Control and Dynamic Systems V29

Contributors

Preface

New Insights in the Numerical Reliability Properties of Existing Kalman Filter Implementations

I. Introduction

II. Notation and Preliminaries

III. Error Analysis of the Propagation of Round-Off Errors

IV. Error Analysis of the Propagation of Modeling Errors

V. Error Analysis of the Propagation of Discretization Errors

VI. Experimental Evaluation of the Different Kalman Filters

VII. Comparison of the Different Filters

VIII. Concluding Remarks

Appendix A: Error Analysis of Some Basic Linear Algebra Problems

Appendix B: The Skew Householder Transformation

References

Algorithms for System Fault Detection through Modeling and Estimation Techniques

I. Introduction

II. The Fault Detection Problem

III. Various Approaches to Fault Detection

IV. Failure Accommodation

V. Conclusions

References

Arranging Computer Architectures to Create Higher Performance Controllers

I. Introduction

II. Computer Architectures—They're Not All the Same!

III. Increasing the Power of the Host Computer

IV. Using Array Processors to Cut Computation Time

V. Using Different Computer Subsystems to Separate Real-Time Events from Non-Real-Time Events

VI. Using Intelligent Devices to Share the Real-Time Burden

VII. Using Intelligent Interfaces to Increase Communication Speeds

VIII. Application Example: Helicopter Controller Used to Suppress Vibration and to Augment Stability

IX. Concluding Remarks

References

Computational Techniques in Angle-Only Tracking Filtering

I. Introduction

II. Observability of Single-Sensor Angle-Only Tracking

III. Angular Sensitivity

IV. Additional Information

V. Kalman Filters and Maneuvering Target Tracking Techniques

VI. Some Other Useful AOT Filtering Techniques

VII. Discussion, Conclusion, and Further Research Topics

References

Gradient Projection Methods for Systems Optimization Problems

I. Introduction

II. Unconstrained Variable Metric Gradient Methods

III. Ordinary Gradient Projection Methods

IV Two Metric Gradient Projection Methods

V. Newtonian Scaling for Optimal Control Problems

References

Optimal Control, Estimation, and Compensation of Linear Discrete-Time Systems with Stochastic Parameters

I. Introduction

II. Stability, Stabilizability, and Detectability

III. Optimal Control

IV. Optimal Estimation

V. Optimal Compensation

VI. Conclusions

References

An Algorithm for the Approximation of Multivariable Linear Systems

I. Introduction

II. Least-Squares Approximation

III. A Recursive Algorithm

IV. A Simulation Example

V. Conclusions

Appendix A: Proof of Lemma 3

Appendix B: Proof of Lemma 4

Appendix C: Proof of Validity of the Algorithm

References

Algorithms for Discrete Time Adaptive Control of Rapidly Time-Varying Systems

I. Introduction

II. Recursive Parameter Estimation for Time-Varying Systems

III. Adaptive Control

IV. Convergence Considerations

V. Conclusion

Appendix

References

Algorithms for Decentralized Hierarchical Systems with Application to Stream Water Quality

I. Introduction

II. The Decentralized Optimal Control Problem

III. Hierarchical Algorithms

IV. Applications to Stream Water Quality

V. Conclusions

References

Index