Indirect model reference adaptive fuzzy control of dynamic fuzzy-state space model

A parameter estimator is developed for a plant that can be represented by a dynamic fuzzy-state space model. The essential idea behind an online estimation is the comparison of the measured state with that 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 systems with 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