1 Introduction. - 1. 1 Fuzzy Modeling with the Use of Prior Knowledge. - 1. 2 Fuzzy model-based Control. - 1. 3 Illustrative Examples. - 1. 4 Summary. - 2 Fuzzy Model Structures and their Analysis. - 2. 1 Introduction to Fuzzy Modeling. - 2. 2 Takagi-Sugeno Fuzzy Models (TS). - 2. 3 Fuzzy Models with Multivariate Membership Functions (MMF). - 2. 4 Input Reduction of Fuzzy Models. - 2. 5 Fuzzy Model Inversion. - 2. 6 Linearization and Derivatives of Fuzzy Models. - 3 Fuzzy Models of Dynamical Systems. - 3. 1 Data-Driven Empirical Modeling. - 3. 2 TS Fuzzy Models of Dynamical Systems. - 3. 3 TS Fuzzy Models of MIMO Systems. - 3. 4 Hybrid Fuzzy Convolution Model (HFCM). - 3. 5 Fuzzy Hammerstein Model (FH). - 4 Fuzzy Model Identification. - 4. 1 Identification as an Optimization Problem. - 4. 2 Consequent Parameter Identification. - 4. 3 Model Structure Identification. - 4. 4 Antecedent Membership Function Identification. - 4. 5 MMF Fuzzy Model Identification. - 4. 6 Hybrid Fuzzy Convolution Model Identification. - 4. 7 Fuzzy Hammerstein Model Identification. - 5 Fuzzy Model based Control. - 5. 1 Introduction to Fuzzy Control. - 5. 2 Inverse Fuzzy Model based (Adaptive) Control. - 5. 3 Introduction to Model Predictive Control. - 5. 4 TS Fuzzy Model based Predictive Control. - 5. 5 MIMO Fuzzy model based Predictive Control. - 5. 6 HFCM based Predictor Corrector Controller. - 5. 7 HFCM based Predictive Control. - 5. 8 Fuzzy Hammerstein Model based Predictive Control. - 5. 9 Grey-Box TS Fuzzy Model based Adaptive Control. - A Process Models Used for Case Studies. - A. l Model of the pH Process. - A. 2 Electrical Water-Heater. - A. 3 Distillation Column. - A. 4 Model of the liquid level rig. - References. Language: English