Model predictive control and moving horizon estimation for water level regulation in inland waterways

Segovia, P.; Rajaoarisoa, L.; Nejjari, Fatiha; Duviella, E.; Puig, Vicenç

doi:10.1016/j.jprocont.2018.12.017

Cited by 39 publications

(21 citation statements)

References 36 publications

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“…Short-term perspectives regard the implementation and testing of model predictive control (MPC) strategies such as those proposed in [28,29], but using an accurate HEC-RAS model of a real canal in the north of France. Such models are based on precise geographic information systems (GIS), whose data are provided by the Institut Géographique National (IGN), a French organization that manages a highly accurate geographical database of the French territory.…”

Section: Discussionmentioning

confidence: 99%

Design of a MATLAB HEC-RAS Interface to Test Advanced Control Strategies on Water Systems

Deshays

Segovia

Duviella

2021

Water

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The software package HEC-RAS (Hydrologic Engineering Center’s River Analysis System) is widely used by the water engineering community to analyze hydraulic systems and perform development planning. Furthermore, it integrates a control module that allows implementing basic controllers. For more complex approaches, developers from the automatic control and artificial intelligence (AI) communities usually design, implement, and test new algorithms using dedicated software such as MATLAB. However, models of hydraulic systems employed in MATLAB are often very simple. The main objective of the paper is to design a simulation architecture by coupling HEC-RAS with MATLAB, thus improving the accuracy of the dynamics of the hydraulic systems considered in the control simulations. The main feature of the MATLAB HEC-RAS interface design is that it allows one to execute customized code at regular time intervals during the simulation. In this way, closed-loop control and optimization algorithms can be implemented and tested. Moreover, the generic interface allows for any configuration of hydrographical systems. The proposed interface is presented in this paper, and the performance of the approach is demonstrated considering two case studies of different nature.

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Section: Discussionmentioning

confidence: 99%

Design of a MATLAB HEC-RAS Interface to Test Advanced Control Strategies on Water Systems

Deshays

Segovia

Duviella

2021

Water

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“…This layer is concerned with the design and resolution of the two MPC (one for each mode) and the MHE (employed in both modes). Their design is adapted from [3] to consider the case of N r reaches with different delays {n 1 , n 2 , . .…”

Section: B Intermediate Layermentioning

confidence: 99%

“…Modeling and control of open-channel systems have been extensively studied in the last several decades, motivated by many engineering applications, e.g. control of irrigation [1] and drainage canals [2], inland waterways management [3], hydro-power turbine control [4] and regulation of sewage systems [5]. Open-channel systems are characterized by complex dynamics, and are best described by the Saint-Venant equations, a set of partial differential equations [6].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical model predictive control and moving horizon estimation for open-channel systems with multiple time delays

Guekam

Segovia

Etienne

et al. 2021

2021 European Control Conference (ECC)

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This work presents the design of a hierarchical control and state estimation approach for the optimal water level management of open-channel systems using gates and pumping stations as actuators. Each reach may be characterized by a different time delay and a different prioritization of objectives. The design is divided in three layers: the upper layer determines the current operating mode. The intermediate layer is concerned with the design of appropriate controllers and observers to compute the references. Finally, the lower layer solves a scheduling problem to minimize the error between the references and the applied controls by discrete actuators. Simulation of a realistic case study based on part of the inland waterways in the north of France is used to demonstrate the effectiveness of the proposed approach.

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“…Frison et al investigate MHE computation time and conclude MHE can be computed quickly enough to enable real-time control. Consequentially, many recent studies have combined MHE with MPC [58][59][60][61].…”

Section: Use Of Mhe In Mpcmentioning

confidence: 99%

Proactive Energy Optimization in Residential Buildings with Weather and Market Forecasts

et al. 2019

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This work explores the development of a home energy management system (HEMS) that uses weather and market forecasts to optimize the usage of home appliances and to manage battery usage and solar power production. A Moving Horizon Estimation (MHE) application is used to find the unknown home model parameters. These parameters are then updated in a Model Predictive Controller (MPC) which optimizes and balances competing comfort and economic objectives. Combining MHE and MPC applications alleviates model complexity commonly seen in HEMS by using a lumped parameter model that is adapted to fit a high-fidelity model. Heating, ventilation, and air conditioning (HVAC) on/off behaviors are simulated by using Mathematical Program with Complementarity Constraints (MPCCs) and solved in near real time with a non-linear solver. Removing HVAC on/off as a discrete variable and replacing it with an MPCC reduces solve time. The results of this work indicate that energy management optimization significantly decreases energy costs and balances energy usage more effectively throughout the day. A case study for Phoenix, Arizona shows an energy reduction of 21% and a cost reduction of 40%. This simulated home contributes less to the grid peak load and therefore improves grid stability and reduces the amplitude of load-following cycles for utilities. The case study combines renewable energy, energy storage, forecasts, cooling system, variable rate electricity plan and a multi-objective function allowing for a complete home energy optimization assessment. There remain several challenges, including improved forecast models, improved computational performance to allow the algorithms to run in real time, and mixed empirical/physics-based machine-learning methods to guide the model structure.

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Model predictive control and moving horizon estimation for water level regulation in inland waterways

Cited by 39 publications

References 36 publications

Design of a MATLAB HEC-RAS Interface to Test Advanced Control Strategies on Water Systems

Design of a MATLAB HEC-RAS Interface to Test Advanced Control Strategies on Water Systems

Hierarchical model predictive control and moving horizon estimation for open-channel systems with multiple time delays

Proactive Energy Optimization in Residential Buildings with Weather and Market Forecasts

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