Robust adaptive control of uncertain nonlinear systems with unmodeled dynamics using command filter

This article proposes a robust adaptive controller design method for strict feedback nonlinear systems with unmodeled dynamics and input saturation. By using command filters, the explosion of complexity is obviated. The influence of filter errors bought in by command filters is eliminated by introducing compensating signals. Moreover, by skillfully constructing an nth-order auxiliary dynamic system, the effect of input saturation is avoided, where the disadvantages of conventional methods based on the hyperbolic tangent function are overcome. To tackle the effect of unmodeled dynamics which can destroy the performance and even destabilize the system, based on input-to-state stability theory, a dynamic signal is designed. Finally, the Lyapunov theory-based stability analysis proves that all the closed-loop signals are uniformly ultimately bounded. The effectiveness of the proposed controller design scheme is verified in simulation experiments.