Chang, Jia Ren (2025) Development of a digital twin for the control of flow and level systems using PID and cascade control strategies. Final Year Project, UTAR.
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Abstract
This project presents the development and validation of a digital twin for flow and level control systems, including a cascade control configuration, aiming to enhance educational platforms through sustainable and interactive learning tools. The performance of P, PI, and PID controllers was experimentally evaluated in regulating flow rate, highlighting the trade-offs between steady-state error, overshoot, and system stability. A mathematical model of the physical process was derived using first principles, linearized, and transformed into transfer functions for simulation in MATLAB Simulink. Some parameters were estimated and assumed through comparison with experimental data, achieving close alignment and confirming the model's accuracy for flow control system. Simulations of the flow, level, and cascade control systems revealed that higher proportional gains improved response time but introduced oscillations, while integral and derivative actions contributed to error elimination and improved damping, respectively. The cascade control system demonstrated enhanced stability and responsiveness by addressing disturbances at the inner-loop level. Despite some discrepancies during initial transients, likely due to simplified assumptions and unmodeled disturbances, the digital twin effectively replicates real system behaviour and serves as a valuable educational resource for control system learning and analysis. Keywords: Digital Twin, PID Controller, MATLAB Simulink, Virtual Laboratory, Engineering Education Subject area: Flow and Level Control Systems
Item Type: | Final Year Project / Dissertation / Thesis (Final Year Project) |
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Subjects: | T Technology > T Technology (General) T Technology > TC Hydraulic engineering. Ocean engineering |
Divisions: | Faculty of Engineering and Green Technology > Bachelor of Engineering (Honours) Industrial Engineering |
Depositing User: | ML Main Library |
Date Deposited: | 28 Aug 2025 11:04 |
Last Modified: | 28 Aug 2025 11:04 |
URI: | http://eprints.utar.edu.my/id/eprint/7237 |
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