Decentralized adaptive control for a water distribution system

Didier Georges
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引用次数: 45

Abstract

This paper considers the design of a decentralized adaptive controller for a water distribution system. This system consists of a 40-kilometer long canal connected to three secondary canals and four main reservoirs supplied by a 7 m/sup 3/ s/sup -1/ river (the Bourne river). More than 20 pumping stations are distributed along the canals, bringing water to the agricultural plain of Valence (South-East of France). The system is currently manually operated through flow control gates. The author's medium-term objective is to automatically operate this system and to improve water distribution efficiency and safety. In terms of control the primary goal is to satisfy the water demand at each pumping station, while guaranteeing a minimum water level, overflow avoidance and minimum wastes of water, in each section and reservoir of the system. The author's approach is divided into two main stages. An on-line identification procedure based both on a multi-input multi-output parametrized model and Kalman filtering. A state-space predictive control scheme using a Kalman state estimator defined on the basis of the on-line identified model. The author shows how this control scheme can be decentralized in case of large-scale water distribution systems, such as the author's process.<>
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配水系统的分散自适应控制
本文研究了给水系统分散自适应控制器的设计。该系统包括一条40公里长的运河,与三条次级运河和四个主要水库相连,由一条7米/sup 3/ s/sup -1/的河流(伯恩河)供应。运河沿线分布着20多个泵站,将水输送到瓦朗斯(法国东南部)的农业平原。该系统目前是通过流量控制门手动操作的。笔者的中期目标是实现该系统的自动化运行,提高配水效率和安全性。在控制方面,主要目标是满足每个泵站的用水需求,同时保证系统各段和各水库的最低水位、避免溢流和最小的水浪费。作者的研究方法主要分为两个阶段。一种基于多输入多输出参数化模型和卡尔曼滤波的在线辨识方法。基于在线辨识模型,提出了一种基于卡尔曼状态估计器的状态空间预测控制方案。作者展示了这种控制方案如何在大型配水系统(如作者的过程)的情况下分散。
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