Zongli Lin – författare

Structural properties play an important role in our understanding of linear systems in the state space representation. The structural canonical form representation of linear systems not only reveals the structural properties but also facilitates the design of feedback laws that meet various control objectives. In particular, it decomposes the system into various subsystems. These subsystems, along with the interconnections that exist among them, clearly show the structural properties of the system. The simplicity of the subsystems and their explicit interconnections with each other lead us to a deeper insight into how feedback control would take effect on the system, and thus to the explicit construction of feedback laws that meet our design specifications. The discovery of structural canonical forms and their applications in feedback design for various performance specifications has been an active area of research for a long time. The effectiveness of the structural decomposition approach has also been extensively explored in nonlinear systems and control theory in the recent past. The aim of this book is to systematically present various canonical represen­ tations of the linear system, that explicitly reveal different structural properties of the system, and to report on some recent developments on its utilization in sys­ tem analysis and design.

Saturation nonlinearities are ubiquitous in engineering systems. In control systems, every physical actuator or sensor is subject to saturation owing to its maximum and minimum limits. A digital filter is subject to saturation if it is implemented in a finite word length format. Saturation nonlinearities are also purposely introduced into engineering systems such as control sys­ tems and neural network systems. Regardless of how saturation arises, the analysis and design of a system that contains saturation nonlinearities is an important problem. Not only is this problem theoretically challenging, but it is also practically imperative. This book intends to study control systems with actuator saturation in a systematic way. It will also present some related results on systems with state saturation or sensor saturation. Roughly speaking, there are two strategies for dealing with actuator sat­ uration. The first strategy is to neglect the saturation in the first stage of the control design process, and then to add some problem-specific schemes to deal with the adverse effects caused by saturation. These schemes, known as anti-windup schemes, are typically introduced using ad hoc modifications and extensive simulations. The basic idea behind these schemes is to intro­ duce additional feedbacks in such a way that the actuator stays properly within its limits. Most of these schemes lead to improved performance but poorly understood stability properties.

Surge Control of Active-magnetic-bearing-suspended Centrifugal Compressors sets out the fundamentals of integrating active magnetic bearing (AMB) rotor suspension technology in compressor systems, and describes how this relatively new bearing technology can be employed in active control of compressor surge initiation. The authors provide a self-contained and comprehensive review of rotordynamics and the fundamentals of AMB technology. The active stabilization of compressor surge employing AMBs in a machine is fully explored, from modeling of instability and controller design, to the implementation and experimental testing of the control algorithm in a specially-constructed, industrial-size centrifugal compression system. The results of these tests demonstrate the great potential of the new surge control method suggested in this text. This book will be useful for engineers in industries that involve turbocompressors and magnetic bearings, as well as for researchers and graduate students in the field of applied control. Whatever their level of experience, engineers working in the fields of turbomachinery, magnetic bearings, rotordynamics and controls will find the material in this book  absorbing as all these important aspects of engineering are integrated to create a multi-disciplinary solution to a real-life industrial problem and the book is a suitable introduction to the area for newcomers.

Surge Control of Active-magnetic-bearing-suspended Centrifugal Compressors sets out the fundamentals of integrating active magnetic bearing (AMB) rotor suspension technology in compressor systems, and describes how this relatively new bearing technology can be employed in active control of compressor surge initiation. The authors provide a self-contained and comprehensive review of rotordynamics and the fundamentals of AMB technology. The active stabilization of compressor surge employing AMBs in a machine is fully explored, from modeling of instability and controller design, to the implementation and experimental testing of the control algorithm in a specially-constructed, industrial-size centrifugal compression system. The results of these tests demonstrate the great potential of the new surge control method suggested in this text. This book will be useful for engineers in industries that involve turbocompressors and magnetic bearings, as well as for researchers and graduate students in the field of applied control. Whatever their level of experience, engineers working in the fields of turbomachinery, magnetic bearings, rotordynamics and controls will find the material in this book  absorbing as all these important aspects of engineering are integrated to create a multi-disciplinary solution to a real-life industrial problem and the book is a suitable introduction to the area for newcomers.

