Sampled-data-based uncertainty compensation control for a class of continuous-time nonlinear MIMO systems

Abstract

This paper proposes a sampled-data-based uncertainty compensation control strategy for a class of continuous-time multi-input multi-output nonlinear systems with strong coupling uncertainties. Unlike observer-based uncertainty compensation control methods, this paper utilizes the true value of the total disturbance at an instant in the previous sampling interval rather than its observed value in the last sampling time to compensate for the total disturbance. The total disturbance considered in this paper is composed of the unmodeled nonlinear coupling dynamics and external disturbance. The continuous-time systems and the sampled-data feedback control make up a hybrid closed-loop control system, which, together with the strongly coupled nonlinear uncertainties of the system, brings a significant hurdle to verifying the stability and convergence of the closed-loop control system. A new eigenvalue-and-series-based analysis method is proposed to overcome this hurdle. It is proved that when the tracking target is a bounded function, the tracking error can be arbitrarily small when the sampling period is small enough. Furthermore, when the tracking target is a constant and the nonlinear term is time-invariant, the tracking error converges to zero as time tends to infinity. Numerical results on the attitude control for a 2-DOF UAV validate the effectiveness and merits of the proposed method.