Variance-constrained multi-objective stochastic control and filtering:
"Variance-Constrained Multi-Objective Stochastic Control and Filtering covers the latest research results and presents the state-of-the-art of control and filtering problems while taking multiple design objectives into consideration"--
Gespeichert in:
| Beteilige Person: | |
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| Weitere beteiligte Personen: | , |
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Chichester, West Sussex, United Kingdom
Wiley
2015
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781118929490/?ar |
| Zusammenfassung: | "Variance-Constrained Multi-Objective Stochastic Control and Filtering covers the latest research results and presents the state-of-the-art of control and filtering problems while taking multiple design objectives into consideration"-- |
| Beschreibung: | Machine generated contents note: Preface vii Acknowledgements ix List of Abbreviations xi 1 Introduction 1 1.1 Analysis and Synthesis of Nonlinear Stochastic Systems 2 1.1.1 Nonlinear Systems 3 1.1.2 Stochastic Systems 4 1.2 Multi-Objective Control and Filtering with Variance Constraints 5 1.2.1 Covariance Control Theory 5 1.2.2 Multiple Performance Requirements 7 1.2.3 Design Techniques for Nonlinear Stochastic Systems with Variance Constraints 9 1.2.4 A Special Case of Multi-Objective Design: Mixed H2/H1 Control/Filtering 11 1.3 Outline 12 2 Robust H1 Control with Variance Constraints 17 2.1 Problem Formulation 18 2.2 Stability, H1 Performance and Variance Analysis 20 2.2.1 Stability, H1 Performance Analysis 21 2.2.2 Variance Analysis 23 2.3 Robust Controller Design 27 2.4 Numerical Example 30 2.5 Summary 33 3 Robust Mixed H2=H1 Filtering 41 3.1 System Description and Problem Formulation 42 3.2 Algebraic Characterizations for Robust H2=H1 Filtering 44 3.2.1 Robust H2 Filtering 44 3.2.2 Robust H1 Filtering 50 3.3 Robust H2=H1 Filter Design Techniques 51 3.4 An Illustrative Example 60 3.5 Summary 62 4 Filtering with Missing Measurements 63 4.1 Problem Formulation 64 4.2 Stability and Variance Analysis 67 4.3 Robust Filter Design 71 4.4 Numerical Example 75 4.5 Summary 78 5 Robust Fault-Tolerant Control 87 5.1 Problem Formulation 88 5.2 Stability and Variance Analysis 90 5.3 Robust Controller Design 92 5.4 Numerical Example 98 5.5 Summary 103 6 Robust H2 SMC 105 6.1 The System Model 106 6.2 Robust H2 Sliding Mode Control 107 6.2.1 Switching Surface 107 6.2.2 Performances of the Sliding Motion 108 6.2.3 Computational Algorithm 114 6.3 Sliding Mode Controller 115 6.4 Numerical Example 116 6.5 Summary 118 7 Dissipative Control with Degraded Measurements 125 7.1 Problem Formulation 126 7.2 Stability, Dissipativity and Variance Analysis 129 7.3 Observer-Based Controller Design 134 7.3.1 Solvability of Multi-Objective Control Problem 134 7.3.2 Computational Algorithm 139 7.4 Numerical Example 140 7.5 Summary 142 8 Variance-Constrained H1 Control with Multiplicative Noises 145 8.1 Problem Formulation 146 8.2 Stability, H1 Performance, Variance Analysis 147 8.2.1 Stability 148 8.2.2 H1 performance 150 8.2.3 Variance analysis 152 8.3 Robust State Feedback Controller Design 153 8.4 A Numerical Example 156 8.5 Summary 157 9 Robust Finite-Horizon H1 Control 159 9.1 Problem Formulation 160 9.2 Performance Analysis 162 9.2.1 H1 Performance 162 9.2.2 Variance Analysis 164 9.3 Robust Finite Horizon Controller Design 167 9.4 Numerical Example 171 9.5 Summary 173 10 Finite-Horizon Filtering with Degraded Measurements 177 10.1 Problem Formulation 178 10.2 Performance Analysis 181 10.2.1 H1 Performance Analysis 181 10.2.2 System Covariance Analysis 186 10.3 Robust Filter Design 187 10.4 Numerical Example 190 10.5 Summary 191 11 Mixed H2=H1 Control with Randomly Occurring Nonlinearities: the Finite-Horizon Case 197 11.1 Problem Formulation 199 11.2 H1 Performance 200 11.3 Mixed H2=H1 Controller Design 204 11.3.1 State-Feedback Controller Design 204 11.3.2 Computational Algorithm 207 11.4 Numerical Example 207 11.5 Summary 211 12 Finite-Horizon H2=H1 Control of MJSs with Sensor Failures 213 12.1 Problem Formulation 214 12.2 H1 Performance 216 12.3 Mixed H2=H1 Controller Design 220 12.3.1 Controller Design 220 12.3.2 Computational Algorithm 224 12.4 Numerical Example 224 12.5 Summary 227 13 Finite-Horizon Control with ROSF 229 13.1 Problem Formulation 230 13.2 H1 And Covariance Performances Analysis 234 13.2.1 H1 Performance 234 13.2.2 Covariance Analysis 238 13.3 Robust Finite-Horizon Controller Design 240 13.3.1 Controller Design 240 13.3.2 Computational Algorithm 243 13.4 Numerical Example 243 13.5 Summary 244 14 Finite-Horizon H2=H1 Control with Actuator Failures 247 14.1 Problem Formulation 248 14.2 H1 Performance 251 14.3 Multi-Objective Controller Design 253 14.3.1 Controller Design 253 14.3.2 Computational Algorithm 256 14.4 Numerical Example 257 14.5 Summary 259 15 Conclusions and Future Topics 261 References 263. - Includes bibliographical references and index. - Print version record and CIP data provided by publisher |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9781118929476 1118929470 9781118929490 |
Internformat
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| 264 | 1 | |a Chichester, West Sussex, United Kingdom |b Wiley |c 2015 | |
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| 500 | |a Machine generated contents note: Preface vii Acknowledgements ix List of Abbreviations xi 1 Introduction 1 1.1 Analysis and Synthesis of Nonlinear Stochastic Systems 2 1.1.1 Nonlinear Systems 3 1.1.2 Stochastic Systems 4 1.2 Multi-Objective Control and Filtering with Variance Constraints 5 1.2.1 Covariance Control Theory 5 1.2.2 Multiple Performance Requirements 7 1.2.3 Design Techniques for Nonlinear Stochastic Systems with Variance Constraints 9 1.2.4 A Special Case of Multi-Objective Design: Mixed H2/H1 Control/Filtering 11 1.3 Outline 12 2 Robust H1 Control with Variance Constraints 17 2.1 Problem Formulation 18 2.2 Stability, H1 Performance and Variance Analysis 20 2.2.1 Stability, H1 Performance Analysis 21 2.2.2 Variance Analysis 23 2.3 Robust Controller Design 27 2.4 Numerical Example 30 2.5 Summary 33 3 Robust Mixed H2=H1 Filtering 41 3.1 System Description and Problem Formulation 42 3.2 Algebraic Characterizations for Robust H2=H1 Filtering 44 3.2.1 Robust H2 Filtering 44 3.2.2 Robust H1 Filtering 50 3.3 Robust H2=H1 Filter Design Techniques 51 3.4 An Illustrative Example 60 3.5 Summary 62 4 Filtering with Missing Measurements 63 4.1 Problem Formulation 64 4.2 Stability and Variance Analysis 67 4.3 Robust Filter Design 71 4.4 Numerical Example 75 4.5 Summary 78 5 Robust Fault-Tolerant Control 87 5.1 Problem Formulation 88 5.2 Stability and Variance Analysis 90 5.3 Robust Controller Design 92 5.4 Numerical Example 98 5.5 Summary 103 6 Robust H2 SMC 105 6.1 The System Model 106 6.2 Robust H2 Sliding Mode Control 107 6.2.1 Switching Surface 107 6.2.2 Performances of the Sliding Motion 108 6.2.3 Computational Algorithm 114 6.3 Sliding Mode Controller 115 6.4 Numerical Example 116 6.5 Summary 118 7 Dissipative Control with Degraded Measurements 125 7.1 Problem Formulation 126 7.2 Stability, Dissipativity and Variance Analysis 129 7.3 Observer-Based Controller Design 134 7.3.1 Solvability of Multi-Objective Control Problem 134 7.3.2 Computational Algorithm 139 7.4 Numerical Example 140 7.5 Summary 142 8 Variance-Constrained H1 Control with Multiplicative Noises 145 8.1 Problem Formulation 146 8.2 Stability, H1 Performance, Variance Analysis 147 8.2.1 Stability 148 8.2.2 H1 performance 150 8.2.3 Variance analysis 152 8.3 Robust State Feedback Controller Design 153 8.4 A Numerical Example 156 8.5 Summary 157 9 Robust Finite-Horizon H1 Control 159 9.1 Problem Formulation 160 9.2 Performance Analysis 162 9.2.1 H1 Performance 162 9.2.2 Variance Analysis 164 9.3 Robust Finite Horizon Controller Design 167 9.4 Numerical Example 171 9.5 Summary 173 10 Finite-Horizon Filtering with Degraded Measurements 177 10.1 Problem Formulation 178 10.2 Performance Analysis 181 10.2.1 H1 Performance Analysis 181 10.2.2 System Covariance Analysis 186 10.3 Robust Filter Design 187 10.4 Numerical Example 190 10.5 Summary 191 11 Mixed H2=H1 Control with Randomly Occurring Nonlinearities: the Finite-Horizon Case 197 11.1 Problem Formulation 199 11.2 H1 Performance 200 11.3 Mixed H2=H1 Controller Design 204 11.3.1 State-Feedback Controller Design 204 11.3.2 Computational Algorithm 207 11.4 Numerical Example 207 11.5 Summary 211 12 Finite-Horizon H2=H1 Control of MJSs with Sensor Failures 213 12.1 Problem Formulation 214 12.2 H1 Performance 216 12.3 Mixed H2=H1 Controller Design 220 12.3.1 Controller Design 220 12.3.2 Computational Algorithm 224 12.4 Numerical Example 224 12.5 Summary 227 13 Finite-Horizon Control with ROSF 229 13.1 Problem Formulation 230 13.2 H1 And Covariance Performances Analysis 234 13.2.1 H1 Performance 234 13.2.2 Covariance Analysis 238 13.3 Robust Finite-Horizon Controller Design 240 13.3.1 Controller Design 240 13.3.2 Computational Algorithm 243 13.4 Numerical Example 243 13.5 Summary 244 14 Finite-Horizon H2=H1 Control with Actuator Failures 247 14.1 Problem Formulation 248 14.2 H1 Performance 251 14.3 Multi-Objective Controller Design 253 14.3.1 Controller Design 253 14.3.2 Computational Algorithm 256 14.4 Numerical Example 257 14.5 Summary 259 15 Conclusions and Future Topics 261 References 263. - Includes bibliographical references and index. - Print version record and CIP data provided by publisher | ||
| 520 | |a "Variance-Constrained Multi-Objective Stochastic Control and Filtering covers the latest research results and presents the state-of-the-art of control and filtering problems while taking multiple design objectives into consideration"-- | ||
| 650 | 0 | |a Automatic control |x Mathematics | |
| 650 | 0 | |a Stochastic processes | |
| 650 | 2 | |a Stochastic Processes | |
| 650 | 4 | |a Commande automatique ; Mathématiques | |
| 650 | 4 | |a Processus stochastiques | |
| 650 | 4 | |a TECHNOLOGY & ENGINEERING ; Engineering (General) | |
| 650 | 4 | |a Automatic control ; Mathematics | |
| 650 | 4 | |a Stochastic processes | |
| 700 | 1 | |a Wang, Zidong |d 1966- |e MitwirkendeR |4 ctb | |
| 700 | 1 | |a Bo, Yuming |e MitwirkendeR |4 ctb | |
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| publisher | Wiley |
