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Research and Application of Fuzzy Control with Multiple Weighted Factors by Genetic Algorithm

机译:遗传算法对多重加权因子的模糊控制研究与应用

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It is difficult to control the complex object with lagging uncertainty and nonlinearity effectively. To solve this kind of control problem, this paper presents a self-correction fuzzy controller with multiple weighted factors based on genetic algorithm. According to information achieved on line, it finds the global optimum weighted factors with a high speed by the improved genetic algorithm so that to amend and perfect the control rules. It also has done some simulation experiments in the tobacco-redrying control process. The simulation results demonstrate that this kind of control method can achieve good performance.
机译:难以有效地控制复杂对象,有效地滞后不确定性和非线性。为了解决这种控制问题,本文提出了一种基于遗传算法的多加权因子的自我校正模糊控制器。根据在线实现的信息,它通过改进的遗传算法找到了具有高速的全局最佳加权因素,以便修改和完善控制规则。它还在烟草红酒控制过程中做了一些模拟实验。仿真结果表明,这种控制方法可以实现良好的性能。

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