Global and Semi-global Regulated State Synchronization for Homogeneous Networks of Non-introspective Agents in Presence of Input Saturation– A Scale-free Protocol Design

This paper studies global and semi-global regulated state synchronization of homogeneous networks of nonintrospective agents in presence of input saturation based on additional information exchange where the reference trajectory is given by a so-called exosystem which is assumed to be globally reachable. Our protocol design methodology does not need any knowledge of the directed network topology and the spectrum of the associated Laplacian matrix. Moreover, the proposed protocol is scalable and achieves synchronization for any arbitrary number of agents

Filtering Theory - With Applications to Fault Detection, Isolation, and Estimation

The focus of this book is on filtering for linear processes, and its primary goal is to design filters from a class of linear stable unbiased filters that yield an estimation error with the lowest root-mean-square (RMS) norm. Various hierarchical classes of filtering problems are defined based on the availability of statistical knowledge regarding noise, disturbances, and other uncertainties. An important characteristic of the approach employed in this work for several aspects of filter analysis and design is structural in nature, revealing an inherent freedom to incorporate other classical secondary engineering constraints—such as placement of filter poles at desired locations—in filter design. Such a structural approach requires an understanding of powerful tools that then may be used in several engineering applications besides filtering. Key features and topics covered: * Provides an in-depth structural study of powerful tools such as Riccati equations, linear matrix inequalities, and quadratic matrix inequalities. * Develops a general and structural theory of $H_2$ and $H_\infty$ optimal filtering as well as generalized $H_2$ and $H_\infty$ optimal filtering in a broad framework with an extensive and complete analysis and synthesis of filter design. * Examines several hierarchically ordered layers of noise decoupled filtering problems under a single umbrella. * Illustrates the application of filtering theory to fault detection, isolation, and estimation. Filtering Theory is aimed at a broad audience of practicing engineers, graduate students, and researchers in filtering, signal processing, and control. The book may serve as an advanced graduate text for a course or seminar in filtering theory in applied mathematics or engineering departments. Prerequisites for the reader are a first graduate course in state-space methods as well as a first course in filtering

Synchronization in the presence of unknown, nonuniform and arbitrarily large communication delay

This paper studies both output and state synchronization problems for multi-agent systems with agents that are identical and coupled through a network with unknown, nonuniform and arbitrarily large communication delay. We assume that agents are non-introspective (i.e. agents have no access to any of their own states) in the output synchronization problem. The network can be either undirected or directed. In the case of undirected network, exact knowledge of the network is not required and only a specific lower bound is needed. The objective is to design a decentralized protocol such that the multi-agent system achieves output synchronization or state synchronization for any unknown, nonuniform and arbitrarily large communication delay

Solvability conditions and design for state synchronization of multi-agent systems✩

This paper derives conditions on the agents for the existence of a protocol which achieves synchronization of homogeneous multi-agent systems (MAS) with partial-state coupling, where the communication network is directed and weighted. These solvability conditions are necessary and sufficient for single-input agents and sufficient for multi-input agents. The solvability conditions reveal that the synchronization problem is primarily solvable for two classes of agents. This first class consists of at most weakly unstable agents (i.e. agents have all eigenvalues in the closed left half plane) and the second class consists of at most weakly non-minimum-phase agents (i.e. agents have all zeros in the closed left half plane). Under our solvability condition, we provide in this paper a design, utilizing H∞ optimal control

Filtering Theory - With Applications to Fault Detection, Isolation, and Estimation

The focus of this book is on filtering for linear processes, and its primary goal is to design filters from a class of linear stable unbiased filters that yield an estimation error with the lowest root-mean-square (RMS) norm. Various hierarchical classes of filtering problems are defined based on the availability of statistical knowledge regarding noise, disturbances, and other uncertainties. An important characteristic of the approach employed in this work for several aspects of filter analysis and design is structural in nature, revealing an inherent freedom to incorporate other classical secondary engineering constraints—such as placement of filter poles at desired locations—in filter design. Such a structural approach requires an understanding of powerful tools that then may be used in several engineering applications besides filtering. Key features and topics covered: * Provides an in-depth structural study of powerful tools such as Riccati equations, linear matrix inequalities, and quadratic matrix inequalities. * Develops a general and structural theory of $H_2$ and $H_\infty$ optimal filtering as well as generalized $H_2$ and $H_\infty$ optimal filtering in a broad framework with an extensive and complete analysis and synthesis of filter design. * Examines several hierarchically ordered layers of noise decoupled filtering problems under a single umbrella. * Illustrates the application of filtering theory to fault detection, isolation, and estimation. Filtering Theory is aimed at a broad audience of practicing engineers, graduate students, and researchers in filtering, signal processing, and control. The book may serve as an advanced graduate text for a course or seminar in filtering theory in applied mathematics or engineering departments. Prerequisites for the reader are a first graduate course in state-space methods as well as a first course in filtering

Semi-global state synchronization for multi-agent systems subject to actuator saturation and unknown nonuniform input delay

This paper studies semi-global state synchronization of homogeneous networks with diffusive full-state coupling subject to actuator saturation and unknown nonuniform input delay. We assume that agents are at most critical unstable, that is the agents have all its eigenvalues in the closed left-half complex plane. The communication network is associated with an undirected and weighted graph. In this paper, we derive an upper bound for the input delay tolerance, which explicitly depends on the agent dynamics. Moreover, for any unknown delay less than the upper bound, we propose a linear static protocol for MAS based on a low-gain methodology such that state synchronization is achieved among agents for any initial conditions in a priori given compact set

End-point parametrization and guaranteed stability for a model predictive control scheme

In this paper we consider the closed-loop asymptotic stability of the model predictive control scheme which involves the minimization of a quadratic criterion with a varying weight on the end-point state. In particular, we investigate the stability properties of the (MPC-) controlled system as function of the end-point penalty and provide a useful parametrization of the class of end-point penalties for which stability of the controlled system can be guaranteed. The results are successfully applied for the implementation of an MPC controller of a binary distillation proces