P. Malaterre - Academia.edu (original) (raw)
Papers by P. Malaterre
International Journal for Numerical Methods in Fluids, 2016
Estimating river discharge from in-situ and/or remote sensing data is a key issue for evaluation ... more Estimating river discharge from in-situ and/or remote sensing data is a key issue for evaluation of water balance at local and global scales and for water management. Variational data assimilation (DA) is a powerful approach used in operational weather and ocean forecasting, which can also be used in this context. A distinctive feature of the river discharge estimation problem is the likely presence of significant uncertainty in principal parameters of a hydraulic model, such as bathymetry and friction, which have to be included into the control vector alongside the discharge. However, the conventional variational DA method being used for solving such extended problems often fails. This happens because the control vector iterates (i.e. approximations arising in the course of minimization) result into hydraulic states not supported by the model. In this paper we suggest a novel version of the variational DA method specially designed for solving estimation-under-uncertainty problems, which is based on the ideas of iterative regularization. The method is implemented with SIC 2 , which is a full Saint-Venant based 1D-network model. The SIC 2 software is widely used by research, consultant and industrial communities for modelling river, irrigation canal and drainage network behavior. The adjoint model required for variational DA is obtained by means of automatic differentiation. This is likely to be the first stable consistent adjoint of the 1D-network model of a commercial status in existence. The DA problems considered in this paper are offtake/tributary estimation under uncertainty in the cross-device parameters, and inflow discharge estimation under uncertainty in the bathymetry defining parameters and the friction coefficient. Numerical tests have been designed to understand identifiability of discharge given uncertainty in bathymetry and friction. The developed methodology and software seem useful in the context of the future SWOT satellite mission.
Département DISCO « Dynamiques Interne et de Surface des Continents » 31 Décembre 2018 L'hydrolog... more Département DISCO « Dynamiques Interne et de Surface des Continents » 31 Décembre 2018 L'hydrologie à l'IRD Hydrology has evolved as a transdisciplinary, datadriven science in a remarkably short period of time. Today, hydrology is a vibrant field that recognizes plants, landforms and human activity as key factors influencing the movement, quality and cycling of water.
Irrigation canals have a series structure which is generally used to design multivariable control... more Irrigation canals have a series structure which is generally used to design multivariable controllers based on the aggregation of decentralized monovariable controllers. SISO controllers are designed for each canal pool, assuming that the interactions will not destabilize the overall system. It is shown that, when the canal pools are controlled using the discharge at one boundary, the multivariable decentralized control structure is stable if and only if the SISO controllers are stable. The performance of the multivariable system is also investigated, and it is shown that the interactions decrease the overall performance of the controlled system. This loss of performance can be reduced by using a feedforward controller. Experimental results show the effectiveness of the method.
Irrigation is well known for being the largest water user, responsible for about 70% of the total... more Irrigation is well known for being the largest water user, responsible for about 70% of the total amount of fresh water withdrawals. At the same time, this irrigation contributes for about 40% of the total food production and is vital for many regions of the world such as Western USA, Australia, Southern Europe, and many countries in Asia and Africa. Recent FAO figures indicate that, by the year 2030, food production will have to be increased by about 80% with only a possible increase of 12% of the water withdrawal. One unavoidable way of being able to reach this agenda is to reduce water demand by improving the hydraulic efficiency of irrigation schemes. Technical concepts involved in these modernization projects include open channel hydraulics and control engineering, which are usually taught in separate college curricula. Such projects are carried out in many places in the world, especially in developing countries, with the help of engineers, canal managers and decision makers. T...
