Comparative Analysis of MRAFC Controller MRAC Controller

In this paper model reference adaptive based fuzzy controller is presented .Model reference adaptive controller is very common approach to control linear systems, as it is simple to apply. However, the performance of the linear model reference adaptive control weakens up when the system becomes nonlinear. In this paper, the MRAFC has fast learning features and it has good tracking results even when various changes are made in its system parameters. Model reference adaptive control here consists of a fuzzy based controller and a knowledge based modifier. In this paper the plant model and the reference model responses are studied and the error so obtained is being minimized with the help of MRAFC ..The various graphs have been obtained and the study have been done .Results were obtained via simulation software results shows that the MRAFC system has good performance and it can easily adapt to numerous of variations made in the controlled object.