Model predictive control (MPC) makes use of a model of the system, therefore performances are highly dependent on the accuracy of the model chosen. Applications oriented optimal input design enables optimization of the system identification experiments. In this thesis a method of system identification for MPC applications is simulated on a multivariable nonlinear system consisting of four interconnected water tanks
Applications Oriented Optimal Input Design for MPC: An analysis of a quadruple water tank process
Balsemin, Antonio
2013/2014
Abstract
Model predictive control (MPC) makes use of a model of the system, therefore performances are highly dependent on the accuracy of the model chosen. Applications oriented optimal input design enables optimization of the system identification experiments. In this thesis a method of system identification for MPC applications is simulated on a multivariable nonlinear system consisting of four interconnected water tanksFile in questo prodotto:
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/16617