In IIMI; CEMAGREF. International Workshop on The Application of Mathematical Modelling for the Im... more In IIMI; CEMAGREF. International Workshop on The Application of Mathematical Modelling for the Improvement of Irrigation Canal Operation, October 26-30, 1992, Montpellier, France
In Strosser, P. (Ed.), The collaboration between IIMI and CEMAGREF in Pakistan: Proceedings of a ... more In Strosser, P. (Ed.), The collaboration between IIMI and CEMAGREF in Pakistan: Proceedings of a one-day workshop, October 3, 1997, International Irrigation Management Institute, Lahore. Lahore, Pakistan: IIMI. Pakistan National Program
Journal of Computational Physics
Journal of Computational Physics
Solving data assimilation problems under uncertainty in basic model parameters and in source term... more Solving data assimilation problems under uncertainty in basic model parameters and in source terms may require a careful design of the control set. The task is to avoid such combinations of the control variables which may either lead to ill-posedness of the control problem formulation or compromise the robustness of the solution procedure. We suggest a method for quantifying the performance of a control set which is formed as a subset of the full set of uncertainty-bearing model inputs. Based on this quantity one can decide if the chosen 'safe' control set is sufficient in terms of the prediction accuracy. Technically, the method presents a certain generalization of the 'variational' uncertainty quantification method for observed systems. It is implemented as a matrix-free method, thus allowing high-dimensional applications. Moreover, if the Automatic Differentiation is utilized for computing the tangent linear and adjoint mappings, then it could be applied to any multi-input 'black-box' system. As application example we consider the full Saint-Venant hydraulic network model SIC 2 , which describes the flow dynamics in river and canal networks. The developed methodology seem useful in the context of the future SWOT satellite mission, which will provide observations of river systems the properties of which are known with quite a limited precision.
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IEEE Control Systems Magazine
With a population of more than six billion people, food production from agriculture must be raise... more With a population of more than six billion people, food production from agriculture must be raised to meet increasing demand. While irrigated agriculture provides 40% of the total food production, it represents 80% of the freshwater consumption worldwide. In summer and drought conditions, efficient management of scarce water resources becomes crucial. The majority of irrigation canals are managed manually, however, with large water losses leading to low water efficiency. The present article focuses on the development of algorithms that could contribute to more efficient management of irrigation canals that convey water from a source, generally a dam or reservoir located upstream, to water users. We also describe the implementation of an algorithm for real-time irrigation operations using a supervision, control, and data acquisition (SCADA) system with automatic centralized controller. Irrigation canals can be viewed and modeled as delay systems since it takes time for the water released at the upstream end to reach the user located downstream. We thus present an openloop controller that can deliver water at a given location at a specified time. The development of this controller requires a method for inverting the equations that describe the dynamics of the canal in order to parameterize the controlled input as a function of the desired output. The
Operations Research/Computer Science Interfaces Series, 2015
ABSTRACT
Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management, 2015
Journal of Water Resources Planning and Management, 2015
We investigate the improvement of the operation of a four-reservoir system in the Seine River bas... more We investigate the improvement of the operation of a four-reservoir system in the Seine River basin, France, by use of deterministic and ensemble weather forecasts and real-time control. In the current management, each reservoir is operated independently from the others and following prescribed rule-curves, designed to reduce floods and sustain low-flows under the historical hydrological conditions. However, this management system is inefficient when inflows are significantly different from their seasonal average and may become even more inadequate to cope with the predicted increase in extreme events induced by climate change. In this work, we develop and test a centralized real-time control system to improve reservoirs operation by exploiting numerical weather forecasts that are becoming increasingly available. The proposed management system implements a well-established optimization technique, Model Predictive Control (MPC) and its recently modified version that can incorporate uncertainties, Tree-Based Model Predictive Control (TB-MPC), to account for deterministic and ensemble forecasts respectively. The management system is assessed by simulation over historical events and compared to the "no-forecasts" strategy based on rule-curves. Simulation results show that the proposed real-time control system largely outperforms the "no-forecasts" management strategy, and that explicitly considering forecasts uncertainty through ensembles can compensate for the loss in performance due to forecasts inaccuracy.
Operations Research/Computer Science Interfaces Series, 2015
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2000
The aim of this work is to present an application of recent methods for solving the 1 design prob... more The aim of this work is to present an application of recent methods for solving the 1 design problem, based on the Scaled-Q approach, on a high-order, non-minimum phase system. We start by describing the system which is an open-channel hydraulic system (e.g.: an irrigation canal). From the discretization and linearization of the set of two partial-derivative equations, a state-space model of the system is generated. This model is a high-order MIMO system (five external perturbations w, five control inputs u, ten controlled outputs z, five measured outputs y, 65 states x) and is non-minimum phase. A controller is then designed by minimizing the 1 norm of the impulse response of the transfer matrix between the perturbations w and the outputs z. Time-domain constraints are added into the minimization problem in order to force integrators into the controller. The numerical resolution of the problem proved to be efficient, despite of the characteristics of the system. The obtained results are compared in the timedomain to classical P ID and LQG controllers on the non-linear system. The results are good in terms of performance and robustness, in particular for the rejection of the worst-case perturbation.