Surge Control of Active-magnetic-bearing-suspended Centrifugal Compressors sets out the fundamentals of integrating active magnetic bearing (AMB) rotor suspension technology in compressor systems, and describes how this relatively new bearing technology can be employed in active control of compressor surge initiation. The authors provide a self-contained and comprehensive review of rotordynamics and the fundamentals of AMB technology. The active stabilization of compressor surge employing AMBs in a machine is fully explored, from modeling of instability and controller design, to the implementation and experimental testing of the control algorithm in a specially-constructed, industrial-size centrifugal compression system. The results of these tests demonstrate the great potential of the new surge control method suggested in this text. This book will be useful for engineers in industries that involve turbocompressors and magnetic bearings, as well as for researchers and graduate students in the field of applied control. Whatever their level of experience, engineers working in the fields of turbomachinery, magnetic bearings, rotordynamics and controls will find the material in this book  absorbing as all these important aspects of engineering are integrated to create a multi-disciplinary solution to a real-life industrial problem and the book is a suitable introduction to the area for newcomers.

Saturation nonlinearities are ubiquitous in engineering systems. In control systems, every physical actuator or sensor is subject to saturation owing to its maximum and minimum limits. A digital filter is subject to saturation if it is implemented in a finite word length format. Saturation nonlinearities are also purposely introduced into engineering systems such as control sys­ tems and neural network systems. Regardless of how saturation arises, the analysis and design of a system that contains saturation nonlinearities is an important problem. Not only is this problem theoretically challenging, but it is also practically imperative. This book intends to study control systems with actuator saturation in a systematic way. It will also present some related results on systems with state saturation or sensor saturation. Roughly speaking, there are two strategies for dealing with actuator sat­ uration. The first strategy is to neglect the saturation in the first stage of the control design process, and then to add some problem-specific schemes to deal with the adverse effects caused by saturation. These schemes, known as anti-windup schemes, are typically introduced using ad hoc modifications and extensive simulations. The basic idea behind these schemes is to intro­ duce additional feedbacks in such a way that the actuator stays properly within its limits. Most of these schemes lead to improved performance but poorly understood stability properties.

Structural properties play an important role in our understanding of linear systems in the state space representation. The structural canonical form representation of linear systems not only reveals the structural properties but also facilitates the design of feedback laws that meet various control objectives. In particular, it decomposes the system into various subsystems. These subsystems, along with the interconnections that exist among them, clearly show the structural properties of the system. The simplicity of the subsystems and their explicit interconnections with each other lead us to a deeper insight into how feedback control would take effect on the system, and thus to the explicit construction of feedback laws that meet our design specifications. The discovery of structural canonical forms and their applications in feedback design for various performance specifications has been an active area of research for a long time. The effectiveness of the structural decomposition approach has also been extensively explored in nonlinear systems and control theory in the recent past. The aim of this book is to systematically present various canonical represen­ tations of the linear system, that explicitly reveal different structural properties of the system, and to report on some recent developments on its utilization in sys­ tem analysis and design.

Saturation nonlinearities are ubiquitous in engineering systems. In control systems, every physical actuator or sensor is subject to saturation owing to its maximum and minimum limits. A digital filter is subject to saturation if it is implemented in a finite word length format. Saturation nonlinearities are also purposely introduced into engineering systems such as control sys­ tems and neural network systems. Regardless of how saturation arises, the analysis and design of a system that contains saturation nonlinearities is an important problem. Not only is this problem theoretically challenging, but it is also practically imperative. This book intends to study control systems with actuator saturation in a systematic way. It will also present some related results on systems with state saturation or sensor saturation. Roughly speaking, there are two strategies for dealing with actuator sat­ uration. The first strategy is to neglect the saturation in the first stage of the control design process, and then to add some problem-specific schemes to deal with the adverse effects caused by saturation. These schemes, known as anti-windup schemes, are typically introduced using ad hoc modifications and extensive simulations. The basic idea behind these schemes is to intro­ duce additional feedbacks in such a way that the actuator stays properly within its limits. Most of these schemes lead to improved performance but poorly understood stability properties.

