on the state and dynamical properties of the controlled plant. The potential advantages of this control approach cannot, however, be achieved without adequate online resource-management policies. This paper addresses scheduling of multiple self-triggered control tasks that execute on a uniprocessor platform, where the optimization objective is to find trade-offs between the control performance and CPU usage of all control tasks. Our experimental results show that efficiency in terms of control performance and reduced CPU usage can be achieved with the heuristic proposed in this paper.

On the minimum attention and anytime attention problems for nonlinear systems

Abstract: The current convergence of control, communication and computation opens the door to new avenues for the applicability of control systems, but it also leads to new constraints and requirements. The traditional quadratic cost function has become too plain to represent the diverse performance indices of today's complex applications. For instance, the implementation cost of a control law has become a major factor, since resources are frequently shared among different tasks. Implementation costs of control laws depend on a wide range of factors: computation complexity, sensor accuracy, required bandwidth, actuation speed, or sampling rates, to name a few. In this paper we focus on the notion of attention, that is, how often the loop needs to be closed in order to achieve a desired performance. We propose two attention-aware control laws: first, a technique to construct minimum attention control laws that maximizes the open loop operation of a nonlinear control system; and second, a control algorithm that permits the system run in open loop for a pre-scheduled amount of time.

Input-output robustness for discrete systems

Abstract: Robustness is the property that a system only exhibits small deviations from the nominal behavior upon the occurrence of small disturbances. While the importance of robustness in engineering design is well accepted, it is less clear how to verify and design discrete systems for robustness. We present a theory of input-output robustness for discrete systems inspired by existing notions of input-output stability (IO-stability) in continuous control theory. We show that IO-stability captures two intuitive goals of robustness: bounded disturbances lead to bounded deviations from nominal behavior, and the effect of a sporadic disturbance disappears in finitely many steps. We show that existing notions of robustness for discrete systems do not have these two properties. For systems modeled as finite-state transducers, we show that IO-stability can be verified and the synthesis problem can be solved in polynomial time. We illustrate our theory using a reference broadcast synchronization protocol for wireless networks.

Synthesis of safety controllers robust to unmodeled intermittent disturbances

Abstract: The synthesis of controllers enforcing safety properties is a well understood problem for which we have practical algorithms as well as a deep theoretical understanding. This problem is typically formulated as game between the controller seeking to enforce the safety property and the environment seeking to violate it. The solution of these games is given by a winning set: inside the winning set the controller can enforce the desired property as long as it chooses one of the many inputs that forces the system to remain inside the winning set; outside the winning set the environment can violate the winning property independently of the controller's actions. In this paper we answer the following two questions: (1) Among the several inputs available to the controller inside the winning set, are there inputs that are “better” than others? (2) What should the controller do when the state is outside the winning set? In answering these questions we are guided by a desire to be robust to unmodeled intermittent disturbances.

Abstracting Partially Feedback Linearizable Systems Compositionally

Abstract: Symbolic controller synthesis offers the ability to design controllers enforcing a rich class of specifications such as those expressible in temporal logic. Despite the promise of symbolic controller synthesis and correct-by-design control software, this design methodology is not yet widely applicable due to the complexity of constructing finite-state abstractions for large continuous systems. In this letter, we investigate a compositional approach to the construction of abstractions by exploiting the cascading structure of partially feedback linearizable systems. We show how the linearized part and the zero dynamics can be independently abstracted and subsequently composed to obtain an abstraction of the original continuous system. We also illustrate through examples how this compositional approach significantly reduces the time required for construction of abstractions.

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.