State and Parameter Estimation

  • Magdi S. Mahmoud
  • Madan G. Singh
Chapter
Part of the Communications and Control Engineering Series book series (CCE)

Abstract

The purpose of this chapter is to study the behaviour of discrete-time dynamical systems under the influence of external effects which can be described in a statistical way. It can be argued that all real systems operate in a stochastic environment where they are subject to noise (unknown disturbances) and, in addition, the controller has to rely, in practice, on imperfect measurements. The noise may arise due to unpredictable changes at the input end of the system, and/or due to inaccurate measurements at the output end. In either case, exact information about the state of the system is not available, and we should therefore seek methods to estimate the state of the system on the basis of statistically related data. This leads to the state estimation problem. In other applications, the coefficients of the models need to be determined on the basis of the input and output records which are corrupted by noise components. This defines the parameter estimation problem. Both these problems are examined in this chapter and techniques for their solutions are developed.

Keywords

Kalman Filter Random Vector Noise Process Error Covariance Matrix Measurement Record 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin, Heidelberg 1984

Authors and Affiliations

  • Magdi S. Mahmoud
    • 1
  • Madan G. Singh
    • 2
  1. 1.Electrical and Computer Engineering Dept.Kuwait UniversityKuwait
  2. 2.ManchesterUK

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