Tomography-assisted control for the microwave drying process of polymer foams. (June 2022)

• Record Type: Journal Article
• Authors: Hosseini, Marzieh; Kaasinen, Anna; Link, Guido; Aliyari Shoorehdeli, Mahdi; Lähivaara, Timo; Vauhkonen, Marko
• Is Part Of: Journal of process control. Volume 114(2022)
• Page Start: 16
• Page End: 28
• Publication Date: 2022-06
• Subjects: LQG control -- PI control -- System identification -- Process tomography -- Electrical capacitance tomography -- Microwave drying; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2022.03.011
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract: This paper presents the integration of electrical capacitance tomography (ECT) with a moisture controller for the microwave drying of polymer foam. The proportional–integral (PI) control and the linear quadratic Gaussian (LQG) control are employed in designing the controller. The control objective in this process is that the moisture of polymer foam after the drying process reaches the desired set point. The permittivity distribution of polymer foam after the drying process is estimated in real-time using a designed ECT sensor and transferred as feedback to the controller. Since the permittivity and the moisture are strongly correlated, the material moisture can be controlled by controlling the permittivity. A state-space model is derived for the microwave drying process based on a system identification approach using the experimental data from the process. The derived model is employed in designing the LQG controller and adjusting the parameters of the PI controller. The designed controllers are implemented on a testbed microwave oven, and the experimental results show that the designed controllers are able to follow the desired set point moisture. The performance of the system with both controllers is compared, and their advantages and disadvantages are discussed. Moreover, the benefits of having a moisture controller for the microwave drying process are shown in simulation studies compared to an uncontrolled system. Highlights: Electrical capacitance tomography (ECT) to estimate the moisture distribution Modeling the microwave drying process using the system identification approach Combining the process tomography and control to achieve the desired moisture Implementing a proportional–integral (PI) controller to track the set point moisture Designing a linear quadratic Gaussian (LQG) controller using a black-box model