摘要
针对压缩映射遗传算法(CMGA)操作效率太低,收敛至最优解迭代次数太多的问题,采用了近亲交叉回避策略改进压缩映射遗传算法,不但保证收敛到全局最优解,而且提高了算法的收敛速度和操作效率。为了能对具体被控对象的性能进行有选择性的控制,分析了ITAE积分性能指标作为目标函数的缺点,在目标函数中增加了超调量、控制量和上升时间等综合因素,得到了性能更好的目标函数,应用于改进压缩映射遗传算法的适应度函数,并把以上改进算法的模糊规则优化应用于地板采暖系统,与模糊控制、未改进的压缩映射遗传算法优化模糊控制进行比较,提高了系统的控制效率,简化了模糊控制器的设计难度。仿真结果证明该方法在地板采暖系统中的有效性。
To the problem of low operational efficiency and high iterations of contraction mapping genetic algorithm（CMGA）,This paper uses the police of close relative across blench is used to not only converge to global optimal solution,and to improve convergent speed and operational efficiency.In order to control the performance of a specific object selectivly,the disadvantages of ITAE as the aim function are analyzed.The synthetic factors in aim function,such as,overshoot quantify,control and rising time are added.A better aim function is made and used to fitness function of improved CMGA.The improved CMGA is applied to the optimization of fuzzy rule weighted factors in floor heating system.Compared with fuzzy control and the common CMGA,the proposed method improves the effection of system,simplifies the difficult to design fuzzy controller.The simulated results show the effectiveness of the proposed method in floor heating system.
出处
《控制工程》
CSCD
北大核心
2010年第6期789-791,795,共4页
Control Engineering of China
基金
国家留学基金资助项目(2004813033)
关键词
压缩映射
遗传算法
近亲交叉回避
目标函数
地板采暖
加权因子
contraction mapping
genetic algorithm
close relative across blench
aim function
floor heating
weighted factor
