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Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms

机译：区间二型模糊逻辑控制器的进化算法优化

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摘要

A method for designing optimal interval type-2 fuzzy logic controllers using evolutionary algorithms is presented in this paper. Interval type-2 fuzzy controllers can outperform conventional type-1 fuzzy controllers when the problem has a high degree of uncertainty. However, designing interval type-2 fuzzy controllers is more difficult because there are more parameters involved. In this paper, interval type-2 fuzzy systems are approximated with the average of two type-1 fuzzy systems, which has been shown to give good results in control if the type-1 fuzzy systems can be obtained appropriately. An evolutionary algorithm is applied to find the optimal interval type-2 fuzzy system as mentioned above. The human evolutionary model is applied for optimizing the interval type-2 fuzzy controller for a particular non-linear plant and results are compared against an optimal type-1 fuzzy controller. A comparative study of simulation results of the type-2 and type-1 fuzzy controllers, under different noise levels, is also presented. Simulation results show that interval type-2 fuzzy controllers obtained with the evolutionary algorithm outperform type-1 fuzzy controllers.
机译：提出了一种基于进化算法的最优区间2型模糊逻辑控制器设计方法。当问题具有高度不确定性时，区间2型模糊控制器的性能可能会优于传统的1型模糊控制器。但是，设计区间2型模糊控制器更加困难，因为其中涉及的参数更多。本文用两个1型模糊系统的平均值来近似区间2型模糊系统，这表明如果能够适当地获得1型模糊系统，则在控制方面会取得良好的效果。如上所述，应用进化算法来找到最优区间类型2模糊系统。将人类进化模型用于优化特定非线性植物的区间2型模糊控制器，并将结果与​​最佳1型模糊控制器进行比较。还对不同噪声水平下的2型和1型模糊控制器的仿真结果进行了比较研究。仿真结果表明，采用进化算法得到的区间2型模糊控制器的性能优于1型模糊控制器。

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