Health-aware LPV-MPC based on system reliability assessment for drinking water networks

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper proposes a health-aware model predictive control (MPC) for drinking water networks that includes an additional goal to extend the components and system reliability. The components and system reliability are incorporated in the MPC model as an extra parameter varying equation that considers the control action as a scheduling variable. The main goal of this work is to exhibit the advantage of taking into account system and component reliability, computed on-line by means of an LPV-MPC algorithm through an instance dedicated to DWNs. The proposed control approach allows the controller to accommodate to the parameter changes. By computing an estimation of the state variables during prediction, the MPC model can be modified considering the estimated state evolution at each time instant. Moreover, the solution of the optimization problem associate to the MPC problem is achieved by solving a series of Quadratic Programs (QP) at each sampling time. A small part of a real water network is used as a case study for illustrating the performance of the proposed approach.Peer ReviewedPostprint (author's final draft

Economic MPC-LPV control for the operational management of water distribution networks

This paper presents an Economic Model Predictive Control (EMPC) for the operational management of water distribution networks (WDNs) with periodic operation based on embedding the nonlinearity of the model to the Linear Parameter Varying (LPV) model of WDNs. The performance of the WDN is identified by a set of difference-algebraic equations while the relation of hydraulic head/pressure and flow in connected pipes is nonlinear. In particular, the WDN model consists of two sections of nonlinear algebraic equations for bidirectional and unidirectional flows in pipes, respectively. The proposed algorithm is embedded the nonlinear algebraic equations into the LPV model. The proposed control approach allows the controller to accommodate the scheduling parameters. By computing the prediction of the state variables along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state at each time instant. This iterative approach improves the implementation efficiency and reduces the computational burden compared to the solution of a non-linear optimization problem. Finally, the proposed strategy is applied to a well-known benchmark of the Richmond WDN.Peer ReviewedPostprint (author's final draft

Economic health-aware LPV-MPC based on system reliability assessment for water transport network

This paper proposes a health-aware control approach for drinking water transport networks. This approach is based on an economic model predictive control (MPC) that considers an additional goal with the aim of extending the components and system reliability. The components and system reliability are incorporated into the MPC model using a Linear Parameter Varying (LPV) modeling approach. The MPC controller uses additionally an economic objective function that determines the optimal filling/emptying sequence of the tanks considering that electricity price varies between day and night and that the demand also follows a 24-h repetitive pattern. The proposed LPV-MPC control approach allows considering the model nonlinearities by embedding them in the parameters. The values of these varying parameters are updated at each iteration taking into account the new values of the scheduling variables. In this way, the optimization problem associated with the MPC problem is solved by means of Quadratic Programming (QP) to avoid the use of nonlinear programming. This iterative approach reduces the computational load compared to the solution of a nonlinear optimization problem. A case study based on the Barcelona water transport network is used for assessing the proposed approach performance.Peer ReviewedPostprint (published version

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Health-aware LPV-MPC based on system reliability assessment for drinking water networks

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper proposes a health-aware model predictive control (MPC) for drinking water networks that includes an additional goal to extend the components and system reliability. The components and system reliability are incorporated in the MPC model as an extra parameter varying equation that considers the control action as a scheduling variable. The main goal of this work is to exhibit the advantage of taking into account system and component reliability, computed on-line by means of an LPV-MPC algorithm through an instance dedicated to DWNs. The proposed control approach allows the controller to accommodate to the parameter changes. By computing an estimation of the state variables during prediction, the MPC model can be modified considering the estimated state evolution at each time instant. Moreover, the solution of the optimization problem associate to the MPC problem is achieved by solving a series of Quadratic Programs (QP) at each sampling time. A small part of a real water network is used as a case study for illustrating the performance of the proposed approach.Peer Reviewe