The design of neural network controller of a class of nonlinear systems with unknown actuator hard-nonlinear

The problem of actuator hard-nonlinear appears in many practical control systems especially the plant with serious nonlinearity and need run in large rang situations. If the controller is designed only with conventional linearly techniques, the presence of hard-nonlinear can debase the performance even lead the closed-loop system to an unstable behavior. In this paper, neural net-based actuator hard-nonlinear compensation scheme with on-line weights tuning law for the nonlinear systems in Brunovsky form is presented to decrease the influence of hard-nonlinear for improving output tracking. Simulation example is given to illustrate the effectiveness of this method.