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Fuzzy control has been successfully applied in many cases to which conventional control algorithms are difficult to be applied. Recently, it was proven that fuzzy systems are capable of approximating any real continuous function to arbitrary accuracy. This result motivates us to use the fuzzy identifiers for nonlinear dynamic systems and then design the fuzzy supervised nonlinear PID controller based on the fuzzy system. There are two main objectives in this paper: (1) We use the Takagi and Sugeno's fuzzy models as an identifier for nonlinear dynamic systems, and derive the identification algorithm, (2) the fuzzy supervisor design method for tracking control is proposed based on this fuzzy system. In order to improve the dynamic response of the closed loop fuzzy model, the optimization of the performance of the fuzzy supervisor will be considered. To prove the potential applications of the proposed strategy, simulation was carried out for the speed control of a DC motor with serial excitation and a first order nonlinear process.