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© 2017

Type-2 Fuzzy Logic

Uncertain Systems’ Modeling and Control

  • Presents a simple and didactic introduction to the principles of Type-2 Fuzzy Logic and extends them to state-of-the art methods in model-based control techniques

  • Uses application scenarios based on process control engineering domains, which are commonly used as a benchmark in the literature, providing a comparative standpoint to other control algorithm’s implementations

  • Provides an open-source software framework where the algorithms used in the book are available, written for Matlab/Simulink and in C Language for embedded systems

Book

Part of the Nonlinear Physical Science book series (NPS)

Table of contents

  1. Front Matter
    Pages i-x
  2. Rómulo Antão, Alexandre Mota, Rui Escadas Martins, José Tenreiro Machado
    Pages 1-5
  3. Rómulo Antão, Alexandre Mota, Rui Escadas Martins, José Tenreiro Machado
    Pages 7-34
  4. Rómulo Antão, Alexandre Mota, Rui Escadas Martins, José Tenreiro Machado
    Pages 35-57
  5. Rómulo Antão, Alexandre Mota, Rui Escadas Martins, José Tenreiro Machado
    Pages 59-79
  6. Rómulo Antão, Alexandre Mota, Rui Escadas Martins, José Tenreiro Machado
    Pages 81-110
  7. Rómulo Antão, Alexandre Mota, Rui Escadas Martins, José Tenreiro Machado
    Pages 111-124
  8. Rómulo Antão, Alexandre Mota, Rui Escadas Martins, José Tenreiro Machado
    Pages 125-127
  9. Back Matter
    Pages 129-130

About this book

Introduction

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.

Keywords

Model Predictive Control System Modeling Takagi-Sugeno Fuzzy Logic Systems Generalized Predictive Control principles Fuzzy Logic

Authors and affiliations

  1. 1.Department of Electronics, Telecommunications and InformaticsUniversity of Aveiro, Department of Electronics, Telecommunications and InformaticsAvieroPortugal

About the authors

Dr. Rómulo Antão (Rómulo José Magalhães Martins Antão) 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 (José António Tenreiro Machado) is Principal Coordinator Professor at the Institute of Engineering, Polytechnic Institute of Porto, Portugal.

Bibliographic information

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