基于改进的粒子群PID控制在变风量系统中的应用

目的研究变风量空调系统温度-风量PID控制器的整定方法,利用粒子群算法的特点设计一种较为高效、稳定的自适应控制器.方法以常规PID控制方法的整定结果作为参考,选择PID参数的取值区间,选取种群数量、维数、最大寻优速度、收缩因子等粒子群内部参量,根据粒子群的演化规则自动完成最优控制.结果采用引入收缩因子的粒子群PID自适应控制器时,系统的调节时间约为常规控制方法的50%,超调量减少了约75%.且动态过程快速而平稳;而当系统突加阶跃扰动时,粒子群PID自适应控制器的调节时间及超调量均约为常规控制方法的50%,系统控制品质得到了较大的改善.结论仿真结果表明,采用上述自适应控制器后,空调房间的温度调节过程加快,室内外干扰因素对房间温度的影响明显降低,整个系统体现了良好的动态性能及较强的鲁棒性.

Application of Improved Particle Swarm Optimization PID Control in Variable Air Volume System

Aiming at studying on traditional PID control on VAV system regulating parameters, the pso with construction factor controller was proposed. First, the PID parameters＇ value interval based on the results regulated by the conventional PID control was chosen, then population quantity, dimension, maximum optimization speed,the construction factor and so on were selected, which were interior parameters of particle swarm optimization. According to the evolving rules, the pso controller was able to complete the optimum control automatically. When using the pso controller,the system＇s control time was decreased by 50% than the traditional control time and the overshoot was reduced by 75 %. When adding a step disturbance, the system＇s control time and overshoot were approximately half of the traditional ones. Based on the simulation resuits, the temperature controlling process speeds up and the influence of disturbance in the room reduces obviously. The pso with construction factor controller has good dynamic performance and excellent robust property,which also provides a new approach to computer-aided designing of PID controller on VAV system.