International Journal for Numerical Methods in Fluids, 2016
Estimating river discharge from in-situ and/or remote sensing data is a key issue for evaluation ... more Estimating river discharge from in-situ and/or remote sensing data is a key issue for evaluation of water balance at local and global scales and for water management. Variational data assimilation (DA) is a powerful approach used in operational weather and ocean forecasting, which can also be used in this context. A distinctive feature of the river discharge estimation problem is the likely presence of significant uncertainty in principal parameters of a hydraulic model, such as bathymetry and friction, which have to be included into the control vector alongside the discharge. However, the conventional variational DA method being used for solving such extended problems often fails. This happens because the control vector iterates (i.e. approximations arising in the course of minimization) result into hydraulic states not supported by the model. In this paper we suggest a novel version of the variational DA method specially designed for solving estimation-under-uncertainty problems, which is based on the ideas of iterative regularization. The method is implemented with SIC 2 , which is a full Saint-Venant based 1D-network model. The SIC 2 software is widely used by research, consultant and industrial communities for modelling river, irrigation canal and drainage network behavior. The adjoint model required for variational DA is obtained by means of automatic differentiation. This is likely to be the first stable consistent adjoint of the 1D-network model of a commercial status in existence. The DA problems considered in this paper are offtake/tributary estimation under uncertainty in the cross-device parameters, and inflow discharge estimation under uncertainty in the bathymetry defining parameters and the friction coefficient. Numerical tests have been designed to understand identifiability of discharge given uncertainty in bathymetry and friction. The developed methodology and software seem useful in the context of the future SWOT satellite mission.
Département DISCO « Dynamiques Interne et de Surface des Continents » 31 Décembre 2018 L'hydrolog... more Département DISCO « Dynamiques Interne et de Surface des Continents » 31 Décembre 2018 L'hydrologie à l'IRD Hydrology has evolved as a transdisciplinary, datadriven science in a remarkably short period of time. Today, hydrology is a vibrant field that recognizes plants, landforms and human activity as key factors influencing the movement, quality and cycling of water.
Irrigation canals have a series structure which is generally used to design multivariable control... more Irrigation canals have a series structure which is generally used to design multivariable controllers based on the aggregation of decentralized monovariable controllers. SISO controllers are designed for each canal pool, assuming that the interactions will not destabilize the overall system. It is shown that, when the canal pools are controlled using the discharge at one boundary, the multivariable decentralized control structure is stable if and only if the SISO controllers are stable. The performance of the multivariable system is also investigated, and it is shown that the interactions decrease the overall performance of the controlled system. This loss of performance can be reduced by using a feedforward controller. Experimental results show the effectiveness of the method.
Irrigation is well known for being the largest water user, responsible for about 70% of the total... more Irrigation is well known for being the largest water user, responsible for about 70% of the total amount of fresh water withdrawals. At the same time, this irrigation contributes for about 40% of the total food production and is vital for many regions of the world such as Western USA, Australia, Southern Europe, and many countries in Asia and Africa. Recent FAO figures indicate that, by the year 2030, food production will have to be increased by about 80% with only a possible increase of 12% of the water withdrawal. One unavoidable way of being able to reach this agenda is to reduce water demand by improving the hydraulic efficiency of irrigation schemes. Technical concepts involved in these modernization projects include open channel hydraulics and control engineering, which are usually taught in separate college curricula. Such projects are carried out in many places in the world, especially in developing countries, with the help of engineers, canal managers and decision makers. T...
