Control and State Estimation for Dynamical Network Systems with Complex Samplings

Computers & Technology

Shen, Bo

Li, Qi

Wang, Zidong

Computer Science

CRC-Press

This book focuses on the control and state estimation problems for dynamical network systems with complex samplings subject to various network-induced phenomena. It includes a series of control and state estimation problems tackled under the passive sampling fashion. Further, it explains the effects from the active sampling fashion, i.e., event-based sampling is examined on the control/estimation performance, and novel design technologies are proposed for controllers/estimators. Simulation results are provided for better understanding of the proposed control/filtering methods. By drawing on a variety of theories and methodologies such as Lyapunov function, linear matrix inequalities, and Kalman theory, su&#64259;cient conditions are derived for guaranteeing the existence of the desired controllers and estimators, which are parameterized according to certain matrix inequalities or recursive matrix equations.<ul> <li>Covers recent advances of control and state estimation for dynamical network systems with complex samplings from the engineering perspective</li> <li>Systematically introduces the complex sampling concept, methods, and application for the control and state estimation</li> <li>Presents unified framework for control and state estimation problems of dynamical network systems with complex samplings</li> <li>Exploits a set of the latest techniques such as linear matrix inequality approach, Vandermonde matrix approach, and trace derivation approach</li> <li>Explains event-triggered multi-rate fusion estimator, resilient distributed sampled-data estimator with predetermined specifications</li> </ul>This book is aimed at researchers, professionals, and graduate students in control engineering and signal processing.

Nonlinear Stochastic Systems with Incomplete Information: Filtering and Control

Nonlinear Stochastic Processes addresses the frequently-encountered problem of incomplete information. The causes of this problem considered here include: missing measurements; sensor delays and saturation; quantization effects; and signal sampling. Divided into three parts, the text begins with a focus on H∞ filtering and control problems associated with general classes of nonlinear stochastic discrete-time systems. Filtering problems are considered in the second part, and in the third the theory and techniques previously developed are applied to the solution of issues arising in complex networks with the design of sampled-data-based controllers and filters. Among its highlights, the text provides: • a unified framework for filtering and control problems in complex communication networks with limited bandwidth; • new concepts such as random sensor and signal saturations for more realistic modeling; and • demonstration of the use of techniques such as the Hamilton–Jacobi–Isaacs, difference linear matrix, and parameter-dependent matrix inequalities and sums of squares to handle the computational challenges inherent in these systems. The collection of recent research results presented in Nonlinear Stochastic Processes will be of interest to academic researchers in control and signal processing. Graduate students working with communication networks with lossy information and control of stochastic systems will also benefit from reading the book.

Shu, Huisheng

Reference

Springer

Nonlinear Stochastic Processes shows the reader how to deal with the issue of network-induced incomplete information. It presents a unified framework for filtering and control problems in complex communication networks with limited bandwidth.

The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel® Xeon Phi™ series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors’ first-hand optimization experience.
The material is organized in three sections. The first section, “Basics of MIC”, introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment. Next, the section on “Performance Optimization” explains general MIC optimization techniques, which are then illustrated step-by-step using the classical parallel programming example of matrix multiplication. Finally, “Project development” presents a set of practical and experience-driven methods for using parallel computing in application projects, including how to determine if a serial or parallel CPU program is suitable for MIC and how to transplant a program onto MIC.
This book appeals to two main audiences: First, software developers for HPC applications – it will enable them to fully exploit the MIC architecture and thus achieve the extreme performance usually required in biological genetics, medical imaging, aerospace, meteorology and other areas of HPC. Second, students and researchers engaged in parallel and high-performance computing – it will guide them on how to push the limits of system performance for HPC applications.

High-Performance Computing on the Intel® Xeon Phi™: How to Fully Exploit MIC Architectures

Wang, Endong

Zhang, Guangyong

Lu, Xiaowei

Wu, Qing

Wang, Yajuan

张青

The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel® Xeon Phi™ series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors’ first-hand optimization experience.The material is organized in three sections. The first section, “Basics of MIC”, introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment. Next, the section on “Performance Optimization” explains general MIC optimization techniques, which are then illustrated step-by-step using the classical parallel programming example of matrix multiplication. Finally, “Project development” presents a set of practical and experience-driven methods for using parallel computing in application projects, including how to determine if a serial or parallel CPU program is suitable for MIC and how to transplant a program onto MIC.This book appeals to two main audiences: First, software developers for HPC applications – it will enable them to fully exploit the MIC architecture and thus achieve the extreme performance usually  required in biological genetics, medical imaging, aerospace, meteorology and other areas of HPC. Second, students and researchers engaged in parallel and high-performance computing – it will guide them on how to push the limits of system performance for HPC applications.

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