Author: Jie Chen
Publisher: Wiley-Interscience
ISBN:
Category : Science
Languages : en
Pages : 458
Book Description
This volume covers system identification. Identification, in the language of control theory, is the process of obtaining a model of the object or process being controlled.
Control-Oriented System Identification
Author: Jie Chen
Publisher: Wiley-Interscience
ISBN:
Category : Science
Languages : en
Pages : 458
Book Description
This volume covers system identification. Identification, in the language of control theory, is the process of obtaining a model of the object or process being controlled.
Publisher: Wiley-Interscience
ISBN:
Category : Science
Languages : en
Pages : 458
Book Description
This volume covers system identification. Identification, in the language of control theory, is the process of obtaining a model of the object or process being controlled.
Robust Control-Oriented Linear Fractional Transform Modelling
Author: Tamal Roy
Publisher: Springer Nature
ISBN: 9811974624
Category : Technology & Engineering
Languages : en
Pages : 166
Book Description
This book covers a new paradigm of system modeling – the robust control-oriented linear fractional transformation (LFT) modeling. A dynamic system expressed in LFT modeling framework paves the way for the application of modern robust controller design technique like μ-synthesis method for controller design. This book covers the generalized robust control-oriented LFT modeling representation of the MIMO system depending upon the uncertainty structure, system dynamics, and the dimensions of the input–output. The modeling framework results into a compact and manageable representation of uncertainty modeling in the form of feedback-like structure that is suitable for design and implementation of the robust control technique like μ-synthesis-based H∞ control theory. This book also describes the application of the proposed methodology in a variety of advanced mechatronic systems like the Twin Rotor MIMO system, wheeled mobile robot, and an industrial robot arm.
Publisher: Springer Nature
ISBN: 9811974624
Category : Technology & Engineering
Languages : en
Pages : 166
Book Description
This book covers a new paradigm of system modeling – the robust control-oriented linear fractional transformation (LFT) modeling. A dynamic system expressed in LFT modeling framework paves the way for the application of modern robust controller design technique like μ-synthesis method for controller design. This book covers the generalized robust control-oriented LFT modeling representation of the MIMO system depending upon the uncertainty structure, system dynamics, and the dimensions of the input–output. The modeling framework results into a compact and manageable representation of uncertainty modeling in the form of feedback-like structure that is suitable for design and implementation of the robust control technique like μ-synthesis-based H∞ control theory. This book also describes the application of the proposed methodology in a variety of advanced mechatronic systems like the Twin Rotor MIMO system, wheeled mobile robot, and an industrial robot arm.
Industrial Process Identification and Control Design
Author: Tao Liu
Publisher: Springer Science & Business Media
ISBN: 0857299778
Category : Technology & Engineering
Languages : en
Pages : 487
Book Description
Industrial Process Identification and Control Design is devoted to advanced identification and control methods for the operation of continuous-time processes both with and without time delay, in industrial and chemical engineering practice. The simple and practical step- or relay-feedback test is employed when applying the proposed identification techniques, which are classified in terms of common industrial process type: open-loop stable; integrating; and unstable, respectively. Correspondingly, control system design and tuning models that follow are presented for single-input-single-output processes. Furthermore, new two-degree-of-freedom control strategies and cascade control system design methods are explored with reference to independently-improving, set-point tracking and load disturbance rejection. Decoupling, multi-loop, and decentralized control techniques for the operation of multiple-input-multiple-output processes are also detailed. Perfect tracking of a desire output trajectory is realized using iterative learning control in uncertain industrial batch processes. All the proposed methods are presented in an easy-to-follow style, illustrated by examples and practical applications. This book will be valuable for researchers in system identification and control theory, and will also be of interest to graduate control students from process, chemical, and electrical engineering backgrounds and to practising control engineers in the process industry.
