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Aggregation-based Model Predictive Control of Open Channel Networks

机译:基于聚合的明渠网络模型预测控制

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By use of the linearized Saint-Venant equations, this paper first recalls the so-called constant volume model of open channel networks. Based on this model, a predictive model of open channel networks is derived. It takes the storage volume variations as state variables and gate openings as control variables with constraints. Considering the structure complexity of open channels and constraints, the control problem of open channel networks is cast in the framework of model predictive control. An equivalent aggregation scheme for the model without any constraints is presented to improve the computational efficiency significantly without any loss of control performance. Then the idea of equivalent aggregation scheme is generalized to the case with constraints and a quasi-equivalent aggregation scheme is developed. A detailed study for a particular open channel network consisting of two pools is illustrated to demonstrate the efficacy of the aggregation-based model predictive control algorithm.
机译:通过使用线性化的Saint-Venant方程,本文首先回顾了开放通道网络的所谓恒定体积模型。在此模型的基础上,导出了开放渠道网络的预测模型。它将存储量的变化作为状态变量,将门的打开量作为具有约束的控制变量。考虑到开放渠道的结构复杂性和约束条件,在模型预测控制的框架下提出开放渠道网络的控制问题。提出了一种没有任何约束的模型等效聚集方案,以显着提高计算效率,而不会损失任何控制性能。然后将等价聚合方案的思想推广到有约束的情况,并提出了一种准等价聚合方案。详细说明了对由两个池组成的特定开放通道网络的研究,以证明基于聚集的模型预测控制算法的有效性。

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