This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets.

Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.

Acerca del autor

Dr. R�mulo Ant�o (R�mulo Jos� Magalh�es Martins Ant�o) received M.Sc. degree in Electronics and Telecommunications Engineering, and Ph.D. degree in Electrotechnical Engineering from the University of Aveiro, Portugal, in 2010 and 2016, respectively. Currently, he works in Modeling and Control domains as a Post-Doctoral researcher at Aveiro University, and working simultaneously as Power Electronics Engineer in Industry. His research areas of interest are system modelling, adaptive control theory, power electronics and embedded systems applied to DC-DC Converters and Motion Control. Prof. Alexandre Mota (Alexandre Manuel Moutela Nunes da Mota) is Associate Professor at the University of Aveiro, Portugal. Prof. Rui Escadas Martins (Rui Manuel Escadas Ramos Martins) is Assistant Professor at the University of Aveiro, Portugal. Prof. J. Tenreiro Machado (Jos� Ant�nio Tenreiro Machado) is Principal Coordinator Professor at the Institute of Engineering, Polytechnic Institute of Porto, Portugal.

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