Advertisement

Estimators for Uncertain Dynamic Systems

  • A. I. Matasov

Part of the Mathematics and Its Applications book series (MAIA, volume 458)

Table of contents

  1. Front Matter
    Pages i-x
  2. A. I. Matasov
    Pages 1-78
  3. A. I. Matasov
    Pages 79-159
  4. A. I. Matasov
    Pages 239-313
  5. Back Matter
    Pages 405-422

About this book

Introduction

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 leads to the necessity to construct the estimators for corresponding dynamic systems. The estimators recover the required information about system state from mea­ surement data. An attempt to solve the estimation problems in an optimal way results in the formulation of different variational problems. The type and complexity of these variational problems depend on the process model, the model of uncertainties, and the estimation performance criterion. A solution of variational problem determines an optimal estimator. Howerever, there exist at least two reasons why we use nonoptimal esti­ mators. The first reason is that the numerical algorithms for solving the corresponding variational problems can be very difficult for numerical imple­ mentation. For example, the dimension of these algorithms can be very high.

Keywords

algorithms complexity control control system filter material model

Authors and affiliations

  • A. I. Matasov
    • 1
  1. 1.Faculty of Mechanics and Mathematics, Department of Applied Mechanics and ControlM.V. Lomonosov Moscow State UniversityMoscowRussia

Bibliographic information

Industry Sectors
Pharma
Materials & Steel
Automotive
Chemical Manufacturing
Electronics
IT & Software
Telecommunications
Energy, Utilities & Environment
Aerospace
Oil, Gas & Geosciences
Engineering