{"product_id":"algebraic-identification-and-estimation-methods-in-feedback-control-systems-hardback-9781118730607","title":"Algebraic Identification and Estimation Methods in Feedback Control Systems (Hardback) 9781118730607","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eAlgebraic Identification and Estimation Methods in Feedback Control Systems\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eHebertt Sira-Ramírez (Author), Carlos García Rodríguez (Author), John Cortés Romero (Author), Alberto Luviano Juárez (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781118730607, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 7 May 2014\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e392 pages\u003cbr\u003e25.2 x 17.8 x 2.5 cm, 0.748 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003ci\u003eAlgebraic Identification and Estimation Methods in Feedback Control Systems\u003c\/i\u003e presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws.\u003c\/p\u003e \u003cp\u003eThis book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology. \u003c\/p\u003e \u003cp\u003eKey features:\u003c\/p\u003e \u003cul\u003e \u003cli\u003ePresents a radically new approach to online parameter and state estimation.\u003c\/li\u003e \u003cli\u003eEnables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory.\u003c\/li\u003e \u003cli\u003eIncludes examples in a variety of physical applications with experimental results.\u003c\/li\u003e \u003cli\u003eCovers the latest developments and applications.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eAlgebraic Identification and Estimation Methods in Feedback Control Systems\u003c\/i\u003e is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSeries Preface xiii  \u003cp\u003ePreface xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Feedback Control of Dynamic Systems 2\u003c\/p\u003e \u003cp\u003e1.1.1 Feedback 2\u003c\/p\u003e \u003cp\u003e1.1.2 Why Do We Need Feedback? 3\u003c\/p\u003e \u003cp\u003e1.2 The Parameter Identification Problem 3\u003c\/p\u003e \u003cp\u003e1.2.1 Identifying a System 4\u003c\/p\u003e \u003cp\u003e1.3 A Brief Survey on Parameter Identification 4\u003c\/p\u003e \u003cp\u003e1.4 The State Estimation Problem 5\u003c\/p\u003e \u003cp\u003e1.4.1 Observers 6\u003c\/p\u003e \u003cp\u003e1.4.2 Reconstructing the State via Time Derivative Estimation 7\u003c\/p\u003e \u003cp\u003e1.5 Algebraic Methods in Control Theory: Differences from Existing Methodologies 8\u003c\/p\u003e \u003cp\u003e1.6 Outline of the Book 9\u003c\/p\u003e \u003cp\u003eReferences 12\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Algebraic Parameter Identification in Linear Systems 15\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 15\u003c\/p\u003e \u003cp\u003e2.1.1 The Parameter-Estimation Problem in Linear Systems 16\u003c\/p\u003e \u003cp\u003e2.2 Introductory Examples 17\u003c\/p\u003e \u003cp\u003e2.2.1 Dragging an Unknown Mass in Open Loop 17\u003c\/p\u003e \u003cp\u003e2.2.2 A Perturbed First-Order System 24\u003c\/p\u003e \u003cp\u003e2.2.3 The Visual Servoing Problem 30\u003c\/p\u003e \u003cp\u003e2.2.4 Balancing of the Plane Rotor 35\u003c\/p\u003e \u003cp\u003e2.2.5 On the Control of the Linear Motor 38\u003c\/p\u003e \u003cp\u003e2.2.6 Double-Bridge Buck Converter 42\u003c\/p\u003e \u003cp\u003e2.2.7 Closed-Loop Behavior 43\u003c\/p\u003e \u003cp\u003e2.2.8 Control of an unknown variable gain motor 47\u003c\/p\u003e \u003cp\u003e2.2.9 Identifying Classical Controller Parameters 50\u003c\/p\u003e \u003cp\u003e2.3 A Case Study Introducing a “Sentinel” Criterion 53\u003c\/p\u003e \u003cp\u003e2.3.1 A Suspension System Model 54\u003c\/p\u003e \u003cp\u003e2.4 Remarks 67\u003c\/p\u003e \u003cp\u003eReferences 68\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Algebraic Parameter Identification in Nonlinear Systems 71\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 71\u003c\/p\u003e \u003cp\u003e3.2 Algebraic Parameter Identification for Nonlinear Systems 72\u003c\/p\u003e \u003cp\u003e3.2.1 Controlling an Uncertain Pendulum 74\u003c\/p\u003e \u003cp\u003e3.2.2 A Block-Driving Problem 80\u003c\/p\u003e \u003cp\u003e3.2.3 The Fully Actuated Rigid Body 84\u003c\/p\u003e \u003cp\u003e3.2.4 Parameter Identification Under Sliding Motions 90\u003c\/p\u003e \u003cp\u003e3.2.5 Control of an Uncertain Inverted Pendulum Driven by a DC Motor 92\u003c\/p\u003e \u003cp\u003e3.2.6 Identification and Control of a Convey Crane 96\u003c\/p\u003e \u003cp\u003e3.2.7 Identification of a Magnetic Levitation System 103\u003c\/p\u003e \u003cp\u003e3.3 An Alternative Construction of the System of Linear Equations 105\u003c\/p\u003e \u003cp\u003e3.3.1 Genesio–Tesi Chaotic System 107\u003c\/p\u003e \u003cp\u003e3.3.2 The Ueda Oscillator 108\u003c\/p\u003e \u003cp\u003e3.3.3 Identification and Control of an Uncertain Brushless DC Motor 112\u003c\/p\u003e \u003cp\u003e3.3.4 Parameter Identification and Self-tuned Control for the Inertia Wheel Pendulum 119\u003c\/p\u003e \u003cp\u003e3.3.5 Algebraic Parameter Identification for Induction Motors 128\u003c\/p\u003e \u003cp\u003e3.3.6 A Criterion to Determine the Estimator Convergence: The Error Index 136\u003c\/p\u003e \u003cp\u003e3.4 Remarks 141\u003c\/p\u003e \u003cp\u003eReferences 141\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Algebraic Parameter Identification in Discrete-Time Systems 145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 145\u003c\/p\u003e \u003cp\u003e4.2 Algebraic Parameter Identification in Discrete-Time Systems 145\u003c\/p\u003e \u003cp\u003e4.2.1 Main Purpose of the Chapter 146\u003c\/p\u003e \u003cp\u003e4.2.2 Problem Formulation and Assumptions 147\u003c\/p\u003e \u003cp\u003e4.2.3 An Introductory Example 148\u003c\/p\u003e \u003cp\u003e4.2.4 Samuelson’s Model of the National Economy 150\u003c\/p\u003e \u003cp\u003e4.2.5 Heating of a Slab from Two Boundary Points 155\u003c\/p\u003e \u003cp\u003e4.2.6 An Exact Backward Shift Reconstructor 157\u003c\/p\u003e \u003cp\u003e4.3 A Nonlinear Filtering Scheme 160\u003c\/p\u003e \u003cp\u003e4.3.1 Hénon System 161\u003c\/p\u003e \u003cp\u003e4.3.2 A Hard Disk Drive 164\u003c\/p\u003e \u003cp\u003e4.3.3 The Visual Servo Tracking Problem 166\u003c\/p\u003e \u003cp\u003e4.3.4 A Shape Control Problem in a Rolling Mill 170\u003c\/p\u003e \u003cp\u003e4.3.5 Algebraic Frequency Identification of a Sinusoidal Signal by Means of Exact Discretization 175\u003c\/p\u003e \u003cp\u003e4.4 Algebraic Identification in Fast-Sampled Linear Systems 178\u003c\/p\u003e \u003cp\u003e4.4.1 The Delta-Operator Approach: A Theoretical Framework 179\u003c\/p\u003e \u003cp\u003e4.4.2 Delta-Transform Properties 181\u003c\/p\u003e \u003cp\u003e4.4.3 A DC Motor Example 181\u003c\/p\u003e \u003cp\u003e4.5 Remarks 188\u003c\/p\u003e \u003cp\u003eReferences 188\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 State and Parameter Estimation in Linear Systems 191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 191\u003c\/p\u003e \u003cp\u003e5.1.1 Signal Time Derivation Through the “Algebraic Derivative Method” 192\u003c\/p\u003e \u003cp\u003e5.1.2 Observability of Nonlinear Systems 192\u003c\/p\u003e \u003cp\u003e5.2 Fast State Estimation 193\u003c\/p\u003e \u003cp\u003e5.2.1 An Elementary Second-Order Example 193\u003c\/p\u003e \u003cp\u003e5.2.2 An Elementary Third-Order Example 194\u003c\/p\u003e \u003cp\u003e5.2.3 A Control System Example 198\u003c\/p\u003e \u003cp\u003e5.2.4 Control of a Perturbed Third-Order System 201\u003c\/p\u003e \u003cp\u003e5.2.5 A Sinusoid Estimation Problem 203\u003c\/p\u003e \u003cp\u003e5.2.6 Identification of Gravitational Wave Parameters 205\u003c\/p\u003e \u003cp\u003e5.2.7 A Power Electronics Example 210\u003c\/p\u003e \u003cp\u003e5.2.8 A Hydraulic Press 213\u003c\/p\u003e \u003cp\u003e5.2.9 Identification and Control of a Plotter 218\u003c\/p\u003e \u003cp\u003e5.3 Recovering Chaotically Encrypted Signals 222\u003c\/p\u003e \u003cp\u003e5.3.1 State Estimation for a Lorenz System 227\u003c\/p\u003e \u003cp\u003e5.3.2 State Estimation for Chen’s System 229\u003c\/p\u003e \u003cp\u003e5.3.3 State Estimation for Chua’s Circuit 231\u003c\/p\u003e \u003cp\u003e5.3.4 State Estimation for Rossler’s System 232\u003c\/p\u003e \u003cp\u003e5.3.5 State Estimation for the Hysteretic Circuit 234\u003c\/p\u003e \u003cp\u003e5.3.6 Simultaneous Chaotic Encoding–Decoding with Singularity Avoidance 239\u003c\/p\u003e \u003cp\u003e5.3.7 Discussion 240\u003c\/p\u003e \u003cp\u003e5.4 Remarks 241\u003c\/p\u003e \u003cp\u003eReferences 242\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Control of Nonlinear Systems via Output Feedback 245\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 245\u003c\/p\u003e \u003cp\u003e6.2 Time-Derivative Calculations 246\u003c\/p\u003e \u003cp\u003e6.2.1 An Introductory Example 247\u003c\/p\u003e \u003cp\u003e6.2.2 Identifying a Switching Input 253\u003c\/p\u003e \u003cp\u003e6.3 The Nonlinear Systems Case 255\u003c\/p\u003e \u003cp\u003e6.3.1 Control of a Synchronous Generator 256\u003c\/p\u003e \u003cp\u003e6.3.2 Control of a Multi-variable Nonlinear System 261\u003c\/p\u003e \u003cp\u003e6.3.3 Experimental Results on a Mechanical System 267\u003c\/p\u003e \u003cp\u003e6.4 Remarks 278\u003c\/p\u003e \u003cp\u003eReferences 279\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Miscellaneous Applications 281\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 281\u003c\/p\u003e \u003cp\u003e7.1.1 The Separately Excited DC Motor 282\u003c\/p\u003e \u003cp\u003e7.1.2 Justification of the ETEDPOF Controller 285\u003c\/p\u003e \u003cp\u003e7.1.3 A Sensorless Scheme Based on Fast Adaptive Observation 287\u003c\/p\u003e \u003cp\u003e7.1.4 Control of the Boost Converter 292\u003c\/p\u003e \u003cp\u003e7.2 Alternative Elimination of Initial Conditions 298\u003c\/p\u003e \u003cp\u003e7.2.1 A Bounded Exponential Function 299\u003c\/p\u003e \u003cp\u003e7.2.2 Correspondence in the Frequency Domain 300\u003c\/p\u003e \u003cp\u003e7.2.3 A System of Second Order 301\u003c\/p\u003e \u003cp\u003e7.3 Other Functions of Time for Parameter Estimation 304\u003c\/p\u003e \u003cp\u003e7.3.1 A Mechanical System Example 304\u003c\/p\u003e \u003cp\u003e7.3.2 A Derivative Approach to Demodulation 310\u003c\/p\u003e \u003cp\u003e7.3.3 Time Derivatives via Parameter Identification 312\u003c\/p\u003e \u003cp\u003e7.3.4 Example 314\u003c\/p\u003e \u003cp\u003e7.4 An Algebraic Denoising Scheme 318\u003c\/p\u003e \u003cp\u003e7.4.1 Example 321\u003c\/p\u003e \u003cp\u003e7.4.2 Numerical Results 322\u003c\/p\u003e \u003cp\u003e7.5 Remarks 325\u003c\/p\u003e \u003cp\u003eReferences 326\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A Parameter Identification in Linear Continuous Systems: A Module Approach 329\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Generalities on Linear Systems Identification 329\u003c\/p\u003e \u003cp\u003eA.1.1 Example 330\u003c\/p\u003e \u003cp\u003eA.1.2 Some Definitions and Results 330\u003c\/p\u003e \u003cp\u003eA.1.3 Linear Identifiability 331\u003c\/p\u003e \u003cp\u003eA.1.4 Structured Perturbations 333\u003c\/p\u003e \u003cp\u003eA.1.5 The Frequency Domain Alternative 337\u003c\/p\u003e \u003cp\u003eReferences 338\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B Parameter Identification in Linear Discrete Systems: A Module Approach 339\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eB.1 A Short Review of Module Theory over Principal Ideal Rings 339\u003c\/p\u003e \u003cp\u003eB.1.1 Systems 340\u003c\/p\u003e \u003cp\u003eB.1.2 Perturbations 340\u003c\/p\u003e \u003cp\u003eB.1.3 Dynamics and Input–Output Systems 341\u003c\/p\u003e \u003cp\u003eB.1.4 Transfer Matrices 341\u003c\/p\u003e \u003cp\u003eB.1.5 Identifiability 342\u003c\/p\u003e \u003cp\u003eB.1.6 An Algebraic Setting for Identifiability 342\u003c\/p\u003e \u003cp\u003eB.1.7 Linear identifiability of transfer functions 344\u003c\/p\u003e \u003cp\u003eB.1.8 Linear Identification of Perturbed Systems 345\u003c\/p\u003e \u003cp\u003eB.1.9 Persistent Trajectories 347\u003c\/p\u003e \u003cp\u003eReferences 348\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix C Simultaneous State and Parameter Estimation: An Algebraic Approach 349\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eC.1 Rings, Fields and Extensions 349\u003c\/p\u003e \u003cp\u003eC.2 Nonlinear Systems 350\u003c\/p\u003e \u003cp\u003eC.2.1 Differential Flatness 351\u003c\/p\u003e \u003cp\u003eC.2.2 Observability and Identifiability 352\u003c\/p\u003e \u003cp\u003eC.2.3 Observability 352\u003c\/p\u003e \u003cp\u003eC.2.4 Identifiable Parameters 352\u003c\/p\u003e \u003cp\u003eC.2.5 Determinable Variables 352\u003c\/p\u003e \u003cp\u003eC.3 Numerical Differentiation 353\u003c\/p\u003e \u003cp\u003eC.3.1 Polynomial Time Signals 353\u003c\/p\u003e \u003cp\u003eC.3.2 Analytic Time Signals 353\u003c\/p\u003e \u003cp\u003eC.3.3 Noisy Signals 354\u003c\/p\u003e \u003cp\u003eReferences 354\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix D Generalized Proportional Integral Control 357\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eD.1 Generalities on GPI Control 357\u003c\/p\u003e \u003cp\u003eD.2 Generalization to MIMO Linear Systems 365\u003c\/p\u003e \u003cp\u003eReferences 368\u003c\/p\u003e \u003cp\u003eIndex 369\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Mechanical engineering \u0026amp; materials [\u003ca title=\"See our other books on Mechanical engineering \u0026amp; materials\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Mechanical%20engineering%20\u0026amp;%20materials%20%5BTG%5D%22\"\u003eTG\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52421365825816,"sku":"9781118730607","price":96.96,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781118730607.jpg?v=1784592557","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/algebraic-identification-and-estimation-methods-in-feedback-control-systems-hardback-9781118730607","provider":"Freshly Printed Books","version":"1.0","type":"link"}