关键词: 量子粒子群算法, 权重系数, PID控制器, 参数优化

Abstract: The conventional parameter optimization of PID controller is easy to produce surge and big overshoot，and therefore heuristics such as Genetic Algorithm（GA），Particle Swarm Optimization（PSO） are employed to enhance the capability of traditional techniques.But the convergence speed of SGA is slowly and PSO may be trapped in the local optima of the objective and leads to poor performance.In this paper，a weight coefficient is introduced into Quantum-behaved Particle Swarm Optimization（QPSO） and an improved QPSO（WQPSO） for the parameter optimization of PID controller is proposed.The comparison of WQPSO，PSO and QPSO based on benchmark function is given.Finally，three examples are given to illustrate the design procedure and exhibit the effectiveness of the proposed method via a comparison study with an existing Z-N，GA and PSO approaches.

Key words: Quantum-behaved Particle Swarm Optimization（QPSO）, weight coefficient, PID controller, parameter optimization