Details

Robust Control


Robust Control

Theory and Applications
1. Aufl.

von: Kang-Zhi Liu, Yu Yao

106,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 15.09.2016
ISBN/EAN: 9781118754412
Sprache: englisch
Anzahl Seiten: 500

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Beschreibungen

<i><b>Comprehensive and up to date coverage of robust control theory and its application</b></i><br /><br />•   Presented in a well-planned and logical way<br /><br />•   Written by a respected leading author, with extensive experience in robust control<br /><br />•   Accompanying website provides solutions manual and other supplementary material
<p>Preface xvii</p> <p>List of Abbreviations xix</p> <p>Notations xxi</p> <p><b>1 Introduction 1</b></p> <p>1.1 Engineering Background of Robust Control 1</p> <p>1.2 Methodologies of Robust Control 4</p> <p>1.3 A Brief History of Robust Control 8</p> <p><b>2 Basics of Linear Algebra and Function Analysis 10</b></p> <p>2.1 Trace, Determinant, Matrix Inverse, and Block Matrix 10</p> <p>2.2 Elementary Linear Transformation of Matrix and Its Matrix Description 12</p> <p>2.3 Linear Vector Space 14</p> <p>2.4 Norm and Inner Product of Vector 18</p> <p>2.5 Linear Subspace 22</p> <p>2.6 Matrix and Linear Mapping 23</p> <p>2.7 Eigenvalue and Eigenvector 28</p> <p>2.8 Invariant Subspace 30</p> <p>2.9 Pseudo-Inverse and Linear Matrix Equation 34</p> <p>2.10 Quadratic Form and Positive Definite Matrix 35</p> <p>2.11 Norm and Inner Product of Matrix 37</p> <p>2.12 Singular Value and Singular Value Decomposition 40</p> <p>2.13 Calculus of Vector and Matrix 43</p> <p>2.14 Kronecker Product 44</p> <p>2.15 Norm and Inner Product of Function 45</p> <p><b>3 Basics of Convex Analysis and LMI 57</b></p> <p>3.1 Convex Set and Convex Function 57</p> <p>3.2 Introduction to LMI 72</p> <p>3.3 Interior Point Method* 81</p> <p><b>4 Fundamentals of Linear System 85</b></p> <p>4.1 Structural Properties of Dynamic System 85</p> <p>4.2 Stability 100</p> <p>4.3 Lyapunov Equation 108</p> <p>4.4 Linear Fractional Transformation 114</p> <p><b>5 System Performance 119</b></p> <p>5.1 Test Signal 120</p> <p>5.2 Steady-State Response 122</p> <p>5.3 Transient Response 130</p> <p>5.4 Comparison of Open-Loop and Closed-Loop Controls 140</p> <p><b>6 Stabilization of Linear Systems 148</b></p> <p>6.1 State Feedback 148</p> <p>6.2 Observer 160</p> <p>6.3 Combined System and Separation Principle 167</p> <p><b>7 Parametrization of Stabilizing Controllers 173</b></p> <p>7.1 Generalized Feedback Control System 174</p> <p>7.2 Parametrization of Controllers 178</p> <p>7.3 Youla Parametrization 184</p> <p>7.4 Structure of Closed-Loop System 186</p> <p>7.5 2-Degree-of-Freedom System 188</p> <p><b>8 Relation between Time Domain and Frequency Domain Properties 197</b></p> <p>8.1 Parseval’s Theorem 197</p> <p>8.2 KYP Lemma 200</p> <p><b>9 Algebraic Riccati Equation 215</b></p> <p>9.1 Algorithm for Riccati Equation 215</p> <p>9.2 Stabilizing Solution 218</p> <p>9.3 Inner Function 223</p> <p><b>10 Performance Limitation of Feedback Control 225</b></p> <p>10.1 Preliminaries 226</p> <p>10.2 Limitation on Achievable Closed-loop Transfer Function 228</p> <p>10.3 Integral Relation 231</p> <p>10.4 Limitation of Reference Tracking 237</p> <p><b>11 Model Uncertainty 245</b></p> <p>11.1 Model Uncertainty: Examples 245</p> <p>11.2 Plant Set with Dynamic Uncertainty 248</p> <p>11.3 Parametric System 253</p> <p>11.4 Plant Set with Phase Information of Uncertainty 264</p> <p>11.5 LPV Model and Nonlinear Systems 266</p> <p>11.6 Robust Stability and Robust Performance 269</p> <p><b>12 Robustness Analysis 1: Small-Gain Principle 272</b></p> <p>12.1 Small-Gain Theorem 272</p> <p>12.2 Robust Stability Criteria 276</p> <p>12.3 Equivalence between H∞ Performance and Robust Stability 277</p> <p>12.4 Analysis of Robust Performance 279</p> <p>12.5 