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作者： Pasqualetti, Fabio Bicchi, Antonio Bullo, Francesco Center for Control Dynamical Systems and Computation University of California Santa Barbara CA United States Centro I. R. E. Piaggio Università di Pisa Pisa Italy

ISBN: (纸本)9781457700804

This work is concerned with the security of a power network against components failure and external attacks. We model a power plant as a linear continuous-time descriptor system. We adopt the framework of structural control theory, and we associate a digraph with the power plant. We provide a necessary and sufficient graph theoretic condition for the existence of vulnerabilities that are inherent to the power network interconnection structure. From a system theoretic perspective, we generalize a known result on the structural rank of the transfer matrix of a state space system to take into account a set of algebraic constraints. © 2011 AACC American Automatic control Council.

关键词： Transfer matrix method

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Design and Real Time implementation of fmincon , MOGA tuned IO-PID and FO-P I λ D μ controllers for Stabilization of TRMS

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Procedia Computer Science 2020年 171卷 1241-1250页

作者： Sudarshan K. Valluru Rajul Kumar Rahul Kumar Center for Control of Dynamical Systems and Computation Dept. of Electrical Engineering Delhi Technological University Delhi-110042 India

The insistence of this paper is to design Fractional order-proportional Integral Derivative (FO-PID) and Integral order –Proportional Integral Derivative (IO-PID) controllers for trajectory tracking control of Twin rotor Multiple Input Multiple Output (MIMO) system (TRMS). The aim of these designed controllers is to move the main and tail actuator at the desired angles accurately to fulfill the demanding attributes so that TRMS should stabilize while hovering. The controller parameters of both the controllers are optimized using fmincon function as well as Multiobjective genetic algorithm. Both the controller are tested in real time and their performance are compared for control of yaw and pitch angles of TRMS. Manual disturbances are given at after 40 seconds of first given disturbance, and the designed controllers are highly capable in diminishing quickly the effect of manual perturbations given to the main and tail rotor of TRMS. From experiment it is observed from comparative performance that FO-PID controller tuned using multiobjective genetic algorithm give best performance in term of time taken to stabilization after the given disturbance.

关键词： FO-PID IO-PID fmincon MOGA TRMS

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On Topological Entropy of Switched Linear systems with Diagonal, Triangular, and General Matrices 57

On Topological Entropy of Switched Linear Systems with Diago...

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57th IEEE Conference on Decision and control, CDC 2018

作者： Yang, Guosong James Schmidt, A. Liberzon, Daniel University of California Center for Control Dynamical Systems and Computation Santa BarbaraCA93106 United States University of Illinois at Urbana-Champaign Coordinated Science Laboratory UrbanaIL61801 United States

ISBN: (纸本)9781538613955

This paper introduces a notion of topological entropy for switched systems, formulated using the minimal number of initial states needed to approximate all initial states within a finite precision. We show that it can be equivalently defined using the maximal number of initial states separable within a finite precision, and introduce switching-related quantities such as the active time of each mode, which prove to be useful in calculating the topological entropy of switched linear systems. For general switched linear systems, we show that the topological entropy is independent of the set of initial states, and establish upper and lower bounds using the active-time-weighted averages of the norms and traces of system matrices in individual modes, respectively. For switched linear systems with scalar-valued state or simultaneously diagonalizable matrices, we derive formulae for the topological entropy using active-time-weighted averages of eigenvalues, which can be extended to the case with simultaneously triangularizable matrices to obtain an upper bound. In these three cases with special matrix structure, we also provide more general but more conservative upper bounds for the topological entropy. © 2018 IEEE.

关键词： Matrix algebra

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Target assignment for robotic networks: Worst-case and stochastic performance in dense environments

Target assignment for robotic networks: Worst-case and stoch...

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Proceedings of the 46th IEEE Conference on Decision and control, Pages 2301-2758

作者： Stephen L. Smith Francesco Bullo Center for Control Dynamical Systems and Computation University of California Santa Barbara CA USA

ISBN: (纸本)9781424414970;1424414970

Consider an equal number of mobile robotic agents and distinct target locations dispersed in an environment. Each agent has a limited communication range and knowledge of every target's position. We study the following target assignment problem: design a distributed algorithm with which the agents divide the targets among themselves and, simultaneously, move to their unique target. This paper focuses on "dense" environments, where the sum of the communication footprints is larger than the area of the environment. We introduce the class of monotonic algorithms, whose worst-case completion time is lower bounded by the area of the environment. We propose a monotonic algorithm called GRID ASSGMT and characterize its asymptotic performance: First, the algorithm is an asymptotically optimal monotonic algorithm for worst-case initial conditions. Second, for uniformly randomly distributed agents and targets the completion time is upper bounded by the diameter of the environment with high probability. Third, if the number of agents exceeds the number of targets by a logarithmic factor, then the completion time is constant with high probability. Our algorithm also solves a sensor based target assignment problem where agents have no initial knowledge of target positions, but acquire them via limited range sensing.

