Study on Optimal Control of Dam Gate Openings by Self-Tuninfg Control Theory

本研究的目的是探讨自校正控制器在洪水条件下对堰闸开度的实时控制，并研究时间序列模型和滤波技术在潮汐河流水位实时预报中的适用性。采用Clarke和高斯罗普的自校正控制器（STC）对堰门开度进行实时控制。本文针对用ARMAX模型描述的系统（堰门开度控制），导出了STC，它由卡尔曼滤波器框架内的在线递推系统辨识算法和反馈控制律组成，反馈控制律的参数取决于当前估计的系统模型。首次将其应用于一个综合生成的数据，以说明STC用于堰门开度控制的特点。然后介绍了它在翁加河堰闸控制中的应用。本文利用丰水期堰闸的实际运行资料，将STC的控制效果与现行的控制策略进行了比较，讨论了台风期间洪水通过感潮河段时水位的模拟和预报技术。采用两种简单的时间序列模型，即周期函数模型和ARMAX模型来描述感潮河段不同位置的水位变化。卡尔曼滤波器用于根据最新信息自动更新模型系数的估计值或递归地进行预测。这些技术应用于预测的问题，在感潮的仙台河，九州，日本的水位。

The intended purposes of the research are to investigate the use of a self-tuning controller to real-time control of weir gates' openings during flood conditions and to study the applicability of time series models and filtering technique to the real-time forecasting of water levels in tidal rivers. The approach adopted for the real-time control of weir gates' openings uses the self-tuning controller (STC) of Clarke and Gawthrop. In this report, STC derived for the system (the control of weir gates' openings) described by an ARMAX model consists of an on-line recursive system identification algorithm within a Kalman filter framework and a feedback control law whose parameters depend on the corrently estimated system model. It is first applied to a synthetically generated data to illustrate the characteristics of the use of STC to the control of weir gates' openings. Its application to control the weir gates at Onga River is then presented. using data of the actual operation of the weir gates during periods of high inflows, the performance of STC is compared with that of the existing control strategy.Techniques for the modelling and prediction of water levels when flood passes through the tidal reach of a river during typhoon periods are discussed. Two simple time series models, a periodic function model and an ARMAX model, are used to describe the water-level variations at different locations in the tidal reach. The Kalman filter is used to automatically update the estimates of model coefficients or make forecasts recursively, based on the latest information. These techniques are applied to the problem of predicting the water levels in the tidal reach of the Sendai River, Kyushu, Japan.