Abstract: Aimming at the problem that the simple Particle Swarm Optimization（PSO） algorithm and its improved algorithms are difficult to deal with local convergence and convergence velocity，this paper proposes a Quantum-behaved Particle Swarms Cooperative Optimization（QPSCO） algorithm.In its two-layer framework with particle swarms cooperative optimization，some quantum-behaved particle swarms are employed to search in the solution space independently and a mutation parameter is introduced for larger searching scale in bottom layer，and a single quantum-behaved swarm is employed to track with the globe best solution while new particles replace those particles flying out the solution space with their position in top layer.Based on the above，this algorithm is applied to PID controller design for a lower-order system with time delay.Simulation results demonstrate that the approach is more effective for parameter optimization and have better global convergence ability than PSO，QPSO et al.