Stability Radius of Norm-Bounded Parametric Systems 282</p> <p><b>13 Robustness Analysis 2: Lyapunov Method 288</b></p> <p>13.1 Overview of Lyapunov Stability Theory 288</p> <p>13.2 Quadratic Stability 290</p> <p>13.3 Lur'e System 296</p> <p>13.4 Passive Systems 307</p> <p><b>14 Robustness Analysis 3: IQC Approach 312</b></p> <p>14.1 Concept of IQC 312</p> <p>14.2 IQC Theorem 314</p> <p>14.3 Applications of IQC 316</p> <p>14.4 Proof of IQC Theorem* 319</p> <p><b>15 H2 Control 322</b></p> <p>15.1 H2 Norm of Transfer Function 322</p> <p>15.2 H2 Control Problem 329</p> <p>15.3 Solution to Nonsingular H2 Control Problem 331</p> <p>15.4 Proof of Nonsingular Solution 332</p> <p>15.5 Singular H2 Control 335</p> <p>15.6 Case Study: H2 Control of an RTP System 337</p> <p><b>16 H∞ Control 346</b></p> <p>16.1 Control Problem and H∞ Norm 346</p> <p>16.2 H∞ Control Problem 348</p> <p>16.3 LMI Solution 1: Variable Elimination 349</p> <p>16.4 LMI Solution 2: Variable Change 351</p> <p>16.5 Design of Generalized Plant and Weighting Function 352</p> <p>16.6 Case Study 354</p> <p>16.7 Scaled H∞ Control 355</p> <p><b>17 μ Synthesis 360</b></p> <p>17.1 Introduction to μ 360</p> <p>17.2 Definition of μ and Its Implication 364</p> <p>17.3 Properties of μ 365</p> <p>17.4 Condition for Robust H∞ Performance 368</p> <p>17.5 D–K Iteration Design 369</p> <p>17.6 Case Study 371</p> <p><b>18 Robust Control of Parametric Systems 375</b></p> <p>18.1 Quadratic Stabilization of Polytopic Systems 375</p> <p>18.2 Quadratic Stabilization of Norm-Bounded Parametric Systems 379</p> <p>18.3 Robust H∞ Control Design of Polytopic Systems 379</p> <p>18.4 Robust H∞ Control Design of Norm-Bounded Parametric Systems 382</p> <p><b>19 Regional Pole Placement 384</b></p> <p>19.1 Convex Region and Its Characterization 384</p> <p>19.2 Condition for Regional Pole Placement 387</p> <p>19.3 Composite LMI Region 392</p> <p>19.4 Feedback Controller Design 394</p> <p>19.5 Analysis of Robust Pole Placement 396</p> <p>19.6 Robust Design of Regional Pole Placement 402</p> <p><b>20 Gain-Scheduled Control 407</b></p> <p>20.1 General Structure 407</p> <p>20.2 LFT-Type Parametric Model 408</p> <p>20.3 Case Study: Stabilization of a Unicycle Robot 414</p> <p>20.4 Affine LPV Model 422</p> <p>20.5 Case Study: Transient Stabilization of a Power System 428</p> <p><b>21 Positive Real Method 436</b></p> <p>21.1 Structure of Uncertain Closed-Loop System 436</p> <p>21.2 Robust Stabilization Based on Strongly Positive Realness 438</p> <p>21.3 Robust Stabilization Based on Strictly Positive Realness 441</p> <p>21.4 Robust Performance Design for Systems with Positive Real Uncertainty 442</p> <p>21.5 Case Study 445</p> <p>Exercises 448</p> <p>Notes and References 449</p> <p>References 450</p> <p>Index 455</p>
<p><b>Professor Kang-Zhi Liu, Dept. of Electrical and Electronic Engineering, Chiba University, Japan.</b> Professor Liu achieved his Ph.D. degree in 1991 from Chiba University, Japan.  His areas of expertise include Control Theory, Control and Operation of Power Systems, and System Integration of Smart-Grid, and he has worked in these related areas for 27 years (4 years as a professor, 13 years as an associate professor, 5 years as an assistant professor, and 5 years as a graduate student). He is currently Associate Editor of both the International Journal of Control Theory and Applications, and the International Journal of Systems Science.  He is the author of 6 books (two in Chinese and four in Japanese).</p> <p><b>Dr. Yu Yao is a Cheng Kong Scholar Chair Professor at the Harbin Institute of Technology, China.</b> He also serves as Vice President of Harbin University of Engineering, China. His research interests include nonlinear systems, robust control and flight control. He has published over 100 journal papers.</p>

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