Structural properties play an important role in our understanding of linear systems in the state space representation. The structural canonical form representation of linear systems not only reveals the structural properties but also facilitates the design of feedback laws that meet various control objectives. In particular, it decomposes the system into various subsystems. These subsystems, along with the interconnections that exist among them, clearly show the structural properties of the system. The simplicity of the subsystems and their explicit interconnections with each other lead us to a deeper insight into how feedback control would take effect on the system, and thus to the explicit construction of feedback laws that meet our design specifications. The discovery of structural canonical forms and their applications in feedback design for various performance specifications has been an active area of research for a long time. The effectiveness of the structural decomposition approach has also been extensively explored in nonlinear systems and control theory in the recent past. The aim of this book is to systematically present various canonical represen­ tations of the linear system, that explicitly reveal different structural properties of the system, and to report on some recent developments on its utilization in sys­ tem analysis and design.

This text gives a unified presentation of low gain and high gain design methodologies. In particular the development of low gain feedback design methodology is discussed. The development of both low and high gain feedback enhances the industrial relevance of modern control theory, by providing solutions to a wide range of problems that are of paramount practical importance. This detailed monograph provides the reader with a comprehensive insight into these problems: research results are examined and solutions to the problems are considered. Compared to that of high gain feedback, the power and significance of low gain feedback is not as widely recognized. The purpose of this monograph is to present some recent developments in low gain feedback, and its applications. Several low gain techniques are examined, including the control of linear systems with saturating actuators, semi-global stabilization of minimum phase input-output linearizable systems and H2 suboptimal control.

This monograph is the first of its kind to present innovative research results on truncated predictor feedback (TPF) designs for general linear systems with input delay. Beginning with a brief review of time delay systems, the first half of the book focuses on TPF with a constant feedback parameter. Both state feedback and output feedback are considered. It is established that TPF achieves stabilization in the presence of an arbitrarily large bounded delay if the open loop system is not exponentially unstable. Examples are presented to illustrate that TPF may fail to stabilize an exponentially unstable system when the delay is sufficiently large. Bounds on the delay are then established under which stabilization can be achieved. The second half of the book explores variations of the TPF laws designed with a non-constant feedback parameter to accommodate unknown delays and improve closed-loop performance. The authors employ a step-by-step approach to presenting the ultimate resulton a completely delay-independent feedback law. Truncated Predictor Based Feedback Designs for Linear Systems with Input Delay will appeal to control engineers, control theorists, and graduate students studying control systems. This volume will also be a valuable resource for engineers and applied mathematicians interested in dynamic systems with time delays.

This monograph is the first of its kind to present innovative research results on truncated predictor feedback (TPF) designs for general linear systems with input delay. Beginning with a brief review of time delay systems, the first half of the book focuses on TPF with a constant feedback parameter. Both state feedback and output feedback are considered. It is established that TPF achieves stabilization in the presence of an arbitrarily large bounded delay if the open loop system is not exponentially unstable. Examples are presented to illustrate that TPF may fail to stabilize an exponentially unstable system when the delay is sufficiently large. Bounds on the delay are then established under which stabilization can be achieved. The second half of the book explores variations of the TPF laws designed with a non-constant feedback parameter to accommodate unknown delays and improve closed-loop performance. The authors employ a step-by-step approach to presenting the ultimate resulton a completely delay-independent feedback law. Truncated Predictor Based Feedback Designs for Linear Systems with Input Delay will appeal to control engineers, control theorists, and graduate students studying control systems. This volume will also be a valuable resource for engineers and applied mathematicians interested in dynamic systems with time delays.

