An indirect adaptive fuzzy approach for uncertain nonlinear SISO systems with disturbances

In this paper, an indirect adaptive fuzzy approach is proposed to achieve robust tracking for a class of uncertain nonlinear single input single output (SISO) systems with external disturbances. Adaptive fuzzy control, adaptive fuzzy identification and attenuation technique are incorporated together for the control objective. Based on the existing robust adaptive fuzzy control scheme, adaptive laws are modified by system modeling error to adjust the estimation parameters converge to their optimal values, which in turn improves the control to guarantee the convergence of output tracking error and modeling error. The effect of both optimal matching error and external disturbance on the controlled system can be attenuated. Desired performance is obtained under a low attenuation level, so the control effort can be enormously saved. Some simulation results are given to illustrate the effectiveness of the proposed approach.