Reliability-aware zonotopic tube-based model predictive control of a drinking water network
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hdl:2117/374256
Tipus de documentArticle
Data publicació2022-06-01
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Reconeixement-NoComercial-SenseObraDerivada 4.0 Internacional
Abstract
A robust economic model predictive control approach that takes into account the reliabilityof actuators in a network ispresented for the control of a drinking water network in the presence of uncertainties in the forecasted demands required forthe predictive control design. The uncertain forecasted demand on the nominal MPC may make the optimization processintractable or, to a lesser extent, degrade the controller performance. Thus, the uncertainty on demand is taken into accountand considered unknown but bounded in a zonotopic set. Based on this uncertainty description, a robust MPC is formulatedto ensure robust constraint satisfaction, performance, stability as well as recursive feasibility throughthe formulation ofan online tube-based MPC and an accompanying appropriate terminal set. Reliability is thenmodelled based on Bayesiannetworks, such that the resulting nonlinear function accommodated in the optimization setup is presented in a pseudo-linearform by means of a linear parameter varying representation, mitigating any additional computational expense thanks to theformulation as a quadratic optimization problem. With the inclusion of a reliability index to the economic dominant cost ofthe MPC, the network users’ requirements are met whilst ensuring improved reliability, therefore decreasing short and longterm operational costs for water utility operators. Capabilities of the designed controller are demonstrated with simulatedscenarios on the Barcelona drinking water network
CitacióKhoury, B.; Nejjari, F.; Puig, V. Reliability-aware zonotopic tube-based model predictive control of a drinking water network. "International journal of applied mathematics and computer science", 1 Juny 2022, vol. 32, núm. 2, p. 197-211.
ISSN2083-8492
Versió de l'editorhttps://dl.acm.org/doi/abs/10.34768/amcs-2022-0015
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