摘要
阐述将遗传算法和模糊逻辑相融合,形成惯性元件误差补偿的模糊优化算法.通过遗传算法来优化模糊推理规则,能赋予模糊推理知识获取能力,适于对给予的数据自动构成推理机构达到所要求的隶属函数优化参数.仿真结果表明该方法对惯导系统中掼性元件误差补偿有一定有效性和可行性.
The paper presented the fuzzy optimal algorithm of error compensation for inertial elements which is composed of genetic algorithm (GA) and fuzzy logic. Through optimizing the fuzzy reasoning rules by GA, thus the anility of acquiring knowledge is obtained in fuzzy system. In addition, the reasoning structure can be constructed automatically and the optimal parameters of the membership functions can be obtained by GA. The simulation results demonstrate that the fuzzy optimal method has certain validity and feasibility for error compensation of inertial elements in inertial system.
出处
《自动化仪表》
CAS
北大核心
1999年第7期6-8,24,共4页
Process Automation Instrumentation
基金
国家"863"计划资助项目
编号为863-306-2D-03-6
关键词
遗传算法
模糊逻辑
优化算法
惯性元件
误差补偿
Genetic algorithm Fuzzy control Membership function Optimal algorithm Navigation system Inertia! element
