| Popis: |
In this paper, a fuzzy-based adaptive scheme for model reference adaptive control (MRAC) is proposed. In MRAC, the choice of proper adaptive gain (γ) is a cumbersome job, and it is usually done by trial and error method. To eliminate this shortcoming, here fuzzy logic is incorporated in the control loop to tune the adaptive gain (γ). In design of model reference adaptive control, MIT rule is followed, where a cost function is defined as a function of error between the outputs of the plant and the reference model, and the controller parameters are adjusted in such a way so that this cost function is minimized. The experiments on the different second-order linear/nonlinear systems are illustrated to show the merits of the proposed fuzzy-based model reference adaptive control (FMRAC) scheme over the MRAC. The performances of the proposed control algorithms are evaluated and shown by means of simulation on MATLAB and Simulink. |
