A Multipredictor-Based LQ Self-Tuning Controller

The problem of controlling a plant with unknown and slowly time-varying para meters is considered. In order to make the resulting adaptive controller robust against model mismatching, future bahaviour of the plant is not described by a single predictive model but by a number of different predictive models whose parameters are independently estimated. Attention is devoted to developing recursive least-squares (RLS) estimators consisting of UD covariance filters or square root information filters that, by exploiting the relationship among different regressors, keep the overall numerical burden as small as possible