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Method for predicting and controlling water level of series of water conveyance canals on basis of fuzzy neural network

机译:基于模糊神经网络的水平预测和控制水位的方法

摘要

Disclosed is a method for predicting and controlling the water level of a series of water conveyance canals on the basis of a fuzzy neural network. The method comprises: conducting the relationship between the opening degree of a gate and the controlled water level of an open channel by means of a fuzzy neural network, and constructing a before-gate water level controller coupled to a predictive control algorithm; on the basis of a control objective of the before-gate water level controller, solving an optimal control rate of the before-gate water level controller by means of a gradient optimization algorithm; and on the basis of the solved optimal control rate, generating a control policy by collecting measured water level change information and multiplying same by the optimal control rate, and thereby achieving the aim of water level prediction and control.
机译:公开了一种用于在模糊神经网络的基础上预测和控制一系列水输送管的水位的方法。 该方法包括:通过模糊神经网络,通过模糊神经网络进行栅极的开度和控制水位之间的关系,并构造耦合到预测控制算法的栅极水位控制器; 在浇口水位控制器的控制目标的基础上,通过梯度优化算法解决前浇口水位控制器的最佳控制速率; 并且在求解的最佳控制速率的基础上,通过收集测量的水位改变信息和通过最佳控制速率乘以相同的控制策略,从而实现水位预测和控制的目的。

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