This paper proposes a novel method of on-line modeling and control through the Takagi-Sugeno (T-S) fuzzy-neural model for a class of general n-link robot manipulators. Compared with previous meth-ods, this paper has two unique aspects: first, a more general n-link robot system using on-line adaptive T-S fuzzy-neural controller is investigated, and sec-ond, the complete proof of the controller is given. The general robot systems are linearized via the mean value theorem, and then the T-S fuzzy-neural model can approximate the linearized system. Also, we pro-pose an on-line identification algorithm and put sig-nificant emphasis on robust tracking controller de-sign using an adaptive scheme for the robot systems. Finally, an example including two cases is provided to demonstrate the feasibility and robustness of the proposed method.