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Mechatronic Control of Distributed Noise and Vibration: A Lyapunov Approach PDF

219 Pages·2001·5.952 MB·English
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Christopher D. Rahn Mechatronic Control of Distributed Noise and Vibration Springer-Verlag Berlin Beideiberg GmbH ONLINE LIBRARY http://www.springer.de/engine/ Christopher D. Rahn Mechatronic Control of Distributed Noise and Vibration A Lyapunov Approach With 59 Figures ~Springer Associate Professor CHRISTOPHER D. RAHN The Pennsylvania State University Department of Mechanical and Nuclear Engineering 150 A Hammond Building University Park, PA 16802 USA e-mail: [email protected] ISBN 978-3-642-07536-0 ISBN 978-3-662-04641-8 (eBook) DOI 10.1007/978-3-662-04641-8 Cip-data applied for This work is subject to copyright. Ali rights are reserved, whether the whole or part of the material is concerned, specificallythe rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfIlm or in other ways, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag Berlin Heidelberg GmbH. Violations are liable for prosecution act under German Copyright Law. http://www.springer.de © Springer-Verlag Berlin Heidelberg 2001 Originally published by Springer-Verlag Berlin Heidelberg New York in 2001 Softcover reprint of the hardcover 1s t edition 2001 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence ofa specific statement, that such names are exemptfrom the relevant protective laws and regulations and therefore free for general use. Typesetting: Camera ready by authors Cover-Design: design & production, Heidelberg Printed on acid free paper SPIN: 10834053 62/3020/kk -5432 1 O To Matthew, Kevin, and Katelin PREFACE Vibration and noise reduce the perceived quality, productivity, and efficiency of many electromechanical systems. Vibration can cause defects and limit production speeds during manufacturing and produce premature failure of finished products due to fa tigue. Potential contact with a vibrating system or hearing darnage from a noisy machine can produce a dangerous, unhealthy, and uncomfortable operating environ ment. Recent advances in computer technology have allowed the development of so phisticated electromechanical systems for the control of vibration and noise. The demanding specifications of many modern systems require higher performance than possible with the traditional, purely mechanical approaches of increasing system stiff ness or damping. Mechatronic systems that integrate computer software and hard ware with electromechanical sensors and actuators to control complex mechanical systems have been demonstrated to provide outstanding vibration and noise reduc tion. The current trends toward higher speed computation and lower cost, higher performance sensors and actuators indicate the continuing possibilities for this con trol approach in future applications. The software control algorithms that act as the brain of the mechatronic sys tem are based on an accurate model of the system to be controlled. At the scale of most mechanical applications, the material composing the system components acts as a continuum. Components that do not deform appreciably under the applied loading may be approximated as rigid bodies. The remaining, distributed components can be modeled by partial differential equations (PDEs) or approximated by ordinary differential equations ( ODEs) using numerical discretization techniques such as the Finite Element Method (FEM). Discretization may be the only option for distributed components with complex geometry or built-up assemblies. Many manufacturing, aerospace, acoustic, robotic, transportation, and power transmission applications, however, have the geometric simplicity that make PDE models the most accurate and concise representation of the system dynamics. The purpose of this book is to present recent advances in the application of Lyapunov's method for distributed parameter systems to the control of vibration and noise. There have been many notable books on vibration and noise control that use a discrete or modal approach (e.g. [98, 54, 103, 45, 46, 43, 94]). In graduate en gineering textbooks, Inman [54) and Junkins [59) introduce distributed control and Lyapunov theory for distributed systems, respectively. Edited books [125, 23) present VIII contributions to the control of distributed parameter vibration. Much of the mathe matical treatises on distributed parameter or infinite dimensional systems ( e.g. [28]), do not address implementation. The recent book by Luo et al. [78] focuses on semi group theory. In de Queiroz et al. [31], applications of Lyapunov's direct method are presented including distributed parameter systems. Unlike previously published work, this book develops adaptive, output feedback controllers that asymptotically stabilize distributed vibration and noise using few sensors and actuators, compensate for the inertial and electrical actuator dynamics, and learn system parameters such as tension and bending stiffness. Visual feedback control using high speed video, setpoint regulation for systems with rigid body modes, and isolation of bounded dis turbances are also presented. The intended audience for the book includes academic and industrial researchers and graduate and advanced undergraduate students in en gineering and applied mathematics. In addition to being a reference text, the book is sufficiently broad and self-contained to act as a graduate text in vibration and noise control. It includes modeling, simulation, control development, and implementation for distributed vibration and noise problems. After a short introduction in Chapter 1, Chapter 2 demonstrates distributed parameter modeling using Hamilton's Principlc. The equations of motion of second order ( e.g. strings, cables, and acoustic