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A kind of adaptive sliding model control algorithm is developed to solve and improve the mathematical model dependency and un-modeled dynamics of a controlled system. The control strategy derived from a kind of data-driven control method in essence,thereby the input and output data are utilized by the controller with no information about the control system model. Theoretical analysis proves that this proposed control algorithm can improve the utilization of the estimated pseudo partial derivative information and accelerate the velocity of the convergence. The stability of the control system is further verified by rigorous mathematical analysis.This new discrete-time nonlinear systems model-free control algorithm obtained better control performance through the simulations for the linear motor position and the information tracking speed,which also achieved robust and accurate traceability.
A kind of adaptive sliding model control algorithm is developed to solve and improve the mathematical model dependency and un-modeled dynamics of a controlled system. Thus the control strategy derived from a kind of data-driven control method in essence, thus the input and output data are utilized by the controller with no information about the control system model. Theoretical analysis proves that this proposed control algorithm can improve the utilization of the estimated pseudo partial derivative information and accelerate the velocity of the convergence. The stability of the control system was further verified by rigorous mathematical analysis. This new discrete-time nonlinear systems model-free control algorithm obtained better control performance through the simulations for the linear motor position and the information tracking speed, which also enable robust and accurate traceability.