An adaptive control algorithm is proposed for continuous stirred tank reactor (CSTR) with unknown functions based on the approximation property of the neural networks.Because the considered reactor contains the nonlinear property and the unknown functions are included in the subsystem

it is a completed system and is very difficult to be controlled.In order to avoid the difficulties

a novel recursive procedure is given to remove the interconnection term and special approximated functions are defined to be approximated by using the neural networks.Using the Lyapunov method

the algorithm ensures that all the signals in the closed-loop are bounded and the output can converge to a neighborhood of zero.A simulation example is given to show effectiveness of the algorithm.