遗传算法优化的模糊+变论域自适应模糊PID复合控制策略

Compound Control Strategy of Fuzzy+Variable Universe Self-adaptive Fuzzy-PID Based on Genetic Algorithm Optimization

  • 摘要: 针对变风量空调系统的不确定性和参数整定困难问题,提出了一种用遗传算法优化的模糊+变论域模糊PID复合控制器的新方法.该控制器由模糊控制和变论域模糊PID控制两部分组成.在系统动态阶段,采用模糊控制使其具有最优的动态性能;当系统进入稳态阶段,采用变论域自适应模糊PID控制使其具有最优的稳态性能.用遗传算法对主控制器的PID参数值进行离线优化,将其作为在线调节的初值,通过变论域的模糊推理在线调整系统的PID参数,使之具有良好的自适应能力.用模糊平滑切换保证了两种不同控制方式的平稳过渡.将提出的复合控制策略应用于变风量空调系统的室温串级控制中,计算机仿真结果表明,该方法使系统具有良好的动、稳态性能,抗干扰和鲁棒性好.

     

    Abstract: With regard to uncertainties and difficult setting of the parameters in variable air volume(VAV) condition system,a new method of compound controller on fuzzy+variable universe fuzzy-PID based on genetic algorithm optimization is proposed.This controller is composed by fuzzy control and variable universe fuzzy-PID control.At the dynamic stage,the fuzzy control enables the system to have the most superior dynamic performance;at the steady-state stage,variable universe self-adaptive fuzzy-PID control enables the system to have the most superior steady-state performance.It applies genetic algorithm offline to optimizing the values of PID parameters of main controller.The output values of offline optimizing are the primary values of online adjusting.Adjusting the PID parameters online with the variable universe fuzzy inference,it ensures that the system has good self-adaptability.The fuzzy method of smooth switching guarantees the steady transition between the two different control strategies.The proposed compound control strategy is applied to the room temperature cascade control of VAV condition system.The simulation result shows that the system has good dynamic and steady-state performance,excellent anti-disturbance and robustness.

     

/

返回文章
返回