• Vol 10, No 3 (2019)
  • Chemical Engineering

Inverted Decoupling 2DoF Internal Model Control for Mimo Processes

Juwari Purwo Sutikno, Zahrotul Azizah, Renanto Handogo, Riza Aris Hikmadiyar, Anwaruddin Hisyam

Corresponding email: juwari@chem-eng.its.ac.id


Cite this article as:
Purwo Sutikno, J., Azizah, Z., Handogo, R., Aris Hikmadiyar, R., Hisyam, A., 2019. Inverted Decoupling 2DoF Internal Model Control for Mimo Processes. International Journal of Technology. Volume 10(3), pp. 502-511
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Juwari Purwo Sutikno Chemical Engineering Department, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia
Zahrotul Azizah Chemical Engineering Department, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia
Renanto Handogo Chemical Engineering Department, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia
Riza Aris Hikmadiyar Chemical Engineering Department, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia
Anwaruddin Hisyam 2Faculty of Chemical and Natural Recourses Engineering, Universiti Malaysia Pahang, 26300 Gambang, Kuantan, Malaysia
Email to Corresponding Author

Abstract
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In general, the multiple-input-multiple-output (MIMO) system is the main method of process control in industry. However, the interaction between variables in the process is a challenge when designing controllers for the system. Strong interaction worsens system performance. Inverted decoupling plays an important role in reducing interaction in the process. Internal model control (IMC) is the controller used in this research. A one degree of freedom (1DoF) IMC controller is only able to provide a good response to set-point tracking, and has a slow response to disturbance rejection. Therefore, a controller that has a good response to set-point tracking and disturbance rejection is a two degrees of freedom (2DoF) IMC. The tuning method uses maximum peak gain margin (Mp-GM) stability criteria based on the uncertainty model. In this study, a reduction in interaction was realized by the addition of inverted decoupling to the 2DoF IMC control scheme. The Wardle & Wood and Wood & Berry column distillation models are given as illustrative examples to demonstrate the performance of the inverted decoupling 2DoF IMC control scheme. A comparison is made of the IAE values of 1DoF IMC, 2DoF IMC, decoupling 2DoF IMC, and inverted decoupling 2DoF IMC, with inverted decoupling 2DoF IMC showing the lowest IAE value.

Interaction; Inverted decoupling; MIMO system; Mp-GM tuning; 2DoF IMC

Introduction

Time delay and coupling are problems that widely occur in industry, especially in the MIMO process (Jin et al., 2016). Coupling is the interaction between process variables and causes difficulties in designing MIMO controllers. One approach to overcoming coupling is by adding additional controllers called decouplers (Seborg et al., 2011). This method is very easy to implement and understand. There are different types of decoupling, such as ideal, simplified, and inverted decoupling, which are often used for industrial process control (Garrido et al., 2014; Li & Chen, 2014). Ideal decoupling is very easy to use in the design of controllers, but it is rarely employed because it has complicated decoupling elements. Simplified decoupling has a simple decoupler, but the decoupling process is complicated, while inverted decoupling can overcome the weakness of simplified decoupling and achieve the ideal decoupling goals (Chen & Zhang, 2007).

Wahid and Ahmad (2016) improved multi-model predictive control, which is used to control the distillation column. This method can reject very large disturbances. The PID controller has been discussed in the literature (Mohebbi & Hashemi, 2016; Mohebbi & Hashemi, 2017).  However, this has a weakness, which is the presence of new disturbance known after measuring output. Haura et al. (2017) simulated a refinery used oil distillation column using a 1DoF IMC controller, achieving a very good response for set-point change (servo problem). Unfortunately, set-point tracking and load-disturbance rejection in the 1DoF IMC controller scheme cannot be regulated or optimized separately. When the parameters are used for set-point tracking, a slow response to load-disturbance rejection is obtained, and vice versa. This means that it is very difficult to achieve stable and robust control simultaneously between set-point tracking and load-disturbance rejection. Sutikno et al. (2013) developed a 2DoF IMC with the Mp-GM (Maximum peak – Gain Margin) tuning method to obtain IMC control parameters. 2DoF IMC can overcome set-point tracking and load-disturbance rejection separately, without affecting each other. The method was used in the process of containing parametric uncertainty and obtained a very good response. However, the method is still limited to the SISO (Single Input Single Output) system, while processes in industry consist of many variables that interact with each other, so further research into Mp-GM tuning in the MIMO system is needed. Astuti et al. (2015) proposed Mp tuning for the MIMO system that was implemented on the Wood & Berry distillation column. The response showed good results for set-point tracking, but gave unsatisfactory results when there was a disturbance in the system. Sutikno et al. (2017) proposed a MIMO system able to represent an industrial process called the quadruple tank system. However, interactions between process variables in this system are strong, and an IMC controller with Mp-GM tuning is not fully able to overcome these. This means the MIMO system requires an additional controller to reduce interaction. The purpose of this study is to add additional controllers called inverted decoupling to the 2DoF IMC scheme, with the design objective to reduce interaction significantly. The system used is MIMO 2×2, which has two inputs and two outputs that interact with each other. The tuning method used in this study is Mp-GM tuning. 

Conclusion

In this study, the system used was MIMO 2×2 with Mp-GM tuning. Four controllers were used to compare the results, namely 1DoF IMC, 2DoF IMC, decoupling 2DoF IMC, and inverted decoupling 2DoF IMC. The results show that inverted decoupling produces the lowest IAE value compared to the other controllers.  This structure is able to reduce the interaction between variables in the MIMO 2×2 process.

Acknowledgement

Thanks to the Institut Teknologi Sepuluh Nopember (ITS) through its Fresh Graduate Scholarship Program, LPPM ITS, Chemical Engineering Department FTI-ITS, and Process Design and Control Laboratory Chemical Engineering ITS.

References

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