Some issues on the practical use of recursive least squares identification in self-tuning control

Abstract

System identification plays an extremely important role in the self-tuning controller. As the recursive least squares (RLS)identification technique has the advantages of simple calculation and good convergence properties, it is the preferred technique for use in the design of the self-tuning controllers. However, use of RLS identification in a real-time environment does raise some problems such as the speed of parameter convergence, identification going to ‘sleep’, covariance matrix ‘blow up’, biased identification, etc. This paper deals with the problems which may arise in the practical use of the RLS identification technique. These issues are the summary of several years' experience of designing self-tuning controllers with RLS identification technique for power system applications. Although some of these issues are difficult to analyse, they are quite effective in dealing with the practical problems.