Optimal predictive control of water transport systems: Arrêt-Darré/Arros case study

This paper proposes the use of predictive optimal control as a suitable methodology to manage efficiently transport water networks. The predictive optimal controller is implemented using MPC control techniques. The Arrêt-Darré/Arros dam-river system located in the Southwest region of France is proposed as case study. A high-fidelity dynamic simulator based on the full Saint-Venant equations and able to reproduce this system is developed in MATLAB/SIMULINK to validate the performance of the developed predictive optimal control system. The control objective in the Arrêt-Darré/Arros dam-river system is to guarantee an ecological flow rate at a control point downstream of the Arrêt-Darré dam by controlling the outflow of this dam in spite of the unmeasured disturbances introduced by rainfalls incomings and farmer withdrawals

Human-in-the-Loop Model Predictive Control of an Irrigation Canal

Until now, advanced model-based control techniques have been predominantly employed to control problems that are relatively straightforward to model. Many systems with complex dynamics or containing sophisticated sensing and actuation elements can be controlled if the corresponding mathematical models are available, even if there is uncertainty in this information. Consequently, the application of model-based control strategies has flourished in numerous areas, including industrial applications [1]-[3].Junta de Andalucía P11-TEP-812

Canal Identification for Fractional Linear Control Purposes

In this paper an LPV rational order control model of an irrigation canal is experimentally obtained by using the described LPV fractional identification procedure. Global LPV model is obtained from polynomial interpolation of local model parameters. Validation results demonstrate that rational order models are more accurate than integer order models. Therefore rational order models of an irrigation canal have an important role to play in management and efficient use of water resources.Postprint (published version

Gain-scheduling multivariable LPV control of an irrigation canal system

The purpose of this paper is to present a multivariable linear parameter varying (LPV) controller with a gain scheduling Smith Predictor (SP) scheme applicable to open-flow canal systems. This LPV controller based on SP is designed taking into account the uncertainty in the estimation of delay and the variation of plant parameters according to the operating point. This new methodology can be applied to a class of delay systems that can be represented by a set of models that can be factorized into a rational multivariable model in series with left/right diagonal (multiple) delays, such as, the case of irrigation canals. A multiple pool canal system is used to test and validate the proposed control approach.Peer ReviewedPostprint (author's final draft

Adaptive and non-adaptive model predictive control of an irrigation channel

The performance achieved with both adaptive and non-adaptive Model Predictive Control (MPC) when applied to a pilot irrigation channel is evaluated. Several control structures are considered, corresponding to various degrees of centralization of sensor information, ranging from local upstream control of the di®erent channel pools to multivariable control using only prox- imal pools, and centralized multivariable control relying on a global channel model. In addition to the non-adaptive version, an adaptive MPC algorithm based on redundantly estimated multiple models is considered and tested with and without feedforward of adjacent pool levels, both for upstream and down- stream control. In order to establish a baseline, the results of upstream and local PID controllers are included for comparison. A systematic simulation study of the performances of these controllers, both for disturbance rejection and reference tracking is shown

Adaptive and non-adaptive model predictive control of an irrigation channel

The performance achieved with both adaptive and non-adaptive Model Predictive Control (MPC) when applied to a pilot irrigation channel is evaluated. Several control structures are considered, corresponding to various degrees of centralization of sensor information, ranging from local upstream control of the di®erent channel pools to multivariable control using only prox- imal pools, and centralized multivariable control relying on a global channel model. In addition to the non-adaptive version, an adaptive MPC algorithm based on redundantly estimated multiple models is considered and tested with and without feedforward of adjacent pool levels, both for upstream and down- stream control. In order to establish a baseline, the results of upstream and local PID controllers are included for comparison. A systematic simulation study of the performances of these controllers, both for disturbance rejection and reference tracking is shown

Irrigation canal models for automatic control purposes

volumes during normal canal operation. In order to develop control algorithms for irrigation canals there is a need for simple linear models to be used in the algorithms. The following simple linear models are approximating the canal in order to give a base to develop control algorithms. The PAC-UPC laboratory canal (Prueba de Algoritmos de Control - Universitat Politècnica de Catalunya) is modelled (input and output discharge) using the following three models: Muskingum, Hayami and Integrator Delay Zero (IDZ) and the results are compared to measurements. All three models are able to describe the irrigation canal in an acceptable way. However, only the IDZ model can capture all the important characteristics. These tested models can be applied to represent real canals for control purposes where it is especially important to obtain good models without extensive measurements. Test campaigns are developped now in cooperation with the CHE (Confederación Hidrográfica del Ebro) in order to test control algorithms to be used in irrigation canals under their management.Peer Reviewe

Model Predictive Control of an Experimental Water Canal

This paper presents the first experimental results of a model predictive controller designed to control the water levels of a modern automated water canal, located at the University of Évora, Portugal. The controller is able to correctly handle known-in-advance water offtakes, while considering the most relevant physical constrains of the experimental setup. The dynamic model used is based on discretized Saint-Venant equations linearized for the steady-state regime taking into account the hydraulic structures present, such as gates and a water offtakes valves. The controller is implemented on a PLC (Programmable Logic Controller) network supervised by a SCADA (Supervisory Control And Data Acquisition) system. The experimental results demonstrate the reliability and effectiveness of the proposed control scheme in real-life typical situations, including gate malfunctioning and extreme water offtake conditions

AN ECONOMIC MODELLING APPROACH FOR VULNERABILITY ASSESMENT IN IRRIGATION FARMS IN SPAIN

Farm Management,

SCADA and related technologies

Presented at SCADA and related technologies for irrigation district modernization, II: a USCID water management conference held on June 6-9, 2007 in Denver, Colorado.SCADA systems in irrigation districts have focused on remote monitoring and remote control. In many districts, the remote control is manual, but in others the automation of structures is enabled through the usage of distributed control for the automation of individual structures. This paper presents the concept of an expanded, "umbrella" SCADA system that will perform the standard functions of remote control and remote monitoring, and will also incorporate information flow in the field for operators. The umbrella SCADA system will mesh the equipment-equipment information into an equipment-program-personnel network