In IIMI; CEMAGREF. International Workshop on The Application of Mathematical Modelling for the Im... more In IIMI; CEMAGREF. International Workshop on The Application of Mathematical Modelling for the Improvement of Irrigation Canal Operation, October 26-30, 1992, Montpellier, France
In Strosser, P. (Ed.), The collaboration between IIMI and CEMAGREF in Pakistan: Proceedings of a ... more In Strosser, P. (Ed.), The collaboration between IIMI and CEMAGREF in Pakistan: Proceedings of a one-day workshop, October 3, 1997, International Irrigation Management Institute, Lahore. Lahore, Pakistan: IIMI. Pakistan National Program
Journal of Computational Physics
Journal of Computational Physics
Solving data assimilation problems under uncertainty in basic model parameters and in source term... more Solving data assimilation problems under uncertainty in basic model parameters and in source terms may require a careful design of the control set. The task is to avoid such combinations of the control variables which may either lead to ill-posedness of the control problem formulation or compromise the robustness of the solution procedure. We suggest a method for quantifying the performance of a control set which is formed as a subset of the full set of uncertainty-bearing model inputs. Based on this quantity one can decide if the chosen 'safe' control set is sufficient in terms of the prediction accuracy. Technically, the method presents a certain generalization of the 'variational' uncertainty quantification method for observed systems. It is implemented as a matrix-free method, thus allowing high-dimensional applications. Moreover, if the Automatic Differentiation is utilized for computing the tangent linear and adjoint mappings, then it could be applied to any multi-input 'black-box' system. As application example we consider the full Saint-Venant hydraulic network model SIC 2 , which describes the flow dynamics in river and canal networks. The developed methodology seem useful in the context of the future SWOT satellite mission, which will provide observations of river systems the properties of which are known with quite a limited precision.
[
IEEE Control Systems Magazine
With a population of more than six billion people, food production from agriculture must be raise... more With a population of more than six billion people, food production from agriculture must be raised to meet increasing demand. While irrigated agriculture provides 40% of the total food production, it represents 80% of the freshwater consumption worldwide. In summer and drought conditions, efficient management of scarce water resources becomes crucial. The majority of irrigation canals are managed manually, however, with large water losses leading to low water efficiency. The present article focuses on the development of algorithms that could contribute to more efficient management of irrigation canals that convey water from a source, generally a dam or reservoir located upstream, to water users. We also describe the implementation of an algorithm for real-time irrigation operations using a supervision, control, and data acquisition (SCADA) system with automatic centralized controller. Irrigation canals can be viewed and modeled as delay systems since it takes time for the water released at the upstream end to reach the user located downstream. We thus present an openloop controller that can deliver water at a given location at a specified time. The development of this controller requires a method for inverting the equations that describe the dynamics of the canal in order to parameterize the controlled input as a function of the desired output. The
Operations Research/Computer Science Interfaces Series, 2015
ABSTRACT
Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management, 2015
Journal of Water Resources Planning and Management, 2015
We investigate the improvement of the operation of a four-reservoir system in the Seine River bas... more We investigate the improvement of the operation of a four-reservoir system in the Seine River basin, France, by use of deterministic and ensemble weather forecasts and real-time control. In the current management, each reservoir is operated independently from the others and following prescribed rule-curves, designed to reduce floods and sustain low-flows under the historical hydrological conditions. However, this management system is inefficient when inflows are significantly different from their seasonal average and may become even more inadequate to cope with the predicted increase in extreme events induced by climate change. In this work, we develop and test a centralized real-time control system to improve reservoirs operation by exploiting numerical weather forecasts that are becoming increasingly available. The proposed management system implements a well-established optimization technique, Model Predictive Control (MPC) and its recently modified version that can incorporate uncertainties, Tree-Based Model Predictive Control (TB-MPC), to account for deterministic and ensemble forecasts respectively. The management system is assessed by simulation over historical events and compared to the "no-forecasts" strategy based on rule-curves. Simulation results show that the proposed real-time control system largely outperforms the "no-forecasts" management strategy, and that explicitly considering forecasts uncertainty through ensembles can compensate for the loss in performance due to forecasts inaccuracy.
Operations Research/Computer Science Interfaces Series, 2015
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2000
The aim of this work is to present an application of recent methods for solving the 1 design prob... more The aim of this work is to present an application of recent methods for solving the 1 design problem, based on the Scaled-Q approach, on a high-order, non-minimum phase system. We start by describing the system which is an open-channel hydraulic system (e.g.: an irrigation canal). From the discretization and linearization of the set of two partial-derivative equations, a state-space model of the system is generated. This model is a high-order MIMO system (five external perturbations w, five control inputs u, ten controlled outputs z, five measured outputs y, 65 states x) and is non-minimum phase. A controller is then designed by minimizing the 1 norm of the impulse response of the transfer matrix between the perturbations w and the outputs z. Time-domain constraints are added into the minimization problem in order to force integrators into the controller. The numerical resolution of the problem proved to be efficient, despite of the characteristics of the system. The obtained results are compared in the timedomain to classical P ID and LQG controllers on the non-linear system. The results are good in terms of performance and robustness, in particular for the rejection of the worst-case perturbation.