Adaptive disturbance cancellation for a class of MIMO nonlinear Euler–Lagrange systems under input saturation. (January 2020) - Li, Jian; Du, Jialu
Abstract: In this paper, we develop an adaptive disturbance cancellation tracking control strategy with the asymptotically converging output tracking errors for a class of multi-input and multi-output (MIMO) nonlinear Euler–Lagrange systems with unknown time-varying disturbances under input saturation. The unknown time-varying disturbances are firstly described as the outputs of a multivariate linear unknown exosystem with unavailable regressor and regression parameter. To estimate the unavailable regressor, an observer is constructed, such that the disturbance cancellation is converted to an adaptive control problem. An auxiliary dynamic system (ADS) is employed to mitigate the effect of the input saturation. Then, a robust adaptive tracking control law is proposed incorporating the above and a robustifying term into the adaptive vectorial backstepping design tool. It is proven theoretically that the asymptotic convergence of the output tracking errors of Euler–Lagrange systems is achieved, while the uniform ultimate boundedness of the remaining signals of the resulting closed-loop control system is guaranteed. Simulation and comparison results on a two-link rigid manipulator and a scale model ship are presented to illustrate the effectiveness and the superiority of the proposed control scheme. Highlights: The disturbance cancellation is transformed into the adaptive control problem. The asymptotic convergence of the output tracking errors is achieved. Both disturbances and input saturation are considered in the control design.