Skip to main content
main-content

Über dieses Buch

This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as:

· minimum data rate for stabilization of linear systems over noisy channels;

· minimum network requirement for stabilization of linear systems over fading channels; and

· stability of Kalman filtering with intermittent observations.

A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are demonstrated.

Analysis and Design of Networked Control Systems will interest control theorists and engineers working with networked systems and may also be used as a resource for graduate students with backgrounds in applied mathematics, communications or control who are studying such systems.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Overview of Networked Control Systems

Abstract
The primary objective of this chapter is to give an overview of networked control systems (NCSs) and the organization of this book.
Keyou You, Nan Xiao, Lihua Xie

Chapter 2. Entropies and Capacities in Networked Control Systems

Abstract
In this chapter, we introduce some basic concepts and results in communication and information theories.
Keyou You, Nan Xiao, Lihua Xie

Chapter 3. Data Rate Theorem for Stabilization Over Noiseless Channels

Abstract
In classical control theory, a common assumption is that the signals sent from sensors to controllers and from controllers to actuators take continuous values with infinite precision, which is challenged in digital and networked control systems.
Keyou You, Nan Xiao, Lihua Xie

Chapter 4. Data Rate Theorem for Stabilization Over Erasure Channels

Abstract
The quantization process induces information loss in the feedback loop which may significantly affect the operation of the closed-loop system.
Keyou You, Nan Xiao, Lihua Xie

Chapter 5. Data Rate Theorem for Stabilization Over Gilbert-Elliott Channels

Abstract
This chapter continues to investigate the minimum data rate for mean square stabilization of linear systems over a lossy digital channel.
Keyou You, Nan Xiao, Lihua Xie

Chapter 6. Stabilization of Linear Systems Over Fading Channels

Abstract
Fading channels are often encountered in wireless communications and have attracted a lot of attentions in the study of networked control recently.
Keyou You, Nan Xiao, Lihua Xie

Chapter 7. Stabilization of Linear Systems via Infinite-Level Logarithmic Quantization

Abstract
This chapter studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless).
Keyou You, Nan Xiao, Lihua Xie

Chapter 8. Stabilization of Linear Systems via Finite-Level Logarithmic Quantization

Abstract
The logarithmic quantizer is shown in the last chapter to give the coarsest quantization density for quadratic stabilization of an unstable single input linear system. However, it requires an infinite data rate.
Keyou You, Nan Xiao, Lihua Xie

Chapter 9. Stabilization of Markov Jump Linear Systems via Logarithmic Quantization

Abstract
This chapter aims at stabilizing an unstable plant across a lossy channel via quantized feedback.
Keyou You, Nan Xiao, Lihua Xie

Chapter 10. Kalman Filtering with Quantized Innovations

Abstract
This chapter presents a multi-level quantized innovations Kalman filter (MLQ-KF) of linear stochastic systems. For a given multi-level quantization and under the Gaussian assumption on the predicted density, a quantized innovations filter that achieves the MMSE is derived.
Keyou You, Nan Xiao, Lihua Xie

Chapter 11. LQG Control with Quantized Innovation Kalman Filter

Abstract
In this chapter, we generalize the quantized innovation Kalman filter to a symmetric digital channel, and apply it to design the LQG control for discrete-time stochastic systems.
Keyou You, Nan Xiao, Lihua Xie

Chapter 12. Kalman Filtering with Faded Measurements

Abstract
This chapter focuses on the network requirement for ensuring the stability of a remote Kalman filter with faded measurements, where the fading channels undergo transmission failure and signal fluctuation simultaneously.
Keyou You, Nan Xiao, Lihua Xie

Chapter 13. Kalman Filtering with Packet Losses

Abstract
In this chapter, we study the Kalman filtering problem with Markovian packet losses with the focus on the stability of estimation error covariance matrices.
Keyou You, Nan Xiao, Lihua Xie

Chapter 14. Kalman Filtering with Scheduled Measurements

Abstract
Sensor nodes in a WSN are usually battery driven and hence operate on an extremely frugal energy budget. Experimental studies show that communication is a major source of energy consumption in sensor nodes. Thus, it is of paramount importance to reduce the communication load in the network.
Keyou You, Nan Xiao, Lihua Xie

Chapter 15. Parameter Estimation with Scheduled Measurements

Abstract
In the previous chapter, we only discuss the stability of estimator of a dynamical system under scheduled measurements, leaving performance evaluation untouched
Keyou You, Nan Xiao, Lihua Xie

Backmatter

Weitere Informationen