Estimation and Control of Markovian Jump Systems: Applications in Industrial Engineering provides a comprehensive exploration of Markovian Jump Systems (MJSs), a unique class of hybrid systems that model dynamic processes exposed to unpredictable variations, such as random failures, environmental disturbances, and subsystem changes. With a focus on systems with deficient transition descriptions, the book bridges the gap between theoretical insights and practical applications, making it an essential tool for tackling complex challenges in industrial and systems engineering.

Packed with innovative methodologies, the book offers readers a deep dive into fixed-order H-infinity filtering, delay-dependent control strategies, and multidimensional filter design for MJSs. It introduces robust approaches to handle uncertain and partially unknown transition rates and probabilities, leveraging advanced techniques such as convex optimization, Lyapunov-Krasovskii functionals, and linearization procedures. Divided into three sections, filtering for continuous- and discrete-time systems, delay-dependent control strategies, and state estimation frameworks for two-dimensional systems, the book is enriched with illustrative examples, detailed analyses, and synthesis techniques, providing practical solutions for real-world engineering challenges.

Tailored for practitioners, researchers, and graduate students in industrial engineering, systems engineering, operations research, and related fields such as electrical, mechanical, aerospace, and computer engineering, the content is particularly valuable for those with a solid background in mathematics, matrix theory, probability, optimization techniques, and control system theory. Whether focused on theoretical exploration or practical applications for MJSs, it offers the tools and insights necessary to deepen expertise in this dynamic and evolving domain.

Yanling Wei is a Full Professor at the School of Automation, Southeast University, Nanjing, China. He earned his Ph.D. in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2014. He has held positions as a Research Fellow and Senior Research Fellow at the Technical University of Berlin, the National University of Singapore, and KU Leuven. Dr. Wei's research focuses on the modeling and analysis of stochastic systems, intelligent decision-making and control, as well as AI-driven fault diagnosis and maintenance. Additionally, he serves as an Associate Editor for several prominent engineering and measurement journals.

Jianbin Qiu is a Full Professor at the School of Astronautics, Harbin Institute of Technology, Harbin, China, and a Fellow of IEEE. He also serves as the chair of the IEEE Industrial Electronics Society Harbin Chapter, China. Prof. Qiu earned his B.Eng. and Ph.D. degrees in Mechanical and Electrical Engineering from the University of Science and Technology of China, Hefei, in 2004 and 2009, respectively, as well as a Ph.D. in Mechatronics Engineering from the City University of Hong Kong in 2009. He previously held a prestigious Alexander von Humboldt Research Fellowship at the Institute for Automatic Control and Complex Systems, University of Duisburg-Essen, Germany. His research focuses on intelligent and hybrid control systems, signal processing, and robotics. In addition to his academic contributions, Prof. Qiu is an Associate Editor for IEEE Transactions on Fuzzy Systems, IEEE Transactions on Cybernetics, and IEEE Transactions on Industrial Informatics.

Wenqiang Ji is currently a Full Professor at the School of Artificial Intelligence, Hebei University of Technology, Tianjin, China. He received his Ph.D. in Control Science and Engineering from the Harbin Institute of Technology (HIT), Harbin, China, in 2019. His research focuses on modeling and control of fuzzy systems, nonlinear systems, sampled-data control and filtering design, robust control, and sliding mode control. Dr. Ji has authored or coauthored over 30 peer-reviewed technical papers, including numerous publications in IEEE Transactions on Intelligent and Nonlinear Control. He also holds an editorial role with another leading journal in the field.