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Simulation and Control of a Methanol-To-Olefins (MTO) Laboratory Fixed-Bed Reactor

机译:甲醇制烯烃实验室固定床反应器的模拟和控制

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In this research, modeling, simulation and control of a methanol-to-olefins laboratory fixed-bed reactor with electrical resistance furnace has been investigated in both steady-state and dynamic conditions. The reactor was modeled as a one-dimensional pseudo-homogeneous system. Then, the reactor was simulated at steady-state conditions and the effect of different parameters including inlet flow rate, inlet temperature and electrical resistance temperature on reactor performance was studied. Results showed that the most effective parameter is electrical resistance temperature. Thus, it was selected as manipulating variable for controlling product quality. In the next step, dynamic simulation of the process was performed and the effect of different disturbances on the dynamic behavior of the reactor was assessed. Finally, PID and Neural Network Model Predictive (NNMP) controllers were utilized for process control, and their performances were compared to each other. The response of the control system to different disturbances and set point changes showed that both PID and NNMP control systems can maintain the process at the desired conditions. PID controller had smaller rise time and no offset compared to NNMP controller while NNMP controller had smaller overshoot.
机译:在这项研究中,已经研究了在稳态和动态条件下带电阻炉的甲醇制烯烃实验室固定床反应器的建模,仿真和控制。反应器被建模为一维伪均质系统。然后,在稳态条件下对反应器进行了模拟,并研究了包括入口流速,入口温度和电阻温度在内的不同参数对反应器性能的影响。结果表明,最有效的参数是电阻温度。因此,它被选作控制产品质量的操作变量。在下一步中,进行了过程的动态模拟,并评估了不同干扰对反应器动态行为的影响。最后,将PID和神经网络模型预测(NNMP)控制器用于过程控制,并将它们的性能进行了比较。控制系统对不同干扰和设定点变化的响应表明,PID和NNMP控制系统都可以将过程保持在所需的条件下。与NNMP控制器相比,PID控制器的上升时间更短且没有偏移,而NNMP控制器的过冲更小。

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