| record_format | marc |
| spelling | Ma, Lifeng VerfasserIn aut Variance-constrained multi-objective stochastic control and filtering Lifeng Ma, Zidong Wang, Yuming Bo Chichester, West Sussex, United Kingdom Wiley 2015 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Machine generated contents note: Preface vii Acknowledgements ix List of Abbreviations xi 1 Introduction 1 1.1 Analysis and Synthesis of Nonlinear Stochastic Systems 2 1.1.1 Nonlinear Systems 3 1.1.2 Stochastic Systems 4 1.2 Multi-Objective Control and Filtering with Variance Constraints 5 1.2.1 Covariance Control Theory 5 1.2.2 Multiple Performance Requirements 7 1.2.3 Design Techniques for Nonlinear Stochastic Systems with Variance Constraints 9 1.2.4 A Special Case of Multi-Objective Design: Mixed H2/H1 Control/Filtering 11 1.3 Outline 12 2 Robust H1 Control with Variance Constraints 17 2.1 Problem Formulation 18 2.2 Stability, H1 Performance and Variance Analysis 20 2.2.1 Stability, H1 Performance Analysis 21 2.2.2 Variance Analysis 23 2.3 Robust Controller Design 27 2.4 Numerical Example 30 2.5 Summary 33 3 Robust Mixed H2=H1 Filtering 41 3.1 System Description and Problem Formulation 42 3.2 Algebraic Characterizations for Robust H2=H1 Filtering 44 3.2.1 Robust H2 Filtering 44 3.2.2 Robust H1 Filtering 50 3.3 Robust H2=H1 Filter Design Techniques 51 3.4 An Illustrative Example 60 3.5 Summary 62 4 Filtering with Missing Measurements 63 4.1 Problem Formulation 64 4.2 Stability and Variance Analysis 67 4.3 Robust Filter Design 71 4.4 Numerical Example 75 4.5 Summary 78 5 Robust Fault-Tolerant Control 87 5.1 Problem Formulation 88 5.2 Stability and Variance Analysis 90 5.3 Robust Controller Design 92 5.4 Numerical Example 98 5.5 Summary 103 6 Robust H2 SMC 105 6.1 The System Model 106 6.2 Robust H2 Sliding Mode Control 107 6.2.1 Switching Surface 107 6.2.2 Performances of the Sliding Motion 108 6.2.3 Computational Algorithm 114 6.3 Sliding Mode Controller 115 6.4 Numerical Example 116 6.5 Summary 118 7 Dissipative Control with Degraded Measurements 125 7.1 Problem Formulation 126 7.2 Stability, Dissipativity and Variance Analysis 129 7.3 Observer-Based Controller Design 134 7.3.1 Solvability of Multi-Objective Control Problem 134 7.3.2 Computational Algorithm 139 7.4 Numerical Example 140 7.5 Summary 142 8 Variance-Constrained H1 Control with Multiplicative Noises 145 8.1 Problem Formulation 146 8.2 Stability, H1 Performance, Variance Analysis 147 8.2.1 Stability 148 8.2.2 H1 performance 150 8.2.3 Variance analysis 152 8.3 Robust State Feedback Controller Design 153 8.4 A Numerical Example 156 8.5 Summary 157 9 Robust Finite-Horizon H1 Control 159 9.1 Problem Formulation 160 9.2 Performance Analysis 162 9.2.1 H1 Performance 162 9.2.2 Variance Analysis 164 9.3 Robust Finite Horizon Controller Design 167 9.4 Numerical Example 171 9.5 Summary 173 10 Finite-Horizon Filtering with Degraded Measurements 177 10.1 Problem Formulation 178 10.2 Performance Analysis 181 10.2.1 H1 Performance Analysis 181 10.2.2 System Covariance Analysis 186 10.3 Robust Filter Design 187 10.4 Numerical Example 190 10.5 Summary 191 11 Mixed H2=H1 Control with Randomly Occurring Nonlinearities: the Finite-Horizon Case 197 11.1 Problem Formulation 199 11.2 H1 Performance 200 11.3 Mixed H2=H1 Controller Design 204 11.3.1 State-Feedback Controller Design 204 11.3.2 Computational Algorithm 207 11.4 Numerical Example 207 