Discussion on Muskingum versus Integrator-Delay Models for Control Objectives

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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An Adaptive Decoupling Control Design for Flotation Column: A Comparative Study Against Model Predictive Control

IETE Journal of Research ◽

10.1080/03772063.2020.1785340 ◽

2020 ◽

pp. 1-14

Author(s):

Sadreddin Nasseri ◽

Mohammad Reza Khalesi ◽

Amin Ramezani ◽

Mahmoud Abdollahi ◽

Mehdi Mohseni

Keyword(s):

Model Predictive Control ◽

Comparative Study ◽

Predictive Control ◽

Control Design ◽

Decoupling Control ◽

Flotation Column

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A Comparative Study on Model Predictive Control Design for Highway Car-following Scenarios: Space-domain and Time-domain Model

IEEE Access ◽

10.1109/access.2021.3131681 ◽

2021 ◽

pp. 1-1

Author(s):

Youngro Lee ◽

Dae Young Lee ◽

Seung Hwan Lee ◽

Youngki Kim

Keyword(s):

Model Predictive Control ◽

Comparative Study ◽

Predictive Control ◽

Time Domain ◽

Control Design ◽

Domain Model ◽

Space Domain ◽

Car Following

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Systematic Finite-Control-Set Model Predictive Control Design with Unified Model for Isomorphic and Dual Power Converters

2020 IEEE Energy Conversion Congress and Exposition (ECCE) ◽

10.1109/ecce44975.2020.9235729 ◽

2020 ◽

Author(s):

Cheng Xue ◽

Yuzhuo Li ◽

Yunwei Li

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Power Converters ◽

Control Design ◽

Unified Model ◽

Finite Control ◽

Control Set ◽

Dual Power

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Robust parametric predictive control design for polytopically uncertain systems

Proceedings of the 2005, American Control Conference, 2005. ◽

10.1109/acc.2005.1470601 ◽

2005 ◽

Cited By ~ 4

Author(s):

A.M. Manthanwar ◽

V. Sakizlis ◽

E.N. Pistikopoulos

Keyword(s):

Predictive Control ◽

Uncertain Systems ◽

Control Design

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On Modeling and Constrained Model Predictive Control of Open Irrigation Canals

Journal of Control Science and Engineering ◽

10.1155/2017/6257074 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Lihui Cen ◽

Ziqiang Wu ◽

Xiaofang Chen ◽

Yanggui Zou ◽

Shaohui Zhang

Keyword(s):

Model Predictive Control ◽

Prediction Model ◽

Predictive Control ◽

Hyperbolic Partial Differential Equations ◽

Irrigation Canal ◽

Irrigation Canals ◽

Optimal Control Algorithms ◽

Saint Venant Equations ◽

Constrained Model ◽

Constrained Model Predictive Control

This paper proposes a model predictive control of open irrigation canals with constraints. The Saint-Venant equations are widely used in hydraulics to model an open canal. As a set of hyperbolic partial differential equations, they are not solved explicitly and difficult to design optimal control algorithms. In this work, a prediction model of an open canal is developed by discretizing the Saint-Venant equations in both space and time. Based on the prediction model, a constrained model predictive control was firstly investigated for the case of one single-pool canal and then generalized to the case of a cascaded canal with multipools. The hydraulic software SICC was used to simulate the canal and test the algorithms with application to a real-world irrigation canal of Yehe irrigation area located in Hebei province.

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Artificial Pancreas: Model Predictive Control Design from Clinical Experience

Journal of Diabetes Science and Technology ◽

10.1177/193229681300700607 ◽

2013 ◽

Vol 7 (6) ◽

pp. 1470-1483 ◽

Cited By ~ 63

Author(s):

Chiara Toffanin ◽

Mirko Messori ◽

Federico Di Palma ◽

Giuseppe De Nicolao ◽

Claudio Cobelli ◽

...

Keyword(s):

Model Predictive Control ◽

Clinical Experience ◽

Predictive Control ◽

Artificial Pancreas ◽

Control Design

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Optimal Harvesting Effort for Nonlinear Predictive Control Model for a Single Species Fishery

Mathematical Problems in Engineering ◽

10.1155/2015/367593 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Messaoud Bounkhel ◽

Lotfi Tadj

Keyword(s):

Predictive Control ◽

Renewable Resource ◽

Single Species ◽

State Equation ◽

Control Model ◽

Optimal Harvesting ◽

Solution Approach ◽

Nonlinear Predictive Control ◽

Nonlinear State ◽

Resource System

We use nonlinear model predictive control to find the optimal harvesting effort of a renewable resource system with a nonlinear state equation that maximizes a nonlinear profit function. A solution approach is proposed and discussed and satisfactory numerical illustrations are provided.

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