ducts) and fourth order ( e.g. beams and plates) systems are derived. It is shown that the equations of motion for vibration and noise problems can be cast in a matrix operator form with the operators having special properties. Exact solution of the open and closed loop equations of motion using modal analysis is demonstrated. Galerkin's method is used for time simulation of systems with nonuniform parameter distributions and/or damping. Chapter 3 introduces the mathematical tools needed for the application of Lya punov's method to distributed parameter systems. Pointwise and L2 boundedness, asymptotic stability, and exponential stability are defined. Key inequalities are intro duced that aid in the bounding of Lyapunov functionals and their time derivatives. Lyapunov's method, Barbalat's lemma, and LaSalle's invariance principle are intro duced as stability proof techniques. The basics of semigroup theory are demonstrated to determine the existence and uniqueness of a semigroup solution. Chapter 4 develops passive controllers for distributed parameter systems. The effects of boundary, distributed, pointwise, and parametric damping are explored. Passive boundary controllers are developed that provide exponential stability despite actuator dynamics. Free boundary problems such as the gantry crane and flexible link robot are studied. Mechatronic implementation experimentally demonstrates the feasibility and performance of the proposed controllers. Chapter 5 develops Exact Model Knowledge (EMK) Controllers for second and fourth order systems. Simple examples of a pinned-controlled string and a clamped controlled beam are used to demonstrate the techniques. Compensation for compli cating effects such as actuator dynamics, nonuniform parameter distributions, and nonlinearities are demonstrated. Complete boundary actuation ( i. e. on all bound- IX aries) allows setpoint regulation of rigid body and vibrational motion. Isolation Con trollers for acoustic noise and axially moving beam models are developed. Visual feedback controllers are derived and tested on a flexible link robot using a high-speed video camera and two computers interfaced via a dedicated TCP /IP connection. Chapter 6 demonstrates how many of the controllers developed in Chapter 5 can be redesigned as adaptive Controllers that compensate for parametric uncertainty. Adaptive boundary controllers for nonlinear and spatially varying systems and isola tion controllers are developed. Mechatronic testbeds are constructed to demonstrated the improved closed loop performance under EMK and adaptive control relative to passive and classical PID approaches. I would like to thank my former colleagues and students in the Robotics and Mechatronics Labaratory at Clemson University for their contributions to this book. I was fortunate to have worked with Professor Darren Dawson in the Electrical and Computer Engineering Department without whom many of the approaches presented in this book would never have been developed. My former students, Catalin Baicu, Huseyin Canbolat, Fumin Zhang, Siddhartha Nagarkatti, Yugang Li, Aniket Malat pure, Sushil Singh, and Dan Aron, did much of iterative development of Lyapunov fundionals and experimental implementation. I greatly appreciate the review of an early draft of this book by the students in ME 893, Control of Vibration and Noise at Clemson in Spring of 2000. Christopher D. Rahn University Park, PA CONTENTS 1 Introduction 1 2 Distributed Parameter Models 7 201 Harnilton's Principle 0 0 0 0 7 202 Lumped Systems 0 0 0 0 0 0 8 20201 Mechanical Systems 0 8 20202 Electrical Systems 0 9 203 Distributed Systems 0 0 0 0 9 20301 Second Order Systems 10 20302 Fourth Order Systems 16 2.4 Matrix Operator Representation 0 22 2.401 Second Order Systems 23 2.402 Fourth Order Systems 0 0 26 205 Simulation 0 0 0 0 0 0 0 0 0 0 0 0 0 28 20501 Exact Modal Analysis for Undamped Systems 28 20502 Approximate Simulation - Galerkin's Method 35 3 Mathematical Preliminaries 43 301 Definitions 0 0 0 0 0 0 0 0 0 43 302 Inequalities 0 0 0 0 0 0 0 0 0 0 0 0 0 44 303 Existence of a Sernigroup Solution 0 47 30301 Axially Moving String 48 30302 Gantry Crane 0 0 0 0 0 0 0 0 50 3.4 Stability Theorems 0 0 0 0 0 0 0 0 0 53 30401 Lyapunov's Direct Method 0 53 3.402 Barbalat's Lemma 0 0 0 0 0 53 3.403 LaSalle's Invariance Principle 54 4 Passive Control 55 401 Damping 0 0 0 0 0 0 0 0 0 0 0 0 55 401.1 Boundary Damping 0 0 55 401.2 Distributed Damping 0 66 401.3 Pointwise Damping 0 0 73 XII CONTENTS 4.1.4 Parametrie Damping .... 75 4.2 Passive Boundary Control . . . . . 77 4.2.1 Boundary Controlled String 77 4.3 Free Boundary Problems . . 84 4.3.1 Gantry Crane .... 84 4.3.2 Flexible Link Robot 88 5 Exact Model Knowledge Control 91 5.1 Boundary Control . . . . . . . 91 5.1.1 Seeond Order Systems . . 91 5.1.2 Fourth Order Systems . . 97 5.1.3 Baekstepping Compensation for Aetuator Dynamies . 102 5.1.4 Compensation for Geometrie and Material Nonlinearities 106 5.1.5 Effeets of Nonuniform Parameter Distributions . 118 5.1.6 Rigid Body Setpoint Regulation 123 5.2 Domain Control . . . . . . . . . . . . 137 5.2.1 Aeoustie Noise Isolator . . . . . 137 5.2.2 Axially Moving Beam Isolator . 144 5.3 Modal Control using Distributed Sensing 150 5.3.1 Mathematieal Model . . 150 5.3.2 Control Design . . . . . . 151 5.3.3 Residual Mode Stability . 153 5.3.4 Flexible Link Robot Arm. 155 6 Adaptive Control 165 6.1 Boundary Control . . . . . . . 165 6.1.1 Seeond Order Systems 165 6.1. 2 Fourth Order Systems 171 6.1.3 Compensation for Geometrie and Material Nonlinearities 176 6.1.4 Effeets of Nonuniform Parameter Distributions . 180 6.2 Domain Control . . . . . . . . . . . . 184 6.2.1 Aeoustie Noise Isolator . . . . 184 6.2.2 Axially Moving Beam Isolator 189 7 Bibliography 203

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