Abstarct: In this project, a PI-adaptive fuzzy controller for a class of uncertain nonlinear systems is proposed that aims to provide added robustness in the presence of large and fast but bounded uncertainties and disturbances. While the proposed approach requires the uncertainties to be bounded, it does not require this bound to be known. Adaptive control approaches claim to adapt system parameters against uncertainties, but only if these uncertainties change slowly enough. Alternatively, robust control methodologies claim to ensure system stability against uncertainties, but only if these uncertainties remain within known bounds. This is while, in reality, disturbances and uncertainties remain faithfully uncertain. Lyapunov analysis is used to prove stability of the proposed approach. Finally, Particle Swarm Optimization (PSO) is used to optimize the control design parameters, thus the performance of control system is improved. This method is implemented on a siso and mimo magnetic suspension system and its results have been evaluated.