Design and co-simulate control of an extractive distillation column using Aspen plus dynamics with MATLAB and simulink toolbox
Khairul Sham, Muhammad Syahmi (2016) Design and co-simulate control of an extractive distillation column using Aspen plus dynamics with MATLAB and simulink toolbox. Honours thesis, Murdoch University.
This case study investigates the co-simulation of an extractive distillation column using Aspen Dynamics together with MATLAB Simulink toolbox. This extractive distillation column separates Methyl Cyclo Hexane (MCH) from Toluene by using input Phenol as a third component (entractant) to move the ternary system beyond the azeotropic point. The study started with testing the steady state model of the process in Aspen Plus; then continued with importing and testing the process dynamic model in both manual and automatic modes using Aspen Dynamics. Finally, the process model in Aspen Dynamics was connected to the built-in controllers in Simulink then the co-simulation of the controlled process was performed using Aspen Dynamics together with the MATLAB Simulink toolbox.
The case study was an example taken from Aspen Dynamics version 8.4v. With the newest version of Aspen Dynamics and Simulink version 8.4 operating platform Windows 7, it is required to install the 32 bit MATLAB to address compatibility issues between Aspen Dynamics and MATLAB.
The same control system design including four conventional controllers was implemented by Aspen Tech in two different software package structures: in Aspen Dynamics stand-alone simulations and in Aspen Dynamics – Simulink co-simulations to control the feed tank level, reboiler level, reflux drum level and top stream pressure of column by adjusting feed 2 flowrate, coolant flowrate to condenser, bottom (Toluene and Phenol) flowrate and product (MCH) flowrate. Then a new controller was developed in Aspen Dynamics and co-simulation to control the product (MCH) purity by adjusting entrainer (Phenol) flowrate. Advanced controller (DMC) has tried to be developed in co-simulation to replace PI controller. However, attempts to develop DMC had failed after few trials.
All conventional controllers were tuned using auto tuning method in Aspen Dynamics using a special tool, which is 'tuning' tool. It gives the best control parameters to achieve the best possible control response. Set point changes and disturbance changes have been made to PI controllers and variables respectively, and it is intended to investigate the effect on product purity. The new controller is very helpful in improving the level of product purity. All run shows that Aspen Dynamics stand alone, or co-simulation gives the same results in every test.
Before developing Dynamics Model control (DMC) in co-simulation, DMC examples exercises from ‘ENG 420’ was implemented on a simple first order system in MATLAB to understand the basics of the predictive control strategy along with the effect of design parameters.
All results obtained are discussed in Section Results and Discussion. Guideline for the next thesis student has been outlined at the end of this report. Overall, most of the main objectives of this thesis was achieved with very satisfying results. However due to unforeseen circumstances and time constraints, DMC controller is not fully functional.
|Publication Type:||Thesis (Honours)|
|Murdoch Affiliation:||School of Engineering and Information Technology|
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