11.5 Summary 211 12 Finite-Horizon H2=H1 Control of MJSs with Sensor Failures 213 12.1 Problem Formulation 214 12.2 H1 Performance 216 12.3 Mixed H2=H1 Controller Design 220 12.3.1 Controller Design 220 12.3.2 Computational Algorithm 224 12.4 Numerical Example 224 12.5 Summary 227 13 Finite-Horizon Control with ROSF 229 13.1 Problem Formulation 230 13.2 H1 And Covariance Performances Analysis 234 13.2.1 H1 Performance 234 13.2.2 Covariance Analysis 238 13.3 Robust Finite-Horizon Controller Design 240 13.3.1 Controller Design 240 13.3.2 Computational Algorithm 243 13.4 Numerical Example 243 13.5 Summary 244 14 Finite-Horizon H2=H1 Control with Actuator Failures 247 14.1 Problem Formulation 248 14.2 H1 Performance 251 14.3 Multi-Objective Controller Design 253 14.3.1 Controller Design 253 14.3.2 Computational Algorithm 256 14.4 Numerical Example 257 14.5 Summary 259 15 Conclusions and Future Topics 261 References 263. - Includes bibliographical references and index. - Print version record and CIP data provided by publisher "Variance-Constrained Multi-Objective Stochastic Control and Filtering covers the latest research results and presents the state-of-the-art of control and filtering problems while taking multiple design objectives into consideration"-- Automatic control Mathematics Stochastic processes Stochastic Processes Commande automatique ; Mathématiques Processus stochastiques TECHNOLOGY & ENGINEERING ; Engineering (General) Automatic control ; Mathematics Wang, Zidong 1966- MitwirkendeR ctb Bo, Yuming MitwirkendeR ctb 9781118929490 Erscheint auch als Druck-Ausgabe 9781118929490 |
| spellingShingle | Ma, Lifeng Variance-constrained multi-objective stochastic control and filtering Automatic control Mathematics Stochastic processes Stochastic Processes Commande automatique ; Mathématiques Processus stochastiques TECHNOLOGY & ENGINEERING ; Engineering (General) Automatic control ; Mathematics |
| title | Variance-constrained multi-objective stochastic control and filtering |
| title_auth | Variance-constrained multi-objective stochastic control and filtering |
| title_exact_search | Variance-constrained multi-objective stochastic control and filtering |
| title_full | Variance-constrained multi-objective stochastic control and filtering Lifeng Ma, Zidong Wang, Yuming Bo |
| title_fullStr | Variance-constrained multi-objective stochastic control and filtering Lifeng Ma, Zidong Wang, Yuming Bo |
| title_full_unstemmed | Variance-constrained multi-objective stochastic control and filtering Lifeng Ma, Zidong Wang, Yuming Bo |
| title_short | Variance-constrained multi-objective stochastic control and filtering |
| title_sort | variance constrained multi objective stochastic control and filtering |
| topic | Automatic control Mathematics Stochastic processes Stochastic Processes Commande automatique ; Mathématiques Processus stochastiques TECHNOLOGY & ENGINEERING ; Engineering (General) Automatic control ; Mathematics |
| topic_facet | Automatic control Mathematics Stochastic processes Stochastic Processes Commande automatique ; Mathématiques Processus stochastiques TECHNOLOGY & ENGINEERING ; Engineering (General) Automatic control ; Mathematics |
| work_keys_str_mv | AT malifeng varianceconstrainedmultiobjectivestochasticcontrolandfiltering AT wangzidong varianceconstrainedmultiobjectivestochasticcontrolandfiltering AT boyuming varianceconstrainedmultiobjectivestochasticcontrolandfiltering |