Radial basis function sliding-mode control for the Laser alloying process

Abstract

Since the Laser alloying process system has nonlinear coupling and time varying dynamic characteristics, it is very difficult to establish an accurate process model for designing model-based controller. Hence, an adaptive radial basis function sliding-mode control is proposed by combining the advantages of adaptive neural network and sliding-mode control strategies. It has on-line learning ability to deal with the system's nonlinear and time-varying uncertainties by adjusting the control parameters. Two adaptive radial basis function sliding-mode controllers are designed for tuning the Laser power and the traverse velocity simultaneously to tackle the absorptivtiy and geometrical variations of the work pieces. The simulation results show that the good surface lapping performance is achieved by using this intelligent control strategy.