Secure CheckoutPersonal information is secured with SSL technology.
Free ShippingFree global shipping
No minimum order.
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 concept is introduced and extended for TDOF control loops. The Keviczky-Banyasz parameterization (KP) method developed for closed loop systems is also presented. The book is valuable for those who want to see through the jungle of available methods by using a unified approach, and for those who want to prepare computer code with a given algorithm.
- Provides comprehensive coverage of the most widely used control system methodologies
- The first book to use the Youla parameterization (YP) as a common base for comparison and algorithm development
- Compares YP and Keviczky-Banyasz (KB) parameterization to help you write your own computer algorithms
Researchers; professionals, and PhD students working in the controls area
- Dedication 2
- 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 Regulator
- Pole 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 Regulator
- Second-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 “Naïve” Process Model
- Control of Inverse Stable MIMO Process Models
- Decoupling Control of MIMO Process Models
- Decoupling Control Using Youla-Parameterized MIMO Regulators
- Decoupling 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 Identification
- Types 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
- Appendix 2. State-Space Methods
- Appendix 3. Sampled Data Systems
- Appendix 4. Optimization Problems
- Appendix 5. Norms of Signals and Operators
- Appendix 6. Derivations of Process Identification Methods
- Author Index
- Subject Index
- No. of pages:
- © Academic Press 2015
- 18th June 2015
- Academic Press
- Paperback ISBN:
- eBook ISBN:
Professor Keviczky has a PhD in design of regression experiments and a Doctor of Sciences Degree from the Hungarian Academy of Sciences (HAS). He was the founding member of the Hungarian Academy of Engineering and was appointed as a Foreign Member of the Royal Swedish Academy of Engineering Sciences.
He was Director of the Computer and Automation Research Institute (CARI) from 1986-1993 and is still a Research Professor there and a Director at the Multidisciplinary Doctoral School at Széchenyi István University, Gyôr.
He has worked with IFAC in various positions since 1981 and was Associate Editor of IFAC’s Journal Automatica for six years. He was also General Chair of ECC’2009 and the president of the European Union Control Association (EUCA) from 2010-2012.
Keviczky was the founding member of the Steering Committee of the COSY European Science Foundation project and initiated the launch of the EU project DYCOMANS.
He has written c-400 papers and has c-701 citations, placing him as the number one expert in this area in Hungary.
Computer and Automation Research Institute, Hungarian Academy of Sciences, Hungary.
Dr Banyask is currently a senior research scientist at CARI where she has worked since 1969. She has a Doctor of Technical university degree and a Candidate of Technical Sciences degree.
During her career she has been awarded the Frigyes Csáki Medal, the István Kruspér Medal, the Outstanding institutional service award (3 times), CARI, and the Knights’s Cross of the Order of Merit of the Republic of Hungary.
She has written c-180 papers and has 118 citations.
Computer and Automation Research Institute, Hungarian Academy of Sciences, H-1518 Budapest, Kende u 13-17, Hungary
Elsevier.com visitor survey
We are always looking for ways to improve customer experience on Elsevier.com.
We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.
If you decide to participate, a new browser tab will open so you can complete the survey after you have completed your visit to this website.
Thanks in advance for your time.