Janos Abonyi

Fuzzy Model Identification for Control (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book presents new approaches to the construction of fuzzy models for model-based control. The main methods and techniques are illustrated through simulated examples and real-world applications from chemical and process engineering. Supporting MATLAB and Simulink files--available at www.fmt.vein.hu/softcomp--create a computational platform for exploration and illustration of concepts and algorithms presented in the book. Aimed at researchers, practitioners, and professionals in process control and identification, but also accessible to grad students in electrical, chemical, and process engineering.

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Produktdetails

• Verlag: Birkhäuser Boston
• Seitenzahl: 273
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461200277
• Artikelnr.: 44194376

Inhaltsangabe

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.