A Constitution of a Model Reference Adaptive Control, System by Learning Control Method
Kazuhisa OBA, Toshiaki KURETAKE, Kazuo INOUE
Model reference adaptive control system (MRACS) theory is an effective method for dealing with unknown systems. When an MRACS is constituted, current parameters and the state variables of the unknown plant are usually estimated to adjust control parameters. But there are some problems when they are estimated.
This paper presents a design method of an MRACS by an approximately inverse functional compensator. The system is constructed from a viewpoint of a learning control method and is, based on an exact model matching (EMM) technique. The system designed by the proposed method can decrease the control error between the output of the plant and the reference model without estimation of the parameters and the state variables. The, learning control method is used for the plant which can be controlled repeatedly. In the frequency zone of signals passing through the plant and the reference model, the approximately inverse functional compensator has inverse properties of the reference model.