Abstract
State estimation or soft sensing is a field that deals with the methods that are used to estimate the unmeasured process variables through the use of known measurements and process knowledge. The increased degree of automation and the growing demand for higher performance in industrial systems make state estimation an integral part of various operational strategies associated with process systems engineering field. It exhibits a greater role in the design, modeling, monitoring, fault diagnosis, optimization, control, and operation of all kinds of chemical, physical, biological, and other engineering processes through the use of systematic computer-aided approaches. The task of state estimation has become more challenging in the face of growing demand to meet the requirements of process safety, environmental regulations, energy efficiency, better product quality, and optimum utilization of available resources. Its major challenges are the development of concepts, methodologies, and procedures for performance improvement of an engineered system. This introductory chapter explains the significance and importance of state estimation and briefs about the theme of this book that deals with the details of fundamentals, algorithms, examples, applications, and case studies concerning different approaches and methods of state estimation.
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