Control and Dynamic Systems V19

Contents Contributors Preface Contents of Previous Volumes Exact and Approximate State Estimation Techniques for Nonlinear Dynamic Systems I. General Introduction II. State Estimation for Discrete Time-Delayed Systems with Additive White Noise III. State Estimation for Discrete Time-Delayed Systems with Correlated Noise IV. Nonlinear Estimation for Discrete Time-Delayed Systems with Colored Noise V. State Estimation for Nonlinear Distributed-Parameter Systems (DPS) Involving Multiple Delays VI. Exact and Approximate Minimum-Variance Filtering for Nonlinear Continuous Systems VII. Conclusions References Synthesis and Performance of Bayesian Estimators 1. Introduction II. Quality of Bayesian Estimators in Open Loop III. Asymptotic Behavior of Bayesian Estimators in Closed Loop IV. Duality between Robust Control and Bayesian Identification V. Numerical Examples Appendix References Advances in Computational Efficiencies of Linear Filtering Leonard Chin The Purpose I. Introduction II. System Model, Notations, and Conventions III. Algorithm Descriptions IV. Computer Burdens V. Conclusion Appendix References Design of Real-Time Estimation Algorithms for Implementation in Microprocessor and Distributed Processor Systems I. Introduction II. Programming for Real-Time Distributed Systems III. Control of Real-Time Processes IV. Algorithmic and Procedural Issues in Design of Real-Time Estimators V. Decomposition of a Kalman Filter into Concurrent Processes VI. Summary and Conclusions Appendix I Appendix II Appendix III References Global Approximation for Nonlinear Filtering with Application to Spread Spectrum Ranging I. Introduction II. Organization III. Some Global Approximations for Nonlinear Filtering and Their Applications Appendix References Index