Model Predictive Control (MPC) of System Identified Continuous Stirred Tank Reactor (CSTR) with Constraints

Author(s):  
Vennela Thamminaidu ◽  
Shihabudheen K V
2011 ◽  
Vol 403-408 ◽  
pp. 3454-3460
Author(s):  
Fazlollah Armoon ◽  
Hooshang Jazayeri-Rad

Since chemical reactors are utilized to produce specific and valuable products, concentration of products should be regulated at a specified level. As a disturbance input, a change in the inlet concentrations can vary the product concentration. So, in order to regulate the product concentration, the inlet concentrations and the product concentration should be measured. However, measurement of concentration encounters some problems such as high cost and time delay. For compensation of these failures, estimation of concentration has been proposed. In this work, the inlet concentration and the product concentration of a continuous stirred-tank reactor (CSTR) are estimated based on the moving horizon state estimation (MHSE), and the product concentration is regulated based on the model predictive control (MPC). Simulation results indicate that the proposed strategy improves the performance of the CSTR compared with the method in which the inlet concentration is not estimated.


2013 ◽  
Vol 760-762 ◽  
pp. 1000-1003
Author(s):  
Shi Li ◽  
Xi Ju Zong ◽  
Yan Hu

This paper is concerns with the study of model predictive control of continuous stirred-tank reactor (CSTR). Firstly, a nonlinear mechanical model is established for a typical CSTR. Based on mass balance and energy balance, a set of ordinary differential equations are derived. Then, the model is linearized at steady-state point to obtain state space model, which is used in model predictive control (MPC). Finally, MPC strategy is applied, controller parameters and process constrains are discussed.


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