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An adaptive PID decoupling control strategy based on Radial Basis Function (RBF) neural network (NN) is presented in this paper for nonlinear multivariable system. Based on the theory of optimization in groups, the parameters such as proportion, integration and differentiation of PID controller are tuned on-line using the self-learning ability of RBFNN. And the corresponding decoupling control law is achieved by conventional PID control algorithm. Simulation results show that the dynamic decoupling and completely static decoupling are obtained, the closed loop system has the advantages of higher speed response and stronger robustness.