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International Joint Conference on Neural Networks

作者： Kyriakos G. Vamvoudakis Center for Control Dynamical-systems and Computation (CCDC) University of California

ISBN: (纸本)9781509006212

In this paper a game-theoretic adaptive learning algorithm based on an action-dependent value function (Q-function) is proposed to solve the optimal tracking control problem with adversarial inputs and completely unknown system and reference dynamics. In order to convert the tracking problem to a regulation problem we augment the system and the reference states and pick appropriately the user-defined matrices. An integral reinforcement learning approach is used to estimate the parameters of the Q-function while also guaranteeing closed-loop stability, trajectory tracking and convergence of the policies to a saddle point. A simulation result of a Quanser helicopter shows the efficacy of the proposed approach.

关键词： Q-learning Zero-sum game Optimal tracking Uncertain systems Adversaries uncertain systems tracking control Q FUNCTIONS Zero sum game Simulation results Cyber-physical systems tracking problem saddles actuators reference state

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Hide-and-seek with directional sensing

Hide-and-seek with directional sensing

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作者： Borri, Alessandro Bopardikar, Shaunak D. Hespanha, Joao P. Di Benedetto, Maria D. Department of Electrical Engineering University of L'Aquila Italy Center for Control Dynamical Systems and Computation University of California Santa Barbara CA 93106 United States

ISBN: (纸本)9783902661937

We consider a game played between a hider, who hides a static object in one of several possible positions in a bounded planar region, and a searcher, who wishes to reach the object by querying sensors placed in the plane. The searcher is a mobile agent, and whenever it physically visits a sensor, the sensor returns a randomdirection, corresponding to a half-plane in which the hidden object is *** first present a novel search heuristic and characterize bounds on the expected distance covered before reaching the object. Next, we model this game as a large-dimensional zero-sum dynamic game and we apply a recently introduced randomized sampling technique that provides a probabilistic level of security to the hider. We observe that, when the randomized sampling approach is only allowed to select a very small number of samples, the cost of the heuristic is comparable to the security level provided by the randomized procedure. However, as we allow the number of samples to increase, the randomized procedure provides a higher probabilistic security level. © 2011 IFAC.

关键词： Mobile agents

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Inference of Infrastructure Network Flows via Physics-Inspired Implicit Neural Networks

Inference of Infrastructure Network Flows via Physics-Inspir...

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2023 IEEE Conference on control Technology and Applications, CCTA 2023

作者： Seccamonte, Francesco Singh, Ambuj K. Bullo, Francesco University of California Center for Control Dynamical Systems and Computation Santa Barbara United States University of California Department of Computer Science Santa Barbara United States

ISBN: (纸本)9798350335446

We study the problem of inferring edge flows and nodal injections in infrastructure networks. Leveraging the Thomson's Principle from the electric circuits literature, we setup a framework to jointly learn network parameters and missing states. Despite being application agnostic, the proposed approach captures the fundamental physics of the infrastructure, and is able to handle partial observation, node and edge features as well as operational constraints. The physics inspired learning framework leads to a bilevel optimization problem, which is NP hard in general. By exploiting convexity properties, we reformulate the problem as a single level optimization, composed of a graph neural network and an additional implicit layer. The resulting architecture can be trained using standard gradient-based methods. We assess the validity of the proposed approach on two different infrastructure networks (power and traffic), and show it outperforms the current state of the art. © 2023 IEEE.

关键词： Graph neural networks

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On the dubins traveling salesperson problems: Novel approximation algorithms 2nd

On the dubins traveling salesperson problems: Novel approxim...

