Domanski P. Back to Statistics. Tail-Aware Control Performance Assessment 2025
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2025-03-24 16:11:15 GMT
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Due to the popularity of artificial intelligence today, scientists and practitioners tend to ignore the achievements of statistical methods. This book aims to re-establish statistical methods, especially for control practitioners, for whom the task of assessing control performance is important. The author introduces the elements of statistical theory, including basic statistical concepts and the description of distributions. Extending the most common observations toward the tails and extreme statistics, he demonstrates the robust statistics approach that deals with the tails, followed by the description of methods that can visualize and bring forward statistical properties as long as the derivative issues. By addressing statistical issues of sustainability, extreme statistics, non-Gaussianity, L-moments, tail index and index ratio diagrams, the author aims to change traditional concepts and broaden the scope of available methods. Simulation case studies and real industrial cases are also presented. The book will be of interest to site control engineers and scholars assessing control systems and process performance. About the Author Paweł D. Domański was born in 1967 in Warsaw, Poland. He received the M.S. degree in 1991, the Ph.D. degree in 1996 and the D.Sc. degree in 2018, all in control engineering, from the Warsaw University of Technology. Since 1991 he has been working at the Institute of Control and Computational Engineering, Warsaw University of Technology. Besides scientific research, he has participated in dozens of industrial implementations of Advanced Process Control (APC) and optimisation in power and chemical industries. He is the (co-)author of three books and more than 150 publications. His main research interest is in industrial APC applications, control performance quality assessment and optimization. Currently, his research interest is shifting towards multi-agent modelling in the supply chain management environment

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