Control and Dynamic Systems V27

Preface

A New Approach to Adaptive Control

I. Introduction

II. Conceptual Approaches to Adaptive Control: An Overview

III. Formulation of a General Class of Adaptive Control Problems for Linearized Dynamical Systems

IV. Solution of the Adaptive Control Problem of Eqs. (9) and (10) for the Case ([δf [δC(t)], [δF(t)])=0

V. Some Worked Examples Using the New Adaptive Controller, (47) and (50)

VI. Generalization of the New Approach: Consideration of Nonzero [δB], [δF], [δC]

VII. Rapprochement with Traditional Adaptive Control Design

VIII. Summary and Conclusions

IX. Appendix A: Analysis of the Singular Condition Associated with Eq. (34)

X. Appendix B: Optimal Initial Conditions for Full-Order Observers

References

Biological Systems: A General Approach

I. Introduction

II. General Framework for Endodynamic Processes

III. General Method for the Mathematical Formulation of Endodynamic Models

IV. An Example of the Formation of a Specific Model

References

Optimal Control for Air Conditioning Systems: Large-Scale Systems Hierarchy

I. Introduction

II. Computational Competence

III. Optimal Designing

IV. Optimal Operation

V. Optimal Computational Synthesis

VI. Universal Control Corollary

VII. Case Study and Conclusion

Appendix A: HVAC Model Recursion

Appendix B: DP System Exposition

Appendix C: Kalman Filter

Appendix D: TEAM Theoretic Synthesis

Appendix E: Dimensional Grouping

Appendix F: Computational Routines

References

A Linear Programming Approach to Constrained Multivariable Process Control

I. Introduction

II. Review of the Design and Properties of Linear Inferential Control Systems

III. The Structure of Constrained Control Systems

IV. Controller Formulations for Single Input-Single Output Systems

V. Controller Formulation for Multiinput, Multioutput Systems

VI. Constrained Controller Linear Program

VII. Examples

VIII. Conclusions

References

Techniques for the Identification of Distributed Systems Using the Finite Element Approximation

I. Introduction

II. Parameter Identification Problem

III. Infinite-Dimensional Identification

IV. Finite-Element Approximation

V. Finite-Dimensional Identification

VI. Numerical Results

VII. Conclusion

References

An Identification Scheme for Linear Control Systems with Waveform-Type Disturbances

I. Introduction

II. Problem Description

III. The Proposed Algorithm

IV. Input Signal Design

V. Maximum Likelihood Method

VI. Illustrative Examples

VII. Conclusions

References

Realizations for Generalized State Space Singular Systems

I. Introduction

II. Problem Formulation

III. Minimal Realizations for Single Input-Single Output Singular Systems

IV. Standard Forms for Non-c-Controllable and/or Non-e-Observable Singular Systems

V. Some Basic State Space Realizations for Multivariable Singular Systems

VI. Irreducible MFD's and Minimal Realizations

VII. Realization via Markov Parameters

VIII Realization via Markov Parameters and Moments

IX. Illustrative Examples

X. Conclusions

References

Discrete Systems with Multiple Time Scales

I. Introduction

II. Discrete Multiple-Time-Scale Systems

III. Feedback Control Design

IV. Linear Quadratic Regulators

V. Discussion and Concluding Remarks

References

Index