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

作者： Mirtabatabaei, Anahita Jia, Peng Bullo, Francesco Center for Control Dynamical Systems and Computation University of California Santa Barbara Santa Barbara CA 93106 United States

ISBN: (纸本)9783902823229

The formation of opinions in a large population is governed by endogenous (human interactions) and exogenous (media influence) factors. In the analysis of opinion evolution in a large population, decision making rules can be approximated with non-Bayesian "rule of thumb" methods. This paper focuses on an Eulerian bounded-confidence model of opinion dynamics with a potential time-varying exogenous input. First, we prove some properties of this system's dynamics with time-varying input. Second, we prove the convergence of the population's distribution with no input to a sum of Dirac Delta measures. Finally, we define an input's attraction range, and for a normally distributed input and uniformly distributed initial population, we conjecture that the length of attraction range is an increasing affine function of population's confidence bound and input's variance. © 2012 IFAC.

关键词： Dynamics

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Algorithms for the traveling salesman problem with neighborhoods involving a Dubins vehicle

Algorithms for the traveling salesman problem with neighborh...

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作者： Isaacs, Jason T. Klein, Daniel J. Hespanha, João P. Center for Control Dynamical Systems and Computation Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106 United States

ISBN: (纸本)9781457700804

We study the problem of finding the minimum-length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (DTSPN). Two algorithms are presented that transform this infinite dimensional combinatorial optimization problem into a finite dimensional asymmetric TSP by sampling and applying the appropriate transformations, thus allowing the use of existing approximation algorithms. We show for the case of disjoint regions, the first algorithm needs only to sample each region once to produce a tour within a factor of the length of the optimal tour that is independent of the number of regions. We present a second algorithm that performs no worse than the best existing algorithm and can perform significantly better when the regions overlap. © 2011 AACC American Automatic control Council.

关键词： Traveling salesman problem

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Design and experimental implementation of multi-loop LQR, PID, and LQG controllers for the trajectory tracking control of twin rotor MIMO system 3rd

Design and experimental implementation of multi-loop LQR, PI...

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3rd International Conference on Intelligent Communication, control and Devices, ICICCD 2018

作者： Valluru, Sudarshan K. Singh, Madhusudan Ayush Dharavath, Abhiraj Department of Electrical Engineering Incubation Center for Control Dynamical Systems and Computation Delhi Technological University New DelhiDelhi110042 India

ISBN: (纸本)9789811386176

One DOF (degree of freedom) Twin Rotor multi-input multi-output system (TRMS) is one of the benchmarked dynamical systems which has striking comparability with Helicopter. Design of controllers for such complex air vehicle is a daunting task as it has inherent nonlinearities and cross-coupling between its main and tail rotors. Therefore, it is an interesting laboratory benchmarked control problem, to test the performance of various controllers. The control techniques focused in this paper are the experimental implementation of multi-loop controllers such as Linear Quadratic Regulator (LQR), linear proportional integral derivative (L-PID), and Linear Quadratic Gaussian (LQG) controllers on TRMS system to verify the performance of these controllers. © Springer Nature Singapore Pte Ltd. 2020.

关键词： controllers

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Experimental validation of fully informed particle swarm optimization tuned multi-loop L-PID controllers for stabilization of gantry crane system 3rd

Experimental validation of fully informed particle swarm opt...

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3rd International Conference on Intelligent Communication, control and Devices, ICICCD 2018

作者： Valluru, Sudarshan K. Singh, Madhusudan Dobhal, Daksh Kartikeya, Kumar Kaur, Manpreet Goel, Arnav Department of Electrical Engineering Incubation Center for Control Dynamical Systems and Computation Delhi Technological University New DelhiDelhi110042 India

ISBN: (纸本)9789811386176

Linear PID controllers are commonly used as an electrical component to decrease the error between anticipated set value and actual measured values for control of various benchmarked systems. The Multi-Loop Linear PID (ML-PID) controller, gives a robust and efficient performance in most of the situations. This paper presents the implementation of linear PID controller to stabilize and control the Gantry Crane System. Optimal performance is obtained for a few specific combinations of the proportional, integral, and derivative gains, which makes it essential to tune these values through Optimization techniques. The Fully Informed Particle Swarm Optimizer (FIPSO) is used to tune the gain values of the ML-PID controlled Gantry Crane System. These values are validated experimentally, and obtained results prove that the FIPSO tuned multi-loop linear PID controller quickly stabilizes the system subjected to external disturbances. © Springer Nature Singapore Pte Ltd. 2020.

关键词： controllers

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Distributed estimation via iterative projections with application to power network monitoring

Distributed estimation via iterative projections with applic...

