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作 者:董明 朱其新 DONG Ming;ZHU Qixin(School of Environmental Science and Engineering,SUST,Suzhou 215009,China;School of Mechanical Engineering,SUST,Suzhou 215009,China;Jiangsu ProvinceKey Laboratory of Intelligent Building Energy Efficiency,SUST,Suzhou 215009,China)
机构地区:[1]苏州科技大学环境科学与工程学院,江苏苏州215009 [2]苏州科技大学机械工程学院,江苏苏州215009 [3]苏州科技大学江苏省建筑智慧节能重点实验室,江苏苏州215009
出 处:《苏州科技大学学报(工程技术版)》2022年第1期72-80,共9页Journal of Suzhou University of Science and Technology(Engineering and Technology Edition)
基 金:国家自然科学基金项目(51875380,62063010)。
摘 要:针对空调温湿度系统存在的多变量、强耦合和大时滞等特点,提出了一种改进型多变量内模解耦控制方法。多变量内模解耦控制承袭了单变量内模控制的优势,并且采用优化的Butterworth滤波器代替传统的低通滤波器。由于其内部结构复杂,笔者提出利用免疫遗传算法对被控对象模型进行降阶。免疫遗传算法不仅具有遗传算法的搜索特性,还具有免疫算法的多机制求解多目标函数最优解的自适应特性,可以改善遗传算法的“早熟”问题,收敛于全局最优。仿真结果表明,基于免疫遗传算法降阶的模型与原始模型高度匹配,并且使控制系统具有较强的解耦能力和鲁棒性以及抗干扰能力。Aiming at the characteristics in the air conditioning temperature and humidity system, such as multivariability, strong coupling and large time delay, an improved multi-variable internal model decoupling control approach is proposed. The multivariable internal model decoupling control inherits the advantages of the univariate internal model control, and adopts the optimized Butterworth filter instead of the traditional low-pass filter.Because of the complexity of its internal structure, the immune genetic algorithm is proposed to reduce the order of the controlled object model in the paper. The immune genetic algorithm not only has the searching characteristic of genetic algorithm, but also has the adaptive characteristic of multi-mechanism solving the optimal solution of multi-objective function of immune algorithm, which can improve the "precociousness" of the genetic algorithm and converge to the global optimal.The simulation results show that the reduced order model based on immune genetic algorithm highly matches with the original model, and the control system has strong decoupling ability, robustness and anti-interference ability.
关 键 词:温湿度耦合 内模解耦控制 免疫遗传算法 BUTTERWORTH滤波器
分 类 号:TP273[自动化与计算机技术—检测技术与自动化装置]
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