A Model Reference Adaptive Control Based on On-line FRIT Approaches Using a Normalized Recursive Least Square Method*

The model reference adaptive control (MRAC) designed based on the fictitious reference iterative tuning (FRIT) approach in an on-line manner has recently been proposed. The FRIT method is an off-line control parameters tuning method so that the plant output could follow the prescribed reference model output from one-shot experimental input-output data with no need for help from plant model. The MRAC based on on-line FRIT employs a normalized gradient method for the adaptive adjusting law. However, since the gradient algorithm suffers from slow convergence rate. it is desirable to employ an adaptive adjusting law with fast convergence rate. The paper gives a normalized recursive least square (RLS) method for the adaptive adjusting law for the model reference adaptive control based on an on-line FRIT approach. In the traditional MRAC, the RLS method shows faster convergence rate than the gradient algorithm. The paper also proves the boundedness of all signals in the closed loop system as well as asymptotically tracking the reference model output. An effectiveness of the proposed method is shown through a numerical example.