Publisher: Springer Science & Business Media
ISBN: 0857299778
Category : Technology & Engineering
Languages : en
Pages : 487
Book Description
Industrial Process Identification and Control Design is devoted to advanced identification and control methods for the operation of continuous-time processes both with and without time delay, in industrial and chemical engineering practice. The simple and practical step- or relay-feedback test is employed when applying the proposed identification techniques, which are classified in terms of common industrial process type: open-loop stable; integrating; and unstable, respectively. Correspondingly, control system design and tuning models that follow are presented for single-input-single-output processes. Furthermore, new two-degree-of-freedom control strategies and cascade control system design methods are explored with reference to independently-improving, set-point tracking and load disturbance rejection. Decoupling, multi-loop, and decentralized control techniques for the operation of multiple-input-multiple-output processes are also detailed. Perfect tracking of a desire output trajectory is realized using iterative learning control in uncertain industrial batch processes. All the proposed methods are presented in an easy-to-follow style, illustrated by examples and practical applications. This book will be valuable for researchers in system identification and control theory, and will also be of interest to graduate control students from process, chemical, and electrical engineering backgrounds and to practising control engineers in the process industry.
Iterative Identification and Control
Author: P. Albertos Pérez
Publisher: Springer Science & Business Media
ISBN: 9781852335090
Category : Computers
Languages : en
Pages : 332
Book Description
An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.
Publisher: Springer Science & Business Media
ISBN: 9781852335090
Category : Computers
Languages : en
Pages : 332
Book Description
An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.
Iterative Identification and Control
Author: Pedro Albertos
Publisher: Springer Science & Business Media
ISBN: 1447102053
Category : Computers
Languages : en
Pages : 320
Book Description
An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.
Publisher: Springer Science & Business Media
ISBN: 1447102053
Category : Computers
Languages : en
Pages : 320
Book Description
An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.
Modelling and Identification with Rational Orthogonal Basis Functions
Author: Peter S.C. Heuberger
Publisher: Springer Science & Business Media
ISBN: 1846281784
Category : Technology & Engineering
Languages : en
Pages : 415
Book Description
Models of dynamical systems are of great importance in almost all fields of science and engineering and specifically in control, signal processing and information science. A model is always only an approximation of a real phenomenon so that having an approximation theory which allows for the analysis of model quality is a substantial concern. The use of rational orthogonal basis functions to represent dynamical systems and stochastic signals can provide such a theory and underpin advanced analysis and efficient modelling. It also has the potential to extend beyond these areas to deal with many problems in circuit theory, telecommunications, systems, control theory and signal processing. Modelling and Identification with Rational Orthogonal Basis Functions affords a self-contained description of the development of the field over the last 15 years, furnishing researchers and practising engineers working with dynamical systems and stochastic processes with a standard reference work.
Publisher: Springer Science & Business Media
ISBN: 1846281784
Category : Technology & Engineering
Languages : en
Pages : 415
Book Description
Models of dynamical systems are of great importance in almost all fields of science and engineering and specifically in control, signal processing and information science. A model is always only an approximation of a real phenomenon so that having an approximation theory which allows for the analysis of model quality is a substantial concern. The use of rational orthogonal basis functions to represent dynamical systems and stochastic signals can provide such a theory and underpin advanced analysis and efficient modelling. It also has the potential to extend beyond these areas to deal with many problems in circuit theory, telecommunications, systems, control theory and signal processing. Modelling and Identification with Rational Orthogonal Basis Functions affords a self-contained description of the development of the field over the last 15 years, furnishing researchers and practising engineers working with dynamical systems and stochastic processes with a standard reference work.
Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019)
Author: Rui Wang
Publisher: Springer Nature
ISBN: 9811504741
Category : Technology & Engineering
Languages : en
Pages : 1340
Book Description
This book includes original, peer-reviewed research papers from the 11th International Conference on Modelling, Identification and Control (ICMIC2019), held in Tianjin, China on July 13-15, 2019. The topics covered include but are not limited to: System Identification, Linear/Nonlinear Control Systems, Data-driven Modelling and Control, Process Modelling and Process Control, Fault Diagnosis and Reliable Control, Intelligent Systems, and Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
Publisher: Springer Nature
ISBN: 9811504741
Category : Technology & Engineering
Languages : en
Pages : 1340
Book Description
This book includes original, peer-reviewed research papers from the 11th International Conference on Modelling, Identification and Control (ICMIC2019), held in Tianjin, China on July 13-15, 2019. The topics covered include but are not limited to: System Identification, Linear/Nonlinear Control Systems, Data-driven Modelling and Control, Process Modelling and Process Control, Fault Diagnosis and Reliable Control, Intelligent Systems, and Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.
