神经网络预测控制程序的源代码

详细介绍了状态观测器及其在控制系统中的应用。Observers inControl SystemsA Practical guideGeorge ellisDanaher corporation4ACADEMIC PRESSAn imprint of elsevier ScienceAmsterdam Boston London New York Oxford ParisSan Diego San Francisco Singapore Sydney TokyoThis book is printed on acid-free paper ooCopyright 2002, Elsevier Science (USA)All rightsNo part of this publication may be reproduced or transmitted in any form or by anymeans, electronic or mechanical, including photocopy, recording, or any informationstorage and retrieval system, without permission in writing from the publisher. Requestsfor permission to make copies of any part of the work should be mailed to thefollowing address: Permissions Department, Harcourt, Inc, 6277 Sea Harbor DriveOrlando. Florida. 32887-6777.ACADEMIC PRESSAn imprint of Elsevier Science525 B Street, Suite 1900, San Diego, CA 92101-4495, USAhttp://www.academicpress.comAcademic pr84 Theobalds Road. London WCIX 8RR. UKhttp://www.academicpress.comLibrary of congress control Number: 2002104256International Standard book Number: 0-12-237472-XPrinted in the United States of america020304050607MB987654321TO Lee Ann, my loving wife, and our daughter Gretchen, who makes us both proud.Observers in Control Systems■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■Acknowledgments■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■Safety■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■1 Control Systems and the role of observers■■■■■■■■■■■■■■■■1.1 Overviewaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa1.2 Preview of observers21.3 Summary of the book2 Control-System Background52.1 Control-System Structures52.2 Goals of control systems132.3 Visual Model Simulation Environment2. 4 Software Experiments: Introduction to Visual ModelQ182.5 Exercises393 Review of the Frequency Domain.■■■■■■■■■■■■■■■■■■■■■■■■■■■■■3. 1 Overview of the s-domain413.2 Overview of the z-Domain543.3 The Open-Loop Method593.4 A Zone-Based Tuning Procedure623.5 Exercises664 The Luenberger observer: Correcting SensorProblems674. 1 What Is a luenberger observer?674.2 Experiments 4A-4C: Enhancing Stability with an Observer724.3 Predictor-Corrector Form of the Luenberger Observer774. 4 Filter Form of the luenberger observer. ..................................784.5 Designing a Luenberger observer824.6 Introduction to Tuning an observer compensator9047 Exercises955 The Luenberger Observer and Model Inaccuracy... 975.1 Model Inaccuracy.........….……,975.2 Effects of Model Inaccuracy .............................................1005.3 Experimental Evaluation1025.4 Exercises1146 The Luenberger observer and disturbances1156.1 Disturbances1156.2 Disturbance Response1236.3 Disturbance DecouplingIB..-.81296.4 Exercises1387 Noise in the Luenberger Observer…,,,…,,…,…,1417.1 Noise in Control Systems1417.2 Sensor noise and the luenberger observer1457.3 Noise Sensitivity when Using Disturbance Decoupling1567. 4 Reducing Noise Susceptibility in Observer-Based Systems1617.5 Exercises1708 Using the Luenberger Observer in Motion Control1738.1 The Luenberger observers in motion Systems1738.2 Observing Velocity to Reduce Phase Lag1858.3 Using observers to Improve Disturbance Response..... 2028.4 Exercises212Referencesn213A Observer-Based resolver conversion in industrialServo Systems1■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■217B Cures for mechanical resonance in IndustrialServo Systems227Introductionaaa日aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa日aaaaa.aaaaaaaaaaaaaaa日aa227TWo-Part Transfer function228LOW-Frequency Resonance229Velocity Control Law…...8....230Methods of Correction Applied to Low-Frequency Resonance231Conc| usion.…235Acknowledgments235References235C European Symbols for Block Diagrams237Part Linear functions237Part l: nonlinear functions238D Development of the bilinear transformation241Bilinear Transformation241Prewarning242Factoring polynomials243Phase Advancing………………………,243Solutions toChapter 2245Chapter 3245Chapter 4246Chapter 5重口m口m246Chapter 6247Chapter7.….B..8..8..8...248Chapter 8249Index251AcknowledgmentsWriting a book is a large task and requires support from numerous people, and thosepeople deserve thanks. First, I thank LeeAnn, my devoted wife of more than 20 yearsShe has been an unflagging fan, a counselor, and a demanding editor. She taught memuch of what I have managed to learn about how to express a thought in ink. Thanksto my mother who was sure I would grow into someone in whom she would be proudwhen facts should have dissuaded her Thanks also to my father for his insistence thatI obtain a college education; that privilege was denied to him, an intelligent man borninto a family of modest meansI am grateful for the education provided by Virginia Tech Go Hokies. The basicsof electrical engineering imparted to me over my years at school allowed me to graspthe concepts I apply regularly today. I am grateful to Mr. Emory Pace, a toughprofessor who led me through numerous calculus courses and, in doing so, gaveme the confidence on which I would rely throughout my college career and beyondI am especially grateful to Dr Charles Nunnally; having arrived at university froma successful career in industry, he provided my earliest exposure to the practicalapplication of the material I strove to learn. I also thank Dr robert lorenz of theUniversity of Wisconsin at Madison, who introduced me to observers some years agoHis instruction has been enlightening and practical. Several of his university coursesare available in video format and are recommended for those who would like toextend their knowledge of controls. In particular, readers should consider ME 746which presents observers and numerous other subjectsI thank those who reviewed the manuscript for this book. Special thanks goes toDan Carlson for his contributions to almost every chapter contained herein Thanksalso to Eric Berg for his numerous insights. Thanks to the people of KollmorgenCorporation(now, Danaher Corporation), my long-time employer, for their continuing support in writing this book. Finally, thanks to Academic Press, especially to JoelClaypool, my editor, for the opportunity to write this edition and for editing, printing, distributing, and performing the myriad other tasks required to publish a bookX1

