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Robust Parameter Estimation

  • Aniruddha Datta
Part of the Advances in Industrial Control book series (AIC)

Abstract

In the last two chapters, we have designed and analyzed on-line parameter estimators and adaptive control schemes under the assumption that there are no modelling errors. Such an assumption is unrealistic since in the real world, modelling errors such as disturbances, sensor noise, unmodelled dynamics, nonlinearities, etc. will most likely be present. The aim of this chapter is to first examine how the on-line parameter estimators of Chapter 4 behave in the presence of modelling errors. Thereafter we will explore several approaches for correcting possible unsatisfactory behaviour. Parameter estimators that can behave satisfactorily even in the presence of modelling errors are called Robust Parameter Estimators. Thus this chapter is primarily concerned with the design and analysis of robust parameter estimators.

Keywords

Modelling Error Parameter Estimator Dead Zone Gradient Projection Method Unmodelled Dynamic 
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 London 1998

Authors and Affiliations

  • Aniruddha Datta
    • 1
  1. 1.Department of Electrical EngineeringTexas A & M UniversityCollege StationUSA

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