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Showing 1 - 10 of 10 matches in All Departments
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.
Includes MATLAB-based computational and design algorithms utilizing the "Linear Systems Toolkit." All results and case studies presented in both the continuous- and discrete-time settings.
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 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.
Every physical actuator is subject to saturation. When the actuator saturates, the performance of the control system designed will seriously deteriorate. Currently there is a surge of interest in increasing the practical applicability of control theory by incorporating the effect of saturation into the design of a control system. Control Systems with Actuator Saturation: Analysis and Design examines the problem of actuator saturation in depth. The overall approach takes into account the saturation nonlinearities at the outset of the control design. In the case that a control law is designed a priori to meet either the performance or stability requirement, it analyzes the closed-loop system under actuator saturation systematically and redesigns the controller in such a way that the preformance is retained while stability is improved. It also presents some related results on systems with state saturation or sensor saturation. Features and topics: * Results apply to general open-loop systems, including
exponentially unstable ones. Thus, they are widely applicable to
practical systems This book is an excellent resource forprofessionals, researchers, practitioners and graduate students in control, electrical, and mechanical engineering. All scientists and engineers interested in control systems with actuator saturation will find this book an essential resource. Some first--year graduate courses in linear systems and multivariable control or some background in nonlinear control systems would greatly facilitate the reading of this book.
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 result on 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.
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."
Includes MATLAB-based computational and design algorithms utilizing the "Linear Systems Toolkit." All results and case studies presented in both the continuous- and discrete-time settings.
This book gives a unified and unique 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 result on 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.
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