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Fuzzy neural network water-mixed control system based on hybrid algorithm

机译:基于混合算法的模糊神经网络水混合控制系统

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A fuzzy neural network algorithm was proposed for the water-mixed system, for the system usually has the property of high nonlinearity, large time-delay, time-variant and it's difficult to establish mathematical models. The genetic algorithm and the BP algorithm were combined together. The fuzzy membership function was optimized by the improved genetic algorithm which has ability of global searching. At the same time, the fuzzy neural network's weights were optimized by BP algorithm which has ability of local searching. At the end, the systems will have better adaptability as well as better convergent speed. To make the floor heating system safer and steady a new method was proposed to change the frequency of the booster pump. The simulation results show that the proposed controller which can rapidly control the temperature is better than fuzzy controller.
机译:针对水混系统提出了一种模糊神经网络算法,该系统通常具有非线性高,时滞大,时变大,难以建立数学模型的特点。遗传算法和BP算法结合在一起。通过改进的遗传算法对模糊隶属度函数进行优化,该算法具有全局搜索能力。同时,利用具有局部搜索能力的BP算法对模糊神经网络的权重进行了优化。最后,这些系统将具有更好的适应性和更快的收敛速度。为了使地板采暖系统更安全,更稳定,提出了一种改变增压泵频率的新方法。仿真结果表明,所提出的能够快速控制温度的控制器优于模糊控制器。

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