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2nd International Conference on Robotics Science and systems, RSS 2006

作者： Savla, Ketan Frazzoli, Emilio Bullo, Francesco Center for Control Dynamical Systems and Computation University of California at Santa Barbara United States Mechanical and Aerospace Engineering Department University of California Los Angeles United States

ISBN: (纸本)9780262693486

In this paper we study minimum-time motion planning and routing problems for the Dubins vehicle, i.e., a nonholonomic vehicle that is constrained to move along planar paths of bounded curvature, without reversing direction. Motivated by autonomous aerial vehicle applications, we consider the Traveling Salesperson Problem for the Dubins vehicle (DTSP): given n points on a plane, what is the shortest Dubins tour through these points and what is its length? Specifically, we study a stochastic version of the DTSP where the n targets are randomly sampled from a uniform distribution. We show that the expected length of such a tour is of order at least n2/3 and we propose a novel algorithm yielding a solution with length of order n2/3 with high probability. Additionally, we study a dynamic version of the DTSP: given a stochastic process that generates target points, is there a policy which guarantees that the number of unvisited points does not diverge over time? If such stable policies exist, what is the minimum expected time that a newly generated target waits before being visited by the vehicle? We propose a novel stabilizing algorithm such that the expected wait time is provably within a constant factor from the optimum.

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A gossip based heuristic algorithm for heterogeneous multi-vehicle routing problems

A gossip based heuristic algorithm for heterogeneous multi-v...

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3rd IFAC Workshop on Distributed Estimation and control in Networked systems, NECSYS 2012

作者： Rosa, Daniele Franceschelli, Mauro Seatzu, Carla Bullo, Francesco Dep. of Electrical and Electronic Engineering Univ. of Cagliari Italy Center for Control Dynamical Systems and Computation Univ. of Santa Barbara CA United States

ISBN: (纸本)9783902823229

In this paper we propose a novel algorithm based on gossip communication for the Heterogeneous Multi-Vehicle Routing (HMVR) problem. A collection of tasks is arbitrarily placed in a plane and a set of robots cooperates to minimize the maximum time required to visit and execute all tasks. Each task (resp. each robot) has different cost (resp. speed). The proposed algorithm relies only upon pairwise asynchronous communications between robots and attempts to balance the routing and execution cost of the task assignment through a heuristic. The proposed heuristic exploits polynomial-time approximation algorithms to solve the Euclidean Traveling Salesman Problem (ETSP). Some characterization of the convergence properties of the algorithm are provided together with extensive simulations to corroborate the results. © 2012 IFAC.

关键词： Robots

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Exploring synchronization in complex oscillator networks

Exploring synchronization in complex oscillator networks

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IEEE Conference on Decision and control

作者： Florian Dörfler Francesco Bullo Center for Control Dynamical Systems and Computation University of California USA

ISBN: (纸本)9781467320658

The emergence of synchronization in a network of coupled oscillators is a pervasive topic in various scientific disciplines ranging from biology, physics, and chemistry to social networks and engineering applications. A coupled oscillator network is characterized by a population of heterogeneous oscillators and a graph describing the interaction among the oscillators. These two ingredients give rise to a rich dynamic behavior that keeps on fascinating the scientific community. In this article, we present a tutorial introduction to coupled oscillator networks, we review the vast literature on theory and applications, and we present a collection of different synchronization notions, conditions, and analysis approaches. We focus on the canonical phase oscillator models occurring in countless real-world synchronization phenomena, and present their rich phenomenology. We review a set of applications relevant to control scientists. We explore different approaches to phase and frequency synchronization, and we present a collection of synchronization conditions and performance estimates. For all results we present self-contained proofs that illustrate a sample of different analysis methods in a tutorial style.

关键词： Synchronization Oscillators Frequency synchronization Mathematical model Couplings Vehicle dynamics Analytical models

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Accuracy and decision time for sequential decision aggregation

Accuracy and decision time for sequential decision aggregati...