This monograph is the first of its kind to present innovative research results on truncated predictor feedback (TPF) designs for general linear systems with input delay. Beginning with a brief review of time delay systems, the first half of the book focuses on TPF with a constant feedback parameter. Both state feedback and output feedback are considered. It is established that TPF achieves stabilization in the presence of an arbitrarily large bounded delay if the open loop system is not exponentially unstable. Examples are presented to illustrate that TPF may fail to stabilize an exponentially unstable system when the delay is sufficiently large. Bounds on the delay are then established under which stabilization can be achieved. The second half of the book explores variations of the TPF laws designed with a non-constant feedback parameter to accommodate unknown delays and improve closed-loop performance. The authors employ a step-by-step approach to presenting the ultimate resulton a completely delay-independent feedback law. Truncated Predictor Based Feedback Designs for Linear Systems with Input Delay will appeal to control engineers, control theorists, and graduate students studying control systems. This volume will also be a valuable resource for engineers and applied mathematicians interested in dynamic systems with time delays.

This monograph explores the analysis and design of model-free optimal control systems based on reinforcement learning (RL) theory, presenting new methods that overcome recent challenges faced by RL.  New developments in the design of sensor data efficient RL algorithms are demonstrated that not only reduce the requirement of sensors by means of output feedback, but also ensure optimality and stability guarantees.  A variety of practical challenges are considered, including disturbance rejection, control constraints, and communication delays.  Ideas from game theory are incorporated to solve output feedback disturbance rejection problems, and the concepts of low gain feedback control are employed to develop RL controllers that achieve global stability under control constraints.Output Feedback Reinforcement Learning Control for Linear Systems will be a valuable reference for graduate students, control theorists working on optimal control systems, engineers, and applied mathematicians.

This monograph explores the analysis and design of model-free optimal control systems based on reinforcement learning (RL) theory, presenting new methods that overcome recent challenges faced by RL.  New developments in the design of sensor data efficient RL algorithms are demonstrated that not only reduce the requirement of sensors by means of output feedback, but also ensure optimality and stability guarantees.  A variety of practical challenges are considered, including disturbance rejection, control constraints, and communication delays.  Ideas from game theory are incorporated to solve output feedback disturbance rejection problems, and the concepts of low gain feedback control are employed to develop RL controllers that achieve global stability under control constraints.Output Feedback Reinforcement Learning Control for Linear Systems will be a valuable reference for graduate students, control theorists working on optimal control systems, engineers, and applied mathematicians.

This monograph explores the analysis and design of model-free optimal control systems based on reinforcement learning (RL) theory, presenting new methods that overcome recent challenges faced by RL.  New developments in the design of sensor data efficient RL algorithms are demonstrated that not only reduce the requirement of sensors by means of output feedback, but also ensure optimality and stability guarantees.  A variety of practical challenges are considered, including disturbance rejection, control constraints, and communication delays.  Ideas from game theory are incorporated to solve output feedback disturbance rejection problems, and the concepts of low gain feedback control are employed to develop RL controllers that achieve global stability under control constraints.Output Feedback Reinforcement Learning Control for Linear Systems will be a valuable reference for graduate students, control theorists working on optimal control systems, engineers, and applied mathematicians.

This monograph investigates the stability and performance of control systems subject to actuator saturation. It presents new results obtained by both improving the treatment of the saturation function and constructing new Lyapunov functions.  In particular, two improved treatments of the saturation function are described that exploit the intricate structural properties of its traditional convex hull representation.  The authors apply these treatments to the estimation of the domain of attraction and the finite-gain L2 performance by using the quadratic Lyapunov function and the composite quadratic Lyapunov function. Additionally, an algebraic computation method is given for the exact determination of the maximal contractively invariant ellipsoid, a level set of a quadratic Lyapunov function.The authors conclude with a look at some of the problems that can be solved by the methods developed and described throughout the book. Numerous step-by-step descriptions, examples, and simulations are provided to illustrate the effectiveness of their results. Stability and Performance of Control Systems with Actuator Saturation will be an invaluable reference for graduate students, researchers, and practitioners in control engineering and applied mathematics.