Decentralized/distributed control and dynamic systems Part 2 of 3 /
Control and Dynamic Systems V23.
| Corporate Author: | |
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| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Language Notes: | English. |
| Published: |
Orlando, Fla. :
Academic Press,
1986.
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| Series: | Control and dynamic systems ;
v. 23. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Front Cover; Decentralized/Distributed Control and Dynamic Systems; Copyright Page; Table of Contents; CONTRIBUTORS; PREFACE; Chapter 1. Multimodeling, Singular Perturbations, and Stochastic Decision Problems; I. Introduction; II. Modeling and Control of Stochastic Singularly Perturbed Systems; III. Multimodeling by Singular Perturbations; IV. Multiagent Decision Problems; V. Conclusions; References; Chapter 2. Resource Management of Time-Critical Data Processing Systems; I. Introduction; II. Single-Processor Load Dynamics; III. Performance Measures; IV. Control Strategies; V. BMD Example
- VI. Global Object ReallocationVII. Summary and Conclusion; Appendix; References; Chapter 3. Parametrical Optimization Approach for Decentralized Regulation of Discrete Systems; I. Introduction; II. Mathematical Formulation: The Gradient Matrix; III. Numerical Algorithm for the Decentralized Gain Determination; IV. Determination of a Stabilizing Initial Gain; V. Conclusion; References; Chapter 4. Decentralized Optimal Control for Large-Scale Interconnected Systems; I. Introduction; II. Decentralized Optimal Control Problem; III. Single-Input Subsystems; IV. Multi-Input Subsystems
- V. Illustrative ExampleVI. Conclusion; Appendix; References; Chapter 5. Techniques in Model Reduction for Large-Scale Systems; I. Introduction; II. The Theory of Aggregation; III. The Dominant Pole Approach; IV. Pade-Type Approximant and Partial Realization; V. Routh Approximation; VI. Perturbation Method; VII. Error Minimization Approach; VIII. Applications; IX. Conclusions; References; Chapter 6. Optimal Estimation Theory for Distributed Parameter Systems; I. Introduction; II. System Modeling; III. Description of the Estimation Problems; IV. Wiener-Hopf Theorem
- V. Derivation of the Optimal PredictorVI. Derivation of the Optimal Filter; VII. Derivation of the Optimal Smoothing Estimator; VIII. Optimal Sensor Location; IX. Conclusions; References; Chapter 7. The Linear-Quadratic Control Problem; I. Introduction; II. Preliminaries and Problem Formulation; III. First-Order Necessary Conditions for Optimality; IV. Solution of the Linear-Quadratic Problem Using the First-Order Necessary Conditions-A Transition Matrix Approach; V. The Symplectic Property of the Transition Matrix of Hamiltonian Systems; VI. The Riccati Matrix Differential Equation
- VII. A Canonical Transformation of the Hamiltonian SystemVIII. Necessary and Sufficient Condition for the Positivity of the Quadratic Cost Criterion; IX. The Linear-Quadratic Problem with Linear Terminal Constraints- A Transition Matrix Approach; X. Normality and Controllability for the Linear-Quadratic Problem; XI. Necessary and Sufficient Condition for the Positivity of the Terminally Constrained Quadratic Cost Criterion; XII. Further Properties of the Solution of the Matrix Riccati Equation; XIII. The Linear Regulator Problem; XIV. Summary and Extensions; References