This paper presents a new adaptive terminal sliding mode tracking control design for a class of nonlinear systems using fuzzy logic system. The terminal sliding mode control (TSM) was developed to provide faster convergence and higher-precision control than the linear hyperplane-based sliding control. However, the original TSM encountered singularity problem with discontinuous control action. Moreover, a prior knowledge about the plant to be controlled is required. The proposed controller combines a continuous non-singular TSM with an adaptive learning algorithm and fuzzy logic system to estimate the dynamics of the controlled plant so that closed-loop stability and finite-time convergence of tracking errors can be guaranteed. The performance of the proposed control strategy is evaluated through the control of a two-link rigid robotic manipulator. Finally, the effectiveness of the proposed scheme is demonstrated through the control of the ankle and knee movements in paraplegic subjects using functional electrical stimulation. Simulation and experimental results verify that the proposed control strategy can achieve favorable control performance with regard to system parameter variations and external disturbances.