Two-degree-of-freedom control systems : the Youla Parameterization approach /

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This book covers the most important issues from classical and robust control, deterministic and stochastic control, system identification, and adaptive and iterative control strategies. It covers most of the known control system methodologies using a new base, the Youla parameterization (YP). This c...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Keviczky, László (Autor), Bányász, Csilla (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Academic Press, [2015]
Edición:First edition.
Temas:
Feedback control systems.
Automatic control.
Automatic control > Mathematical models.
Systèmes à réaction.
Commande automatique.
Commande automatique > Modèles mathématiques.
TECHNOLOGY & ENGINEERING > Engineering (General)
Automatic control
Automatic control > Mathematical models
Feedback control systems
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover; TWO-DEGREE-OF-FREEDOM CONTROL SYSTEMS; Copyright; DEDICATION; THE BEST STUDENTS; THE CLOSEST COWORKERS; NOTATION; ABBREVIATIONS; CONTENTS; PREFACE; Chapter 1
  • Introduction; 1.1 PROCESS MODELS; 1.2 CLOSED-LOOP CONTROL; 1.3 STABILITY OF THE CLOSED-LOOP CONTROL; 1.4 PARAMETERIZATION OF THE CLOSED-LOOP CONTROL; Chapter 2
  • Control of Stable Processes; 2.1 REGULATORS BASED ON YP; 2.2 OTHER CLASSICAL PARAMETERIZED REGULATORS; 2.3 DEADBEAT REGULATORS; 2.4 PREDICTIVE REGULATORS; Chapter 3
  • Feedback Regulators; POLE PLACEMENT WITH POLE CANCELLATION.
  • POLE PLACEMENT WITH FEEDBACK REGULATORPOLE PLACEMENT WITH CHARACTERISTIC POLYNOMIAL DESIGN; 3.1 CONTROL LOOPS WITH STATE FEEDBACK; 3.2 STATE FEEDBACK LINEAR QUADRATIC (LQ) REGULATORS; 3.3 GENERAL POLYNOMIAL METHOD FOR REGULATOR DESIGN; Chapter 4
  • Concept of the Best Achievable Control; DECOMPOSITION OF SENSITIVITY FUNCTION; DECOMPOSITION OF SENSITIVITY FUNCTION FOR YP REGULATORS; DIRECT OPTIMIZATION OF SENSITIVITY FUNCTION; SPECIAL METHODS; EMPIRICAL RELATIONSHIPS; 4.1 OPTIMIZATION OF DESIGN LOSS; 4.2 OPTIMIZATION OF REALIZABILITY LOSS; 4.3 OPTIMIZATION OF MODELING LOSS.
  • Chapter 5
  • Conventional PID RegulatorSECOND-ORDER CT PROCESS WITH DEAD-TIME; OBSERVER-BASED PID REGULATOR; Chapter 6
  • Control of Stochastic Processes; MINIMUM VARIANCE (MV) REGULATOR; GENERALIZED MINIMUM VARIANCE REGULATOR; PREDICTION OF DETERMINISTIC SIGNALS; PREDICTION OF STOCHASTIC SIGNALS; Chapter 7
  • Control of Multivariable Processes; YOULA-PARAMETERIZED MIMO CLOSED-LOOP CONTROL; YOULA-PARAMETERIZED MIMO REGULATOR FOR THE ``NAIVE'' PROCESS MODEL; CONTROL OF INVERSE STABLE MIMO PROCESS MODELS; DECOUPLING CONTROL OF MIMO PROCESS MODELS.
  • DECOUPLING CONTROL USING YOULA-PARAMETERIZED MIMO REGULATORSDECOUPLING EXAMPLES; MIMO PROCESS MODELS LINEAR IN PARAMETER MATRICES; MIMO PREDICTIVE REGULATORS; MIMO MINIMUM VARIANCE (MV) REGULATOR; Chapter 8
  • Control of Nonlinear Cascade Processes; SIMPLE NONLINEAR CASCADE MODELS; NONLINEAR PROPORTIONAL-INTEGRAL-DERIVATIVE (PID) REGULATOR FOR NONLINEAR CASCADE MODELS; Chapter 9
  • Robust Control; 9.1 ROBUSTNESS OF YOULA-PARAMETERIZED REGULATOR; 9.2 LIMITS OF REGULATOR ROBUSTNESS; 9.3 GAP METRICS; 9.4 DIALECTIC BETWEEN PERFORMANCE AND ROBUSTNESS; 9.5 PRODUCT INEQUALITIES.
  • Chapter 10
  • Process IdentificationTYPES OF MODELS; MODEL VALIDATION; PARAMETER ESTIMATION; 10.1 OFF-LINE PROCESS IDENTIFICATION METHODS; 10.2 RECURSIVE PROCESS IDENTIFICATION METHODS; 10.3 PROCESS IDENTIFICATION IN CLOSED-LOOP CONTROL; Chapter 11
  • Adaptive Regulators and Iterative Tuning; 11.1 ALGORITHMS OF ADAPTIVE LEARNING METHODS; 11.2 ITERATIVE METHODS: SIMULTANEOUS IDENTIFICATION AND CONTROL; 11.3 TRIPLE CONTROL; Appendix 1
  • Mathematical Summary; A.1.1 SOME BASIC THEOREMS OF MATRIX ALGEBRA; A.1.2 FOUNDATIONS OF VECTOR ANALYSIS; A.1.3 KRONECKER PRODUCT OF MATRICES.

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