Model-based Nonlinear Control of Aeroengines
Author: Jiqiang Wang
Publisher: Springer Nature
ISBN: 9811644535
Category : Technology & Engineering
Languages : en
Pages : 255
Book Description
This book aims to develop systematic design methodologies to model-based nonlinear control of aeroengines, focusing on (1) modelling of aeroengine systems—both component-level and identification-based models will be extensively studied and compared; and (2) advanced nonlinear control designs—set-point control, transient control and limit-protection control approaches will all be investigated. The model-based design has been one of the pivotal technologies to advanced control and health management of propulsion systems. It can fulfil advanced designs such as fault-tolerant control, engine modes control and direct thrust control. As a consequence, model-based design has become an important research area in the field of aeroengines due to its theoretical interests and engineering significance. One of the central issues in model-based controls is the tackling of nonlinearities. There are publications concerning with either nonlinear modelling or nonlinear controls; yet, they are scattered throughout the literature. It is time to provide a comprehensive summary of model-based nonlinear controls. Consequently, a series of important results are obtained and a systematic design methodology is developed which provides consistently enhanced performance over a large flight/operational envelope, and it is thus expected to provide useful guidance to practical engineering in aeroengine industry and research.
Publisher: Springer Nature
ISBN: 9811644535
Category : Technology & Engineering
Languages : en
Pages : 255
Book Description
This book aims to develop systematic design methodologies to model-based nonlinear control of aeroengines, focusing on (1) modelling of aeroengine systems—both component-level and identification-based models will be extensively studied and compared; and (2) advanced nonlinear control designs—set-point control, transient control and limit-protection control approaches will all be investigated. The model-based design has been one of the pivotal technologies to advanced control and health management of propulsion systems. It can fulfil advanced designs such as fault-tolerant control, engine modes control and direct thrust control. As a consequence, model-based design has become an important research area in the field of aeroengines due to its theoretical interests and engineering significance. One of the central issues in model-based controls is the tackling of nonlinearities. There are publications concerning with either nonlinear modelling or nonlinear controls; yet, they are scattered throughout the literature. It is time to provide a comprehensive summary of model-based nonlinear controls. Consequently, a series of important results are obtained and a systematic design methodology is developed which provides consistently enhanced performance over a large flight/operational envelope, and it is thus expected to provide useful guidance to practical engineering in aeroengine industry and research.
Identification for Automotive Systems
Author: Daniel Alberer
Publisher: Springer
ISBN: 1447122216
Category : Technology & Engineering
Languages : en
Pages : 359
Book Description
Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.
Publisher: Springer
ISBN: 1447122216
Category : Technology & Engineering
Languages : en
Pages : 359
Book Description
Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.
Data Driven Model Learning for Engineers
Author: Guillaume Mercère
Publisher: Springer Nature
ISBN: 3031316363
Category : Mathematics
Languages : en
Pages : 218
Book Description
The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail. As applications of data-driven model learning become widespread in society, engineers need to understand its underlying principles, then the skills to develop and use the resulting data-driven model learning solutions. After reading this book, the users will have acquired the background, the knowledge and confidence to (i) read other model learning textbooks more easily, (ii) use linear algebra and statistics for data analysis and modeling, (iii) explore other fields of applications where model learning from data plays a central role. Thanks to numerous illustrations and simulations, this textbook will appeal to undergraduate and graduate students who need a first course in data-driven model learning. It will also be useful for practitioners, thanks to the introduction of easy-to-implement recipes dedicated to stationary time series model learning. Only a basic familiarity with advanced calculus, linear algebra and statistics is assumed, making the material accessible to students at the advanced undergraduate level.
Publisher: Springer Nature
ISBN: 3031316363
Category : Mathematics
Languages : en
Pages : 218
Book Description
The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail. As applications of data-driven model learning become widespread in society, engineers need to understand its underlying principles, then the skills to develop and use the resulting data-driven model learning solutions. After reading this book, the users will have acquired the background, the knowledge and confidence to (i) read other model learning textbooks more easily, (ii) use linear algebra and statistics for data analysis and modeling, (iii) explore other fields of applications where model learning from data plays a central role. Thanks to numerous illustrations and simulations, this textbook will appeal to undergraduate and graduate students who need a first course in data-driven model learning. It will also be useful for practitioners, thanks to the introduction of easy-to-implement recipes dedicated to stationary time series model learning. Only a basic familiarity with advanced calculus, linear algebra and statistics is assumed, making the material accessible to students at the advanced undergraduate level.