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作者： Pasqualetti, Fabio Carli, Ruggero Bullo, Francesco Center for Control Dynamical Systems and Computation University of California Santa Barbara United States Department of Information Engineering University of Padova Padova Italy

This work presents a distributed method for control centers to monitor the operating condition of a power network, i.e.;to estimate the network state, and to ultimately determine the occurrence of threatening situations. State estimation has been recognized to be a fundamental task for network control centers to operate safely and reliably a power grid. We consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltage phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state, given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is used, whereas, in the second method, a diffusive interaction is implemented. Our procedures, which require each control center to know only the measurements and the structure of a subpart of the whole network, are computationally efficient and scalable with respect to the network dimension, provided that the number of control centers also increases with the network cardinality. Additionally, a finite-memory approximation of our diffusive algorithm is proposed, and its accuracy is characterized. Finally, our estimation methods are exploited to develop a distributed algorithm to detect corrupted network measurements. © 2012 Elsevier Ltd. All rights reserved.

关键词： State estimation

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Hybrid systems: computation and control 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： João P. Hespanha Ashish Tiwari

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Continuous graph partitioning for camera network surveillance

Continuous graph partitioning for camera network surveillanc...

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

作者： Borra, D. Pasqualetti, F. Bullo, F. Dipartimento di Scienze Matematiche Politecnico di Torino Italy Center for Control Dynamical Systems and Computation University of California Santa Barbara United States

ISBN: (纸本)9783902823229

This work focuses on the problem of designing surveillance trajectories for a network of autonomous cameras. As performance criterion we consider the worst-case detection time of static intruders. First, we represent the environment by means of a robotic roadmap. We show that optimal trajectories can be designed via a continuous graph partitioning problem. This minimization problem is convex and not differentiable. Second, we derive an auxiliary convex and differentiable minimization problem whose minimizer provides a solution to the original problem. Third and finally, we develop three distributed algorithms, for the cameras to partition the roadmap, and, consequently, synchronize along a trajectory with minimum worst-case detection time. Different communication protocols are used for the three algorithms. © 2012 IFAC.

关键词： Trajectories

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João Hespanha [People in control]

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IEEE control systems 2014年第1期34卷 22-24页

作者： Hespanha, João Center for Control Dynamical Systems and Computation University of California Santa BarbaraCA United States Department of Electrical and Computer Engineering University of California Harold Frank Hall Santa BarbaraCA93106-9560 United States

In this issue of IEEE control systems Magazine, we speak with João Hespanha, who is a professor and chair of the Department of Electrical and Computer Engineering and Director of the center for control, dynamical systems, and computation at the University of California, Santa Barbara. He received a Licenciatura and an M.S. at Instituto Superior Técnico, Lisbon, Portugal, in 1991 and 1993, respectively, and a Ph.D. from Yale University in 1998. He was formerly on the faculty in the Department of Electrical Engineering at the University of Southern California. He is a Fellow of IEEE and a recipient of the Automatica Theory/Methodology Best Paper Prize, the George S. Axelby Outstanding Paper Award, and the Antonio Ruberti Young Researcher Prize. His research interests include hybrid systems, networked control systems, cooperative control, advanced sensing, and systems biology. © 2014 IEEE.

关键词： Hybrid systems

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Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees 38

Learning Neural Contracting Dynamics: Extended Linearization...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Jaffe, Sean Davydov, Alexander Lapsekili, Deniz Singh, Ambuj K. Bullo, Francesco Center for Control Dynamical Systems and Computation University of California Santa Barbara United States Department of Computer Science University of California Santa Barbara United States

Global stability and robustness guarantees in learned dynamical systems are essential to ensure well-behavedness of the systems in the face of uncertainty. We present Extended Linearized Contracting Dynamics (ELCD), the first neural network-based dynamical system with global contractivity guarantees in arbitrary metrics. The key feature of ELCD is a parametrization of the extended linearization of the nonlinear vector field. In its most basic form, ELCD is guaranteed to be (i) globally exponentially stable, (ii) equilibrium contracting, and (iii) globally contracting with respect to some metric. To allow for contraction with respect to more general metrics in the data space, we train diffeomorphisms between the data space and a latent space and enforce contractivity in the latent space, which ensures global contractivity in the data space. We demonstrate the performance of ELCD on the high dimensional LASA, multi-link pendulum, and Rosenbrock datasets. © 2024 Neural information processing systems foundation. All rights reserved.

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Worst-case time complexity of a lattice formation problem 44

Worst-case time complexity of a lattice formation problem

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44th Annual Allerton Conference on Communication, control, and Computing 2006

作者： Savla, Ketan Bullo, Francesco Center for Control Dynamical Systems and Computation University of California at Santa Barbara 2338 Engineering Bldg II Santa BarbaraCA93106-5070 United States

ISBN: (纸本)9781604237924

We consider a formation control problem for a robotic network with limited communication and controlled motion abilities. We propose a novel control structure that organizes the robots in concentric layers and that associates to each layer a local leader. Through a load balancing algorithm on the asynchronous network of layers we allocate the desired number of robots on each layer. A final uniform spreading algorithm leads the robots to a lattice-like formation. This novel distributed communication and control algorithm runs in linear time in the worst case.

关键词： Robots

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