An indirect model reference adaptive fuzzy control for SISO Takagi-Sugeno model

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the online estimation is the comparison of the measured state with the state of an estimation model whose structure is the same as that of the parametrized model. Based on the parameter estimation scheme, an indirect model reference adaptive fuzzy control scheme is proposed to provide asymptotic tracking of a reference signal for the systems having uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.