Fixed-Time Control for a Class of Unknown Nonlinear Affine Systems and Its applications to a Lithography Machine

摘要

The fixed-time control problems of a class of unknown nonlinear affine systems subject to external disturbances, unknown input dead zone and output constraints are considered in this paper. The fixed-time state feedback control strategy with adaptive neural networks (NNs) is designed. In the control design, the log-type barrier Lyapunov function (BLF) is chosen to handle the system output constraint. Then, neural networks(NNs) are applied to compensate for the adverse impact of unknown input dead zone and deal with system uncertainties. The novel virtual controllers and novel online updating laws of neural network weights are proposed to fulfill the fixed-time stability of closed-loop systems. The boundednesses of all the signals in closed-loop system are demonstrated via Lyapunov stability theory. Eventually, the experiment performed on the lithography machine is served to demonstrate good performance.