Adaptation algorithm for robust fuzzy controller of nonlinear uncertain systems

This paper investigates a robust adaptive fuzzy controller for a nonlinear uncertain and perturbed system. The control law is obtained from a basic feedback controller using the nominal model supervised by two signals. The first signal computed from an adaptive fuzzy system to eliminate the model uncertainties. The updating of its adjustable parameters is done using a PID law, which is deduced from the stability analysis. The second signal, computed from Riccati like equation, attenuates the effects of both external disturbances and residual errors. The global stability and the robustness are provided using the Lyapunov theory. An illustrative example is considered to show the soundness of the proposed method.