Fuzzy Neural Network Control of the Garbage Incinerator

Yu Xiao-hong, Yang Zhu-zhong, Yang Tao
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Abstract

In order to solve the problem of garbage treatment effectively, a control method is proposed based on Takagi-Sugeno (T-S) fuzzy neural network model after analyzing the characteristics of garbage incinerators system and the main factors affecting combustion. A T-S fuzzy neural network model for garbage incinerators control is established which utilizes BP learning algorithm for data training. Then a simulation research is carried out to verify the feasibility and superiority. Results show that the T-S fuzzy neural network control can well track the input in a relative short time. The contrast analysis with conventional PID control and fuzzy control is done to show a better performance under the fuzzy neural network control. The fuzzy neural network control method can adapt to the complex garbage incineration process, which makes it high application value.
垃圾焚烧炉的模糊神经网络控制
为了有效解决垃圾处理问题,在分析垃圾焚烧炉系统特点和影响燃烧的主要因素后,提出了一种基于T-S模糊神经网络模型的控制方法。利用BP学习算法进行数据训练,建立了垃圾焚烧炉控制的T-S模糊神经网络模型。然后进行了仿真研究,验证了该方法的可行性和优越性。结果表明,T-S模糊神经网络控制能在较短的时间内很好地跟踪输入。通过与传统PID控制和模糊控制的对比分析,表明模糊神经网络控制具有更好的控制性能。模糊神经网络控制方法能适应复杂的垃圾焚烧过程,具有很高的应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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