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Self-organizing fuzzy learning CLOS guidance law design

机译：自我组织模糊学习结束指导法设计

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摘要

A new self-organizing fuzzy logic control (SOFLC) design method is proposed. The proposed method is applied to the command line-of-sight (CLOS) guidance law design. The SOFLC contains two sets of fuzzy inference logic. One is the fuzzy logic controller and the other is the rule modifier. The new learning method of the rule modifier is developed based on a fuzzy learning algorithm. The modification value of each rule is based on the fuzzy firing weight, so that learning of the rule bases is reasonable. Finally, two engagement scenarios are examined, and a comparison between a fuzzy logic control (FLC), an optimal learning FLC, and the proposed SOFLC CLOS guidance laws is made. Simulation results show that the proposed SOFLC guidance law can achieve better guidance performance than the other guidance laws.
机译：提出了一种新的自组织模糊逻辑控制（SOFLC）设计方法。该方法应用于指令视线（CLES）引导法设计。 SOFLC包含两组模糊推理逻辑。一个是模糊逻辑控制器，另一个是规则修饰符。基于模糊学习算法开发了规则修饰符的新学习方法。每个规则的修改值都基于模糊触发重量，因此规则基础的学习是合理的。最后，检查了两个参与情景，并进行了模糊逻辑控制（FLC），最佳学习FLC和所提出的SOFLC结束指导规律的比较。仿真结果表明，拟议的SOFLC指导法可以比其他指导法达到更好的指导性能。

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