A Constant-Volume Control Method for Open Channel Operation

Corriga, G.; Fanni, Alessandra; Sanna, S.; Usai, G.

doi:10.1080/02286203.1982.11759783

Cited by 28 publications

(18 citation statements)

References 2 publications

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“…Merging μ and s V , we can get integrated flow coefficient m : P V s m (8) Flow rate formula can be simplified as : 20166814011 For controlling gates of Middle Route Project, the widths and bottom elevations are known, during the regulation, upstream water level, gate opening and flow rate can be obtained through automation system.…”

Section: Discharge Model Based On Rbfnnmentioning

confidence: 99%

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Study of Discharge Model in South-to-North Water Diversion Middle Route Project Based on Radial Basis Function Neural Network

Chang

Huang

Chen³

et al. 2016

MATEC Web Conf.

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Abstract. The technology for water dispatch is very complex in South-to-North Water Diversion Middle Route Project, and it is necessary to take advantage of automation system for water delivery. The model for calculating flow rate is important to water dispatch, but traditional method often needs to rectify parameters manually. A model based on radial basis function neural network is established to describe the relationship between water level, gate opening and flux. The model uses the network to simulate the optimal function between water level, gate opening and flux coefficient, and calculates the flow rate by the coefficient. By taking the new method into South-to-North Water Diversion Middle Route Project and comparing the neural network model with traditional methods, the results show that the radial basis function neural network model has higher accuracy and efficiency

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Section: Discharge Model Based On Rbfnnmentioning

confidence: 99%

“…At present, domestic and international study of long-distance water dispatch technology have made many research achievements [1]- [8]. However, regulating and operating condition of Middle Route Project is complex and still in the early stages of running through the water, so learning from experience is hard.…”

Section: Introductionmentioning

confidence: 99%

Study of Discharge Model in South-to-North Water Diversion Middle Route Project Based on Radial Basis Function Neural Network

Chang

Huang

Chen³

et al. 2016

MATEC Web Conf.

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“…Therefore, some regulation methods may appear in several categories. (Corriga et al 1980, 1982a, 1982b, Balogun 1985, Garcia 1988, Hubbard et al 1987, Reddy 1986, Filipovic et al 1989, Florea et al, Malaterre 1994and 1995b, Sawadogo et al 1994, and Mixed gates (GEC Alsthom, used by the CNABRL). The latter are sometimes designated as "associated levels gates", because, in certain hydraulic conditions, the purpose of the gate is to maintain a constant difference between its upstream and downstream water levels.…”

Section: Combination Of Bothmentioning

confidence: 99%

Classification of Canal Control Algorithms

Malaterre¹,

Rogers

Schuurmans

1998

J. Irrig. Drain Eng.

206

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Abstract. Different control algorithms for the regulation of irrigation canals have been developed and applied throughout the world. Each of them can be characterized according to several criteria, among which are: the considered variables (controlled, measured, control action variables), the logic of control (type and direction), and the design technique. The following text presents definitions of these terms and a classification of the algorithms detailed in the literature. To summarize and compare algorithms, a structured table of the main published canal control algorithms is presented.

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“…Corriga et al [12,13] proposed a model for open canal networks related to the elevation of the gate. Papageorgiou and Messmer [14,15] and Ermolin [16] proposed an approximation for uniform flow canals derived from linearized Saint-Venant equations.…”

Section: Introductionmentioning

confidence: 99%

Discussion on Muskingum versus Integrator-Delay Models for Control Objectives

Bolea

Puig

Grau

2014

Journal of Applied Mathematics

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A comparative study about two models, Muskingum and integrator-delay (ID) models, for canal control is presented. The former is a simplified hydrological model which is very simple and extensively used in hydraulic engineering for simulation and prediction. The latter is also a model with physical meaning and is widely used for irrigation canals control. Due to a lack of general awareness of Muskingum prediction model in regulation from the control community, authors present this comparative study with the ID control model. Both models have been studied and analyzed for control purposes. This study has been carried out and validated in a real irrigation canal, at Aghili irrigation district in Iran, using two traditional control approaches, PID with feedback and predictive control. The results demonstrate the advantages and drawbacks of both models, showing the benefits and limitations of using the widespread Muskingum model among the hydraulics scientific community for control design.

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A Constant-Volume Control Method for Open Channel Operation

Cited by 28 publications

References 2 publications

Study of Discharge Model in South-to-North Water Diversion Middle Route Project Based on Radial Basis Function Neural Network

Study of Discharge Model in South-to-North Water Diversion Middle Route Project Based on Radial Basis Function Neural Network

Classification of Canal Control Algorithms

Discussion on Muskingum versus Integrator-Delay Models for Control Objectives

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