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针对常规模糊控制规则不能自调整,难以及时适应对象特性变化等问题,提出一种基于知识关联的自组织模糊控制方法。通过对系统特性的分析,基于专家经验制定原始规则,依据性能评判环节建立校正规则。研究了校正规则与原始规则的相关性,构建知识关联度函数,得到新规则的调整模型,实现了对规则的实时更新。以染色机染液温度控制系统为对象进行仿真研究。结果表明,与常规模糊控制相比,基于知识关联的自组织模糊控制方法在被控对象特性变化或较大扰动的情况下,具有适应性强、输出跟踪快、控制精度高等特点,具有较高的实用价值。
Aiming at the problems that conventional fuzzy control rules can not be self-adjusted and it is difficult to adapt to changes of object characteristics in time, a self-organizing fuzzy control method based on knowledge correlation is proposed. Through the analysis of system characteristics, based on expert experience to develop the original rules, based on the performance evaluation of the establishment of the rules of correction. The correlativity between the correction rule and the original rule is studied, the knowledge relevance function is constructed, the adjustment model of the new rule is obtained, and the real-time updating of the rule is realized. Dyeing machine dye temperature control system as the object of simulation study. The results show that, compared with the conventional fuzzy control, the self-organizing fuzzy control method based on knowledge association has the characteristics of strong adaptability, fast output tracking and high control accuracy under the condition of the controlled object’s characteristic changes or large disturbance, The practical value.