A multiestimation adaptive control scheme which incorporates model reduction issues

A multiestimation-based adaptive control scheme is presented for a plant with known poles and unknown zeros. The plant is decomposed in several first order filters with unknown scalar numerators. The scheme chooses in real time the estimator/controller pair possessing the best performance according to an identification performance index by implementing a switching rule between estimators. Each reduced model is obtained by using a different combination of the first order filters. The switching rule is subject to a minimum residence time at each identifier/adaptive controller parameterization for closed-loop stabilization purposes.