The traditional control method could accurately decouple the strip flatness and gauge complex system owning to the characteristics of heavy delay, nonlinear and strong coupling, which could led to lower control precision. Based on immune mechanism, an improved particle swarm optimization algorithm was developed, and the weights of PID neural network (PIDNN) were optimized by using this algorithm to form a new PIDNN controller. Two new PIDNN controllers were adopted to control the complex system of strip flatness and gauge to reduce the coupling effect of system. The simulation results showed that the present algorithm has more obvious advantages than that of the previous PIDNN decoupling control in both dynamic and static aspects. This study could provide some references for the decoupling problem in the control field.