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This book considers the problems of network-based control and optimization. With the rapid development of science and technology, networks play an important role in control systems. Typically, in a control system, the plant and the controller may communicate via a network. Such systems are called networked control systems and they have received significant attention in the literature. The introduction of a network has many advantages such as low cost, easy installation, and maintenance. However, a network also introduces some imperfections such as varying sampling, transmission delays, transmission protocols, packet losses, and so on. Besides, the network may also suffer from network attacks such as Denial of Service attacks. These imperfections may degrade the system performance and even make the closed-loop systems unstable. Therefore, it is necessary to investigate the effect of these imperfections on the stability and performance of control systems in a quantitative manner.
The content of this book consists of two parts. The first part aims at proposing modeling and analyzing approaches for network-based control systems under different problem settings. Model-based event-triggered transmission strategies are proposed to reduce the data transmissions in the network. We also consider the stability problem for networked control systems in the presence of stochastic noise and stochastic detecting instants. For all of these cases, hybrid models are established and Lyapunov functions are constructed. The second part first investigates the distributed unconstrained optimization problem which is solved over a network communication topology. The network may be destroyed by persistent attackers that result in communication failures. A distributed switching algorithm is proposed and a hybrid model is established to analyze stability. Then, the proposed method is extended to constrained aggregative games which are subject to unknown time-varying disturbances and unmodeled terms, and the communication topology is also influenced by attacks. This book provides a unifying framework to understand the complex dynamics of network-based control systems. The content is appropriate for students, control engineers, and scientists who are interested in network-based control and optimization problems.
Introduction
Modeling and Stability Analysis for Networked Control Systems
Model-Based Event-Triggered Control for Distributed Networked Control Systems
Periodic Event-Triggered Control for Decentralized Linear Systems with Quantization Effects and External Disturbances
Event-Triggered Stabilization for Nonlinear Systems by Uniting the Local and Global Controller
Event-Triggered Control for Nonlinear Systems With Stochastic Dynamics, Transmission Instants and Protocols
Distributed Optimization with Network Communication
Stability Analysis of Distributed Convex Optimization Under Persistent Attacks
Distributed Robust Nash Equilibrium Seeking for Aggregative Games Under Persistent Attacks