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**.**