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

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

Modeling and control of a multiple-pool channel

Questa tesi tratta l'analisi di un sottoinsieme della rete di canali del Cavallino, situata lungo la costa Veneziana che si estende da Punta Sabbioni al porto di Piave Vecchia. In particolare, questo lavoro si focalizza su modellizzazione, stima e controllo di una sequenza di canali, assumendo che le misure relative al livello della supercie dell'acqua e la posizione delle strutture di controllo siano disponibili. Una procedura basata su identificazione dei sistemi consente di analizzare e selezionare il modello grey box migliore tra quelli proposti tra ARX e OE, con l'obiettivo di stimare l'andamento del livello dell'acqua. L'obiettivo del controllo è regolare il livello dell'acqua della rete agendo sulle strutture idriche di controllo. Di conseguenza, viene proposto un tipo di controllo decentralizzato. In particolare, viene sfruttato il controllo multivariabile del livello dell'acqua a monte della struttura di controllo, tenendo in considerazione sia chiuse in superficie che sotto il livello dell'acqua. La soluzione proposta è implementata nell'ambiente Matlab e Simulink e si basa su controllori PI aumentati con un filtro passabasso, al fine di controllare il livello dell'acqua in caso di perturbazione di una sequenza di canali consecutivi.This project deals with the analysis of a subset of the water channel network of the Cavallino, that is the section of the Venetian coast that extends from Punta Sabbioni to Piave Vecchia harbor. In particular, this work focuses on modeling, estimation and control design of a multiple channel pools system, assuming that water level measurements and control structure position are available. A system-identication-based procedure is considered for the analysis and selection of an ARX and an OE grey box model, to estimate and control purposes. The control aim is to regulate the water level of the channel network by acting on the hydraulic structure position. Then, a decentralized control is implemented. In particular, a multivariable local upstream control strategy is exploited, involving a model that takes into account both weirs and gates hydraulic control structures. Lastly, a solution is implemented in Matlab and Simulink, based on PI controllers augmented with lowpass filters, in order to control the water level of multiple pools connected in series

New offset-free method for model predictive control of open channels

Irrigation or drainage canals can be controlled by model predictive control (MPC). Applying MPC with an internal model in the presence of unknown disturbances in some cases can lead to steady state offset. Therefore an additional component should be implemented along with the MPC. A new method eliminating the offset has been developed in this paper for MPC. It is based on combining two basic approaches of MPC. It has been implemented to control water levels in the three-pool UPC laboratory canal and further numerically tested using a test case benchmark proposed by the American Society of Civil Engineers (ASCE). It has been found that the developed offset-free method is able to eliminate the steady-state offset, while taking into account known and unknown disturbances.Peer ReviewedPostprint (author's final draft

Integrated simulation and optimization scheme of real-time large-scale water supply network: applied to Catalunya case study

This paper presents an integrated simulation and optimization modeling approach in order to provide the optimal configuration for large-scale water supply systems (LSWSS) in real time. Model predictive control (MPC) has been chosen to handle the complex set of objectives involved in the management of LSWSS. The computation of control strategies by MPC uses a simplified model of the network dynamics. The use of the combined approach of optimization and simulation contributes to making sure that the effect of more complex dynamics, better represented by the simulation model, may be taken into account. Coordination between simulator and optimizer works in a feedback scheme, from which both real-time interaction and extensive validation of the proposed solution have been realized using a case study based on the Catalunya regional water network.This research has been partially funded by by Project ECOCIS DPI2013-48243-C2-1-R of Spanish Ministry of Education and by EFFINET grant FP7- ICT-2012-318556 of the European Commission.Peer Reviewe

Predictive Adaptive Control of water level in canal pools

A case study on the use of a predictive adaptive algorithm to control pool level in a pilot water distribuition canal is described. The algorithm is a modification of the basic MUSMAR controller that includes parallel integral action and, in the case of multiple pools, feedforward action to coordinate the gates. Experimental results in the case of a single pool and simulations for multiple pools are presented. The contributions of the paper stem from the explicitation of rules for tuning the adaptive controller in a practical situation and from the coordination of different pools using reduced complexity controllers and feedforward in a multivariable settin

Multi-Platform Controller Interface for SCADA Application

This paper concerns the development of a SCADA-Controller Interface (SCI) application for an open-channel experimental facility. Water delivery canals are complex and spatially distributed systems. The proposed application is to be applied to test control algorithms developed by several research groups with different technical approaches. The proposed interface allows the development of controllers in different environments - C/C++, MATLAB/Simulink and GNU Prolog - and may be easily extended to other environments. The experimental facilities with the used instrumented canal, the programmable logic controller (PLC) network and the SCADA system are also described in this paper. Finally, some software experimental results are presented

Adaptive and predictive control architecture of inland navigation networks in a global change context: application to the Cuinchy-Fontinettes reach

In this paper, an adaptive and predictive control architecture is proposed to improve the management of inland navigation networks in a global change context. This architecture aims at ensuring the seaworthiness conditions of inland navigation networks, and to improve the efficiency of the water resource management. It is based on supervision and prognosis modules which allow the estimation of the current state of the network, and the forecasting of the extreme event occurrence. According to these indicators and to the management constraints and objectives, control strategies of the inland navigation networks will be adapted to limit the impacts of the extreme events. To achieve this aim, three challenges are considered and discussed in this paper. The first one consists in proposing an accurate modeling approach of navigation reaches which are characterized by large scale, nonlinearities, time delays, unknown inputs and outputs, etc. The second one is to increase the knowledge about potentiality of extreme events, consequences of the climate change. The prediction of these events is rather complex due to their rarity, the spacio-temporal scale of the networks, etc. Finally, the third one is the pooling of the two first contributions, i.e. the model of the system and the knowledge about extreme events. Thus, the resilience of the system and the adaptation of the management strategies could be realizedPeer ReviewedPostprint (author’s final draft