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用于鱼眼摄像头的一个环视参考文档很不错，自己最开始做这个相关的项目就是参考这个文档，发现写的很是不错，非常值得参考特别有用的，哈哈哈哈哈哈哈哈哈哈赵三峰,谢明,陈玉明:基于逆向投影的全景泊车系统设计与实现其中,(x,y)表示校正图像的坐标,(x,y)表示鱼眼图像的坐标此算法的效果如图所示。1------图校正前后图像俯视变换clay.OB图离散化后的路面本文采用直接线性变换()来找到俯视变换的投影矩阵,这种方法的优点在于不需要知道摄像头视RR角等参数,只需要在图像坐标系下标定对特征点就可R以计算出个未知的参数,从而得到单应性矩阵,并利R用单应性矩阼完成俯视变换。其中,M表示合成图像的宽度,单位:像素;No表示直接线性变换的公式如下合成图像的高度,单位:像素;R表示合成区域的宽Coxi i+Coli+Cu22i +Cu3)度,单位:;R1表示合成区域的长度,单位(iam,0)表示图像的坐标,单位:像素;x,y表示合成区C102+(ny2+C12x;+CrC20x:+C21y+C2231+1)域路面的坐标,单位:。下面判断路面上的点被哪个摄像头拍到,因此将路其中,(2v)表示图像坐标,(xy2)为物体空间坐标,面分成八个区域,如图所示Co,co1,…,C2为未知参数。但是本文的物体选择的是路面特征点,因此公式的z=0,简化后的二维公式为:(左前前)(右前)IX). Ti t Coli+CUsC0x;+C21y;+1(左)汽车v C1o x, +C11)2+C13C20x:+C21y1+1如果川矩阵的形式表示,如下(左后)(后)(右后)ROT=C1C1 CI图路而的八个区域图中,Il、ⅣV、V和ⅤI四个区域只能被前,左,RO表示路面坐标到图像左边的变换矩阵,则ROn右,后四个摄像头看到。I、I、VI和VI为两个摄像表示图像到路面的投影矩阵头的交叉区域,可能被两个摄像头看到,因此需要判断图像合成交叉区域被哪个摄像头采集到,四个交叉区域的判别方本文的创新点就在于跳出了传统图像拼接的想维,法相同,因此以区域1为例描述如下采用一种更加简单有效的算法来实现无缝拼接全景。)取区域I内任意一点(jo),计算其路面坐标假设路面合成区域的大小为长R1,宽为Rw,单假定该点可以被前摄像头采集到,通过与前摄位:。R的宽度方向平均分成M等份,R1的高像头的投影矩阵ROlo相乘,便可以得到该点在前摄度方向平均分成N等份,其中任意一点坐标用(mm)像头的像素坐标av),如果0≤

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