Intelligent mechatronic systems rely on intelligent control methods. Fuzzy logic is widely used for approximating the decision-making process of humans in realizing intelligent mechatronic systems. An approach of adaptive fuzzy modeling based parameter optimization fuzzy tree (POFT) for a class of nonlinear time-invariant systems is presented in this chapter. A fuzzy state equation model based on the adaptive fuzzy tree algorithm is developed, which is used to partition the workspace of a nonlinear mechatronic system adaptively. The model obtained by this method has high accuracy and low computational cost. As an illustrative example, the method is applied to the modeling and control problem of the Furuta pendulum. The numerical simulation presented here shows that the method is effective.