In this paper, a finite-time composite adaptive fuzzy control approach is proposed for position tracking of permanent magnet synchronous motors (PMSMs) with uncertain parameters and load torque disturbances. Based on the approximate ability of fuzzy logic systems (FLSs), a novel finite-time adaptive fuzzy control is developed, where dynamic surface control with error compensation mechanism is incorporated in the control design. A serial-parallel estimation model of PMSM is established. The prediction error between PMSM and the serial-parallel estimation model is utilized to construct the adaptive law of FLSs, which can improve the approximate accuracy of FLSs. Moreover, by introducing a new fuzzy adaptive law, the algebraic loop problem in the existing backstepping based control approaches is overcome. It is proven that all signals of closed-loop systems are uniformly ultimately bounded, and the position tracking error can converge to a small neighborhood of the origin in finite time. Finally, the simulation results are presented to show the effectiveness of the proposed control approach, and some comparisons are given to show the rapid and accurate position tracking performance.