Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/69519
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dc.contributor.authorChipurapalli Raj Shekhar
dc.date.accessioned2017-02-01T09:12:11Z
dc.date.available2017-02-01T09:12:11Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10356/69519
dc.description.abstractModel Predictive Control (MPC) is a control method that deals with the multivariable system with constraints. In this dissertation, the MPC methodology is demonstrated on the Coupled Tank System. Using the first principle method, the system parameters for the Coupled Tank System are determined. Model Validation is carried out by comparing simulated data of the model developed with the actual plant. Augmented state space model with incremental input is developed which is used to ensure offset free tracking of the set point. The appropriate choice of augmented state space model is important for the controller performance. Further, the coupled tank system is interfaced with NI DAQmx 6221E using the LabVIEW software. Many experiments has been carried out for the tuning of MPC parameters, control horizon (Nc), prediction horizon (Np) and control weighing factor (λ). The correct selection of MPC parameters are made for implementing MPC algorithm on the coupled tank system. One of the most important features of MPC method is the system constraints. Experiments are carried out when the slew rate constraints, input constraints and output constraints are applied. Comparison between MPC with constraints and MPC without constraints is done.en_US
dc.format.extent113 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleModel predictive control of a mimo systemen_US
dc.typeThesis
dc.contributor.supervisorLing Keck Voonen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
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