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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 fuzzy optimization algorithm which combines genetic algorithm and fuzzy logic to form the error compensation of inertial element is described.The optimization of fuzzy inference rules by genetic algorithm can give the fuzzy inference knowledge acquisition ability and is suitable for automatically forming the reasoning mechanism to the given data The membership function optimization parameters are given.The simulation results show that this method is effective and feasible for the error compensation of the 掼 components in INS.