关键词： Completion time Targets Environments Agents communication range algorithms Monotonic distributed algorithms Dense

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Hybrid systems with memory: Modelling and stability analysis via generalized solutions 19

Hybrid systems with memory: Modelling and stability analysis...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Liu, Jun Teel, Andrew R. Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom Center for Control Dynamical Systems and Computation Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States

ISBN: (纸本)9783902823625

Hybrid systems with memory are dynamical systems exhibiting both hybrid and delay phenomena. We present a general modelling framework for such systems using hybrid functional inclusions, whose generalized solutions are defined on hybrid time domains and evolve in the phase space of hybrid memory arcs equipped with the graphical convergence topology. We prove a general existence result based on some basic conditions on the data of hybrid systems. We further establish sufficient conditions for the stability analysis of hybrid systems with memory using Lyapunov-Razumikhin (L-R) functions. We demonstrate the stability results on a general nonlinear system with switching dynamics and state jumps. © IFAC.

关键词： System stability

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Optimal Sensor Placement For Time Difference of Arrival Localization

Optimal Sensor Placement For Time Difference of Arrival Loca...

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Joint 48th IEEE Conference on Decision and control and 28th Chinese control Conference

作者： Jason T.Isaacs Daniel J.Klein Joao P.Hespanha the Center for Control Dynamical Systemsand Computationand the Department of Electrical and Computer EngineeringUniversity of California

This paper addresses the problem of localizing a source from noisy time-of-arrival *** particular,we are interested in the optimal placement of M planar sensors so as to yield the best expected source location *** main result,on maximizing the expected determinant of the Fisher information matrix for truncated,radially-symmetric source distributions,shows two features not previously ***,the sensors should be placed as far from the expected source position as ***,the sensors should be arranged in a splay configuration in which neighboring sensors are separated by equal angle *** examples are given for point,uniform,and truncated-Gaussian source density functions.

关键词： Optimal Sensor Placement For Time Difference of Arrival Localization Sensor

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A Tutorial on Multivariate k-Statistics and their computation

arXiv

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arXiv 2020年

作者： Smith, Kevin D. Center for Control Dynamical Systems and Computation University of California Santa Barbara United States

This document aims to provide an accessible tutorial on the unbiased estimation of multivariate cumulants, using k-statistics. We offer an explicit and general formula for multivariate k-statistics of arbitrary order. We also prove that the k-statistics are unbiased, using Möbius inversion and rudimentary combinatorics. Many detailed examples are considered throughout the paper. We conclude with a discussion of k-statistics computation, including the challenge of time complexity, and we examine a couple of possible avenues to improve the efficiency of this computation. The purpose of this document is threefold: to provide a clear introduction to k-statistics without relying on specialized tools like the umbral calculus;to construct an explicit formula for k-statistics that might facilitate future approximations and faster algorithms;and to serve as a companion paper to our Python library PyMoments [12], which implements this formula. Copyright © 2020, The Authors. All rights reserved.

关键词： Statistics

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Optimization-based Estimation of Expected Values with Application to Stochastic Programming

Optimization-based Estimation of Expected Values with Applic...

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IEEE Annual Conference on Decision and control

作者： Raphael Chinchilla Joao P. Hespanha Center for Control Dynamical Systems and Computation (CCDC) University of California Santa Barbara CA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This paper constructs bounds on the expected value of a scalar function of a random vector. The bounds are obtained using an optimization method, which can be computed efficiently using state-of-the-art solvers, and do not require integration or sampling the random vector. This optimization based approach is especially useful in stochastic programming, where the criteria to be minimized takes the form of an expected value. In particular, we minimize the bounds to solve problems of discrete time finite horizon open-loop control with stochastic perturbations and also uncertainty in the system's parameters. We illustrate this application with two numerical examples.

关键词： Optimization Programming Upper bound Entropy Random variables Monte Carlo methods Loss measurement

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Conditions for saddle-point equilibria in output-feedback MPC with MHE

Conditions for saddle-point equilibria in output-feedback MP...

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American control Conference (ACC)

作者： David A. Copp João P. Hespanha Center for Control Dynamical Systems and Computation University of California Santa Barbara CA USA

A new method for solving output-feedback model predictive control (MPC) and moving horizon estimation (MHE) problems simultaneously as a single min-max optimization problem was recently proposed. This method allows for stability analysis of the joint output-feedback control and estimation problem. In fact, under the main assumption that a saddle-point solution exists for the min-max optimization problem as well as standard observability and controllability assumptions, practical stability can be established in the presence of noise and disturbances. In this paper we derive sufficient conditions for the existence of a saddle-point solution to this min-max optimization problem. For the specialized linear-quadratic case, we show that a saddle-point solution exists if the system is observable and weights in the cost function are chosen appropriately. A numerical example is given to illustrate the effectiveness of this combined control and estimation approach.

关键词： Stability analysis Cost function Noise measurement Numerical stability Games Estimation

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Iterative algorithms for distributed leader-follower model predictive control

Iterative algorithms for distributed leader-follower model p...

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IEEE Annual Conference on Decision and control

作者： Henrique Ferraz Joao P. Hespanha Center for Control Dynamical-systems and Computation (CCDC) University of California Santa Barbara CA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

Two distributed algorithms to estimate the optimal control input sequence that solves a finite horizon quadratic optimization are proposed. The first algorithm utilizes information from 2-hop neighbors, whereas the second only considers 1-hop neighbors. The estimates obtained from both algorithms converge asymptotically, under appropriate assumptions, for any initialization of the algorithm. For the 2-hop algorithm, we show that the converged estimate is the optimal solution to the original optimization problem, while for the 1-hop algorithm the result is generally a suboptimal solution. We evaluate the methods with simulations for a leader-follower model predictive control problem with unstable linear agents dynamics.

关键词： Prediction algorithms Predictive control Heuristic algorithms Optimal control Cost function Distributed algorithms

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