Exact topology identification of large-scale interconnected dynamical systems from compressive observations

2011 ◽  
Author(s):  
Borhan M. Sanandaji ◽  
Tyrone L. Vincent ◽  
Michael B. Wakin
Keyword(s):  
Dynamical Systems ◽  
Large Scale ◽  
Topology Identification ◽  
Interconnected Dynamical Systems

Introduction

2011 ◽  
Author(s):  
Wassim M. Haddad ◽  
Sergey G. Nersesov
Keyword(s):  
Dynamical Systems ◽  
Finite Time ◽  
Lyapunov Functions ◽  
Large Scale ◽  
Interconnected Systems ◽  
Large Scale Systems ◽  
Vector Lyapunov Functions ◽  
Finite Time Stabilization ◽  
And Control ◽  
Interconnected Dynamical Systems

This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, with an emphasis on vector Lyapunov function methods and vector dissipativity theory. It examines large-scale continuous-time interconnected dynamical systems and describes thermodynamic modeling of large-scale interconnected systems, along with the use of vector Lyapunov functions to control large-scale dynamical systems. It also discusses finite-time stabilization of large-scale systems via control vector Lyapunov functions, coordination control for multiagent interconnected systems, large-scale impulsive dynamical systems, finite-time stabilization of large-scale impulsive dynamical systems, and hybrid decentralized maximum entropy control for large-scale systems. This chapter provides a brief introduction to large-scale interconnected dynamical systems as well as an overview of the book's structure.

Stability and Control of Large-Scale Dynamical Systems

2011 ◽  
Author(s):  
Wassim M. Haddad ◽  
Sergey G. Nersesov
Keyword(s):  
Dynamical Systems ◽  
Decentralized Control ◽  
Finite Time ◽  
Large Scale ◽  
Synthesis Methods ◽  
Network Systems ◽  
Finite Time Stability ◽  
Analysis And Design ◽  
And Control ◽  
Interconnected Dynamical Systems

Modern complex large-scale dynamical systems exist in virtually every aspect of science and engineering, and are associated with a wide variety of physical, technological, environmental, and social phenomena, including aerospace, power, communications, and network systems, to name just a few. This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, and presents the most complete treatment on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. Large-scale dynamical systems are strongly interconnected and consist of interacting subsystems exchanging matter, energy, or information with the environment. The sheer size, or dimensionality, of these systems necessitates decentralized analysis and control system synthesis methods for their analysis and design. Written in a theorem-proof format with examples to illustrate new concepts, this book addresses continuous-time, discrete-time, and hybrid large-scale systems. It develops finite-time stability and finite-time decentralized stabilization, thermodynamic modeling, maximum entropy control, and energy-based decentralized control. This book will interest applied mathematicians, dynamical systems theorists, control theorists, and engineers, and anyone seeking a fundamental and comprehensive understanding of large-scale interconnected dynamical systems and control.

Embedded order reduction of hierarchical systems within an mCCM framework

2018 ◽  
Vol 37 (4) ◽  
pp. 1535-1544
Author(s):  
Michael Popp ◽  
Wolfgang Mathis
Keyword(s):  
Dynamical Systems ◽  
Large Scale ◽  
Piecewise Linear ◽  
Hierarchical Structures ◽  
Order Reduction ◽  
Hierarchical Level ◽  
Hierarchical Systems ◽  
Content Type ◽  
Reduction Methods ◽  
Interconnected Dynamical Systems

Purpose The purpose of this paper is to present the embedding of linear and nonlinear order reduction methods in a theoretical framework for handling hierarchically interconnected dynamical systems. Design/methodology/approach Based on the component connection modeling (CCM), a modified framework called mCCM for describing interconnected dynamic systems especially with hierarchical structures is introduced and used for order reduction purposes. The balanced truncation method for linear systems and the trajectory piecewise linear reduction scheme are used for the order reduction of systems described within the mCCM framework. Findings It is shown that order reduction methods can be embedded into the context of interconnected dynamical systems with the benefit of having a further degree of freedom in form of the hierarchical level, on which the order reduction is performed. Originality/value The aspect of hierarchy within system descriptions is exploited for order reduction purposes. This distinguishes the presented approach from common methods, which already start with single large-scale systems without explicitly considering hierarchical structures.

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