Abstract: An intelligent control model of secondary cooling in continuous slab casting was presented to reduce the difference between actual temperature and target temperature at the surface of slabs during secondary cooling. The model dynamically sets the target temperature at the surface of slabs with support vector machine, forecasts the surface temperature of slabs with diagonal recurrent neural network, and dynamically controls and distributes the water flow of secondary cooling with T-S fuzzy recurrent neural network. Simulation calculation and field test were performed on the process of continuous slab casting in a steel plant. It is shown that the model integrates the problem of controlling the water flow of secondary cooling with the temperature state of slabs during the cooling process, can achieve the dynamic optimum control of secondary cooling and improve the quality of slabs.