Nonlinear Filtering: Concepts and Engineering Applications

Description

Nonlinear Filtering covers linear and nonlinear filtering in a comprehensive manner, with appropriate theoretic and practical development. Aspects of modeling, estimation, recursive filtering, linear filtering, and nonlinear filtering are presented with appropriate and sufficient mathematics. A modeling-control-system approach is used when applicable, and detailed practical applications are presented to elucidate the analysis and filtering concepts. MATLAB routines are included, and examples from a wide range of engineering applications - including aerospace, automated manufacturing, robotics, and advanced control systems - are referenced throughout the text. Content: PrefaceAcknowledgementsAuthorsIntroductionSection I Mathematical Models, Kalman Filtering and H-Infinity Filters1. Dynamic System Models and Basic Concepts2. Filtering and Smoothing3. Hâ Filtering4. Adaptive FilteringSection II Factorization and Approximation Filters5. Factorization Filtering6. Approximation Filters for Nonlinear Systems7. Generalized Model Error Estimators for Nonlinear SystemsSection III Nonlinear Filtering, Estimation and Implementation Approaches8. Nonlinear Estimation and Filtering9. Nonlinear Filtering Based on Characteristic Functions10. Implementation Aspects of Nonlinear Filters11. Nonlinear Parameter Estimation12. Nonlinear ObserversSection IV Appendixes - Basic Concepts and Supporting MaterialAppendix A: System Theoretic Concepts - Controllability, Observability, Identifiability and EstimabilityAppendix B: Probability, Stochastic Processes and Stochastic CalculusAppendix C: Bayesian FilteringAppendix D: Girsanov TheoremAppendix E: Concepts from Signal and Stochastic AnalysesAppendix F: Notes on Simulation and Some AlgorithmsAppendix G: Additional ExamplesIndex