基于遗传算法优化的汽车巡航模糊控制策略  

Application of the Genetic Algorithm to Optimizing Fuzzy Control Strategy in the Cruise Control System

作　　者：刘洪玮[1] 石红瑞[1] 

机构地区：[1]东华大学信息科学与技术学院,上海201620

出　　处：《计算机仿真》2010年第7期285-287,共3页Computer Simulation

摘　　要：研究汽车巡航控制系统中采用模糊控制。模糊控制中的隶属函数和模糊推理规则的选取专家或者技术人员的经验,但人工经验具有随机性和主观性,使得其控制性能往往达不到理想的效果。针对上述问题,采用一种基于遗传算法的模糊控制策略,利用遗传算法并对隶属函数和模糊推理规则进行优化,从而使隶属函数和模糊推理规则的确定摆脱了人为经验的局限,提高了模糊控制的自适应能力。实验结果表明优化后的控制器可以使汽车巡航系统取得较满意的效果。The selection of membership functions and inferential rules of the fuzzy controllers of Cruise system depends mainly on the experience of experts,and the control effects are not good owing to the randomicity and subjectivity of the experience.To overcome this problem,a fuzzy control method based on genetic algorithm is presented.The membership functions and inferential rules are optimized by the genetic algorithm,so that the determination get rid of the artificial experience limitation to improve the rules and membership functions.The result of simulation indicates that cruise control system can obtain satisfactory effect after optimization.

关 键 词：巡航控制系统 遗传算法 模糊控制 仿真 

分 类 号：TM38[电气工程—电机]