Summary: A systematic design methodology for integrating fuzzy modeling and adaptive control is proposed and developed in this paper. This design procedure provides a real-time system identification scheme using less fuzzy rules than those of other existing methods, due to a new sliding-mode learning mechanism embedded in the identified model, which has robust stability not only for stabilization of the identified system but also for trajectory tracking control. The integration of the identification and the adaptive control schemes ensures the suggested methodology to be overall advantageous and more attractive as compared to other existing, usually separated, design approaches. Two typical complex systems are simulated showing some convincing stabilization and tracking performance of the proposed integrated fuzzy system.