Abstract: The optimal control of basis weight and moisture content in paper process with strong coupling, nonlinear and large time delay is difficult to achieve. To solve the problem, the optimal PID neural network controller by particle swarm optimization was adopted in the control system. Because the network structure was simple and a modified error back propagation algorithm with momentum factor was used, the learning speed was increased and the reaction time of the system became short. Particle swarm optimization was used to optimize the initial weights of PID neural network to avoid local optimization for obtaining better control accuracy. Simulation results show PID neural network optimizated by the network’s initial weights is of better adaptability, decoupling ability and robustness in the decoupling control of basis weight and moisture content. It is a new method for the control of basis weight and moisture content in paper process.
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Key words:  particle swarm optimization(PSO), PID neural network, optimization, paper process