Elsevier Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control

Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, extending to classical methods and successively leading to advances in this field. Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful for the audience working in different disciplines in academics, research and industry in areas concerning to process monitoring, fault diagnosis, control and related disciplines. Review Describes various classical and advanced methods of state estimation, with applications concerning a number of chemical and biochemical processes From the Back Cover <p><i>Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control </i>presents various mechanistic model-based state estimators and data-driven model-based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, moving through classical methods and gradually leading to advances in this field.</p> <p>Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful to the persons working in different disciplines in academics, research and industry in areas concerning to process monitoring, diagnosis, control and related disciplines. Because of its features and systematic presentation of the information content from concepts to advances, anyone can learn and advance their knowledge in their respective domains. </p> About the Author Dr. Ch. Venkateswarlu, has formerly worked as Scientist, Senior Principal Scientist and Chief Scientist at Indian Institute of Chemical Technology (IICT), Hyderabad, a premier research and development (R&D) institute of Council of Scientific and Industrial Research (CSIR), India. Recently, he retired as the Director R&D at BV Raju Institute of Technology (BVRIT), Narsapur, Greater Hyderabad. Prior to Director R&D at BVRIT, he worked as Professor, Principal and Head of Chemical Engineering Department of the same institute. He did his graduation from Andhra University as well as from Indian Institute of Chemical Engineers, and post-graduation and Ph.D in Chemical Engineering from Osmania University, Hyderabad, India. He holds 35 years R&D and industry experience along with 20 years teaching experience. His research interests lie in the areas of dynamic process modelling & simulation, process identification & dynamic optimization, process monitoring & fault diagnosis, state estimation & soft sensing, statistical process control & advanced process control, applied engineering mathematics & evolutionary computing, artificial intelligence & expert systems, and bioprocess engineering & bio-informatics. He published more than 120 research papers in peer journals of repute along with few international and national proceeding publications. He is also credited with 150 technical paper presentations and invited lectures. He authored a book published by Elsevier along with few book chapters. He is also in editorial boards of few international journals. He has executed several R&D projects sponsored by DST and Industry. He is a reviewer of severa