Estimators for Uncertain Dynamic Systems

Estimators for Uncertain Dynamic Systems by A.I. Matasov.

When solving the control and design problems in aerospace and naval engi­ neering, energetics, economics, biology, etc., we need to know the state of investigated dynamic processes. The presence of inherent uncertainties in the description of these processes and of noises in measurement devices lead...

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Bibliographic Details
Main Author: Matasov, A.I (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 1998.
Edition:1st ed. 1998.
Series:Mathematics and Its Applications ; 458
Springer eBook Collection.
Subjects:
Electrical engineering.
System theory.
Mechanical engineering.
Calculus of variations.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 1. Guaranteed Parameter Estimation
  • 1. Simplest Guaranteed Estimation Problem
  • 2. Continuous Measurement Case
  • 3. Linear Programming
  • 4. Necessary and Sufficient Conditions for Optimality
  • 5. Dual Problem and Chebyshev Approximation
  • 6. Combined Model for Measurement Noise
  • 7. Least-Squares Method in Guaranteed Parameter Estimation
  • 8. Guaranteed Estimation with Anomalous Measurement Errors
  • 9. Comments to Chapter 1
  • 10. Excercises to Chapter 1
  • 2. Guaranteed Estimation in Dynamic Systems
  • 1. Lagrange Principle and Duality
  • 2. Uncertain Deterministic Disturbances
  • 3. Conditions for Optimality of Estimator
  • 4. Computation of Estimators
  • 5. Optimality of Linear Estimators
  • 6. Phase Constraints in Guaranteed Estimation Problem
  • 7. Comments to Chapter 2
  • 8. Excercises to Chapter 2
  • 3. Kalman Filter in Guaranteed Estimation Problem
  • 1. Level of Nonoptimality for Kaiman Filter
  • 2. Bound for the Level of Nonoptimality
  • 3. Derivation of Main Result
  • 4. Kaiman Filter with Discrete Measurements
  • 5. Proofs for the Case of Discrete Measurements
  • 6. Examples for the Bounds of Nonoptimality Levels
  • 7. Comments to Chapter 3
  • 8. Excercises to Chapter 3
  • 4. Stochastic Guaranteed Estimation Problem
  • 1. Optimal Stochastic Guaranteed Estimation Problem
  • 2. Approximating Problem. Bound for the Level of Nonoptimality
  • 3. Derivation of Main Result for Stochastic Problem
  • 4. Discrete Measurements in Stochastic Estimation Problem
  • 5. Examples for Stochastic Problems
  • 6. Kaiman Filter under Uncertainty in Intensities of Noises
  • 7. Comments to Chapter 4
  • 8. Excercises to Chapter 4
  • 5. Estimation Problems in Systems with Aftereffect
  • 1. Pseudo-Fundamental Matrix and Cauchy Formula
  • 2. Guaranteed Estimation in Dynamic Systems with Delay
  • 3. Level of Nonoptimality in Stochastic Problem
  • 4. Simplified Algorithms for Mean-Square Filtering Problem
  • 5. Control Algorithms for Systems with Aftereffect
  • 6. Reduced Algorithms for Systems with Weakly Connected Blocks
  • 7. Comments to Chapter 5
  • 8. Excercises to Chapter 5.

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