基于改进内模解耦控制的空调系统优化
Air conditioning system optimization based on improved internal model decoupling control
摘要：
内模解耦的控制方法具有较好的抗干扰能力，针对时滞性问题也有较好的控制效果，但是其多变量内模解耦控制器的内部结构复杂，计算量较大。提出了利用遗传算法对内模控制器的参数进行优化。首先对变风量空调系统的解耦控制器进行设计，然后确定目标函数的优化参数，并设计了利用遗传算法进行优化的步骤，最后通过MATLAB进行仿真。仿真结果表明，系统的超调量小，抗干扰能力强，即使在模型不匹配时依然能够实现稳定控制。
Abstract：
The internal model decoupling control method has better anti-interference ability and better control effect on time lag problem, but its multi-variable internal model decoupling controller has complex internal structure and large computational complexity. Presents using the genetic algorithm to optimize the parameters of the internal model controller. Designs a decoupling controller of the variable air volume air conditioning system, determines the optimization parameters of the objective function, and designs the steps of optimization, finally performs the simulation by MATLAB. The simulation results show that the system has small overshoot and strong anti-interference ability, which can achieve stable control even if the model does not match.
Keywords:multi-variabledecoupling,internalmodelcontrol,geneticalgorithm,parameteroptimization,variableairvolume(VAV)airconditioning