Feedback Control of a Two-Tank System : A comparison of Linear MPC, Nonlinear MPC and PI controller
Eilola, Anna-Reetta (2024)
2024
Automaatiotekniikan DI-ohjelma - Master's Programme in Automation Engineering
Tekniikan ja luonnontieteiden tiedekunta - Faculty of Engineering and Natural Sciences
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Hyväksymispäivämäärä
2024-05-20
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202404274711
https://urn.fi/URN:NBN:fi:tuni-202404274711
Tiivistelmä
Most physical processes exhibit nonlinear behavior. In chemical and oil refining industries, nonlinear processes are very common. Even though control strategies have developed over time, nonlinear processes are still challenging to control.
Tank system is a common example of a nonlinear and integrating process, which may be challenging to control. Tank systems are important elements for optimizing production, ensuring quality control, and providing flexibility and redundancy in the process industry. In this thesis, a linear model predictive controller (MPC), a nonlinear model predictive controller, and Proportional-Integral (PI) controller were designed for a two-tank system. The controllers were tested using two simulation scenarios. In the first case, the aim was to keep levels as steady as possible, and in the second case, the aim was to keep inlet and outlet flows as steady as possible. Both scenarios were tested without disturbances, with measured disturbances and with unmeasured disturbances. The controller performances were compared with control performance indicators which were developed in this work.
The outcome of this work was that the linear model predictive controller and PI controller were the most effective in the examined cases. The linear model predictive controller was robust enough to perform well, even in the presence of measured and unmeasured disturbances. The nonlinear model predictive controller performed reasonably well without disturbances and with measured disturbances, but it was unable to handle unmeasured disturbances. The PI controller performed well due to its integral action to eliminate steady-state errors efficiently.
Tank system is a common example of a nonlinear and integrating process, which may be challenging to control. Tank systems are important elements for optimizing production, ensuring quality control, and providing flexibility and redundancy in the process industry. In this thesis, a linear model predictive controller (MPC), a nonlinear model predictive controller, and Proportional-Integral (PI) controller were designed for a two-tank system. The controllers were tested using two simulation scenarios. In the first case, the aim was to keep levels as steady as possible, and in the second case, the aim was to keep inlet and outlet flows as steady as possible. Both scenarios were tested without disturbances, with measured disturbances and with unmeasured disturbances. The controller performances were compared with control performance indicators which were developed in this work.
The outcome of this work was that the linear model predictive controller and PI controller were the most effective in the examined cases. The linear model predictive controller was robust enough to perform well, even in the presence of measured and unmeasured disturbances. The nonlinear model predictive controller performed reasonably well without disturbances and with measured disturbances, but it was unable to handle unmeasured disturbances. The PI controller performed well due to its integral action to eliminate steady-state errors efficiently.