Design of radial basis function neural networks controller based on sliding surface for a coupled tanks system

In this paper, the level control of coupled tanks is investigated. We developed a radial basis function neural networks based on sliding mode for control of coupled tanks system. In this study we used sliding surface and generalized learning rule to eliminate jacobain problem in adaptive neural networks controllers. The simulation results show that the proposed controller is able to control coupled tanks and the chattering phenomenon of conventional switching type sliding mode control does not occur in this study.