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作者： Dandach, Sandra H. Carli, Ruggero Bullo, Francesco Center for Control Dynamical Systems and Computation University of California at Santa Barbara Santa Barbara CA 93106 United States United Technologies Research Center East Hartford CT 06108 United States Department of Information Engineering University of Padova Padova 35131 Italy Department of Mechanical Engineering Center for Control Dynamical Systems and Computation University of California at Santa Barbara Santa Barbara CA 93106 United States

This paper studies prototypical strategies to sequentially aggregate independent decisions. We consider a collection of agents, each performing binary hypothesis testing and each obtaining a decision over time. We assume the agents are identical and receive independent information. Individual decisions are sequentially aggregated via a threshold-based rule. In other words, a collective decision is taken as soon as a specified number of agents report a concordant decision (simultaneous discordant decisions and no-decision outcomes are also handled). We obtain the following results. First, we characterize the probabilities of correct and wrong decisions as a function of time, group size, and decision threshold. The computational requirements of our approach are linear in the group size. Second, we consider the so-called fastest and majority rules, corresponding to specific decision thresholds. For these rules, we provide a comprehensive scalability analysis of both accuracy and decision time. In the limit of large group sizes, we show that the decision time for the fastest rule converges to the earliest possible individual time, and that the decision accuracy for the majority rule shows an exponential improvement over the individual accuracy. Additionally, via a theoretical and numerical analysis, we characterize various speed/accuracy tradeoffs. Finally, we relate our results to some recent observations reported in the cognitive information processing (CIP) literature. © 2011 IEEE.

关键词： Decision making

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Further Results on Distributed Secondary control in Microgrids

Further Results on Distributed Secondary Control in Microgri...

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IEEE Annual Conference on Decision and control

作者： Hedi Bouattour John W. Simpson-Porco Florian Dorfler Francesco Bullo Center for Control Dynamical Systems and Computation University of California at Santa Barbara

ISBN: (纸本)9781467357159

This work presents several analysis and design results for primary droop control and secondary control in inductive microgrids. Building on our recent work, we study the problem of set point design in droop-controlled microgrids, and provide a choice of droop coefficients leading to the desired power flows. We then compare and contrast two distributed secondary controllers, and extend them to the case where only a fraction of inverters cooperate in regulating the network frequency. We show that both these secondary-control schemes achieve frequency regulation in the presence of resistive losses.

关键词： Inverters Synchronization Stability analysis Microgrids Frequency control Steady-state Vectors

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Opinion dynamics and social power evolution: A single-timescale model

arXiv

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arXiv 2017年

作者： Jia, Peng Friedkin, Noah E. Bullo, Francesco Center for Control Dynamical Systems and Computation University of California at Santa Barbara

This paper studies the evolution of self-appraisal and social power, for a group of individuals who discuss and form opinions. We consider a modification of the recently proposed DeGroot-Friedkin (DF) model, in which the opinion formation process takes place on the same timescale as the reflected appraisal process;we call this new model the single-timescale DF model. We provide a comprehensive analysis of the equilibria and convergence properties of the model for the settings of irreducible and reducible influence networks. For the setting of irreducible influence networks, the single-timescale DF model has the same behavior as the original DF model, that is, it predicts among other things that the social power ranking among individuals is asymptotically equal to their centrality ranking, that social power tends to accumulate at the top of the centrality ranking hierarchy, and that an autocratic (resp., democratic) power structure arises when the centrality scores are maximally nonuniform (resp., uniform). For the setting of reducible influence networks, the single-timescale DF model behaves differently from the original DF model in two ways. First, an individual, who corresponds to a reducible node in a reducible influence network, can keep all social power in the single-timescale DF model if the initial condition does so, whereas its social power asymptotically vanishes in the original DF model. Second, when the associated network has multiple sinks, the two models behave very differently: the original DF model has a single globally-attractive equilibrium, whereas any partition of social power among the sinks is allowable at equilibrium in the single-timescale DF model. Copyright © 2017, The Authors. All rights reserved.

关键词： dynamical systems

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Supervisory control of nonlinear systems

Supervisory control of nonlinear systems

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European control Conference (ECC)

作者： João P. Hespanha Center for Control Dynamical Systems and Computation University of California Santa Barbara

The control of nonlinear systems with large uncertainty is especially challenging. In spite of this, significant progress has been made in the area of multi-model supervisory control.

关键词： Supervisory control Nonlinear systems Noise Robustness Uncertainty Process control

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