【摘要】 针对变风量(VAV)空调系统下位机设定点变动时,整个系统完全达到稳态时间过长,且各子系统易出现超调的问题,提出采用一种迭代学习控制(ILC)的设定值序列优化方法。以空调系统中变频风机—管道静压控制回路为实例,说明该方法的可行性。采用递推最小二乘法(RLS)建立该回路的动态模型,并给出了一种新的迭代学习期望轨迹,应用迭代学习PD控制律对其动态过程进行仿真分析,并将此算法用于空调实验平台验证其控制效果。结果表明,ILC可以改善空调子系统的动态特性,为VAV空调系统的全局稳态优化奠定了基础。更多还原

【Abstract】 A set-point sequence optimization method based on ILC is proposed to solve the problems of long adjusting time and overshoot when controller’s set-point changes in VAV air-conditioning system.The methodology is demonstrated feasible through the variable frequency fan-static pressure control loop.The dynamic model of static pressure loop is acquired with Recursive Least Square method(RLS).A novel trajectory is also proposed.The dynamic response of the process is analyzed with PD-ILC theme through simulation and experiment.The results show that ILC can improve the dynamic characteristics of subsystems,which lays the foundation of full steady-state optimization of VAV air-conditioning system.更多还原