The past few years have seen the attention and rapid developments in event-triggered sampled-data systems, in which the effect of event-triggered sensor measurements and controller updates is explored in controller analysis and design. This book offers the first systematic treatment of event-triggered sampled-data control system design using active disturbance rejection control (ADRC), an effective approach that is popular in both theoretic research and industrial applications. Extensive application examples with numerous illustrations are included to show how the event-triggered ADRC with theoretic performance guarantees can be implemented in engineering systems and how the performance can be actually achieved. For theoretic researchers and graduate students, the presented results provide new directions in theoretic research on event-triggered sampled-data systems; for control practitioners, the book offers an effective approach to achieving satisfactory performance with limited sampling rates.

This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications.

The past few years have seen the attention and rapid developments in event-triggered sampled-data systems, in which the effect of event-triggered sensor measurements and controller updates is explored in controller analysis and design. This book offers the first systematic treatment of event-triggered sampled-data control system design using active disturbance rejection control (ADRC), an effective approach that is popular in both theoretic research and industrial applications. Extensive application examples with numerous illustrations are included to show how the event-triggered ADRC with theoretic performance guarantees can be implemented in engineering systems and how the performance can be actually achieved. For theoretic researchers and graduate students, the presented results provide new directions in theoretic research on event-triggered sampled-data systems; for control practitioners, the book offers an effective approach to achieving satisfactory performance with limited sampling rates.

This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications.