Robust tracking control for uncertain MIMO nonlinear systems with input saturation using RWNNDO

In this paper, the robust tracking control scheme is proposed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with input saturation and unknown external disturbance based on the recurrent wavelet neural network disturbance observer (RWNNDO) and the backstepping technique. And then, the developed robust tracking control scheme is applied to an unmanned aerial vehicle (UAV) system. To handle the input saturation, a hyperbolic tangent function and a Nussbaum function are employed, and the dynamic surface method is applied to solve the problem of “explosion of complexity” in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed control scheme for uncertain MIMO nonlinear systems

Robust tracking control for uncertain MIMO nonlinear systems with input saturation using RWNNDO

In this paper, the robust tracking control scheme is proposed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with input saturation and unknown external disturbance based on the recurrent wavelet neural network disturbance observer (RWNNDO) and the backstepping technique. And then, the developed robust tracking control scheme is applied to an unmanned aerial vehicle (UAV) system. To handle the input saturation, a hyperbolic tangent function and a Nussbaum function are employed, and the dynamic surface method is applied to solve the problem of “explosion of complexity” in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed control scheme for uncertain MIMO nonlinear systems