Model predictive control of a mimo system
Model 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. M...
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| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/69519 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Model 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. |
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