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This study is concerned with the development of model-free adaptive control (MFAC) of microwave heating process for the industry application of microwave energy. Precise control of the material's time–temperature profile is essential for preventing thermal runaway. To achieve good tracking performance a data-driven MFAC with input constrain is proposed since it is hard to establish an accurate dynamic model of microwave heating process. The stability of the proposed MFAC algorithm is analyzed. The proposed techniques are implemented and tested on a simple one-dimension non-linear thermodynamics model of the heated product in microwave heating process and the microwave heating system in laboratory, respectively. Simulation and experimental results are presented to compare MFAC with and without considering power input constraint to demonstrate the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Highlights • The receding horizon H ∞ controller is improved for tracking temperature spectrum. • The spectral Galerkin method is improved to derive the microwave heating ODE model. • The controller can tradeoff the relationship of input, boundary and permittivity. • With the help of ODE model and FDTD method, the controller can be implemented. Abstract This paper considers the problem of tracking control for the coupled thermal-electromagnetic model with temperature-dependent permittivity in microwave heating process, where the incident electrical field is subject to the asymmetrical saturation. Due to the nonhomogeneous Neumann boundary condition and inherent infinite-dimensional characteristics for microwave heating process, it is difficult for us to readily design and implement tracking controller. With the help of improved spectral Galerkin method, the traditional partial differential equation (PDE) model is transformed into the linear finite-dimensional ordinary differential equation (ODE) model which can be subsequently used for controller design. Then, the receding horizon H ∞ control strategy is improved to stabilize the derived uncertain ODE error model with asymmetrical input saturation and bounded external disturbance. The outcome of improved algorithm is formulated as a linear matrix inequalities (LMIs) optimization problem, which can be on-line updated by applying the finite-different time-domain (FDTD) method. Finally, the improved control strategy is successfully applied in one-dimensional cavity model for tracking temperature spectrum. [ABSTRACT FROM AUTHOR]

Thermal runaway is a critical feature of microwave lignite drying, which leads to the combustion of lignite. An expert control system (ECS)-based multimode hybrid switching control strategy is developed to solve it. The control strategy has three control modes, which contain two proportional integral derivative modes and a zero mode. Two knowledge-based ECS interface machines of the hybrid switching control strategy are built for mode switching and auxiliary decision. Experimental results demonstrate that fixed microwave power levels lead to the thermal runaway phenomenon during lignite drying process. Using the proposed hybrid switching control strategy, the wet lignite can be safely and efficiently dried to achieve the objective (moisture content 7%). Finally, based on the drying curves, the microwave lignite drying behaviors are adequately represented by the Wang and Singh model, which provides the best description (R2 = 0.9913) for the experimental results. [ABSTRACT FROM PUBLISHER]

In the traditional microwave heating partial differential equation (PDE) model, one of the main characteristics is the infinite-dimensional nature, which does not allow to readily design and implement a controller. Motivated by this obstruction, this paper proposes a microwave heating finite-dimensional ordinary differential equation (ODE) model, which can not only describe the thermodynamics field with nonhomogeneous boundary conditions but also be coupled with the variation of electromagnetic field in temperature-dependent dielectric media. Initially, the equivalent PDE model with a homogeneous boundary condition is derived by constructing an auxiliary function in order to directly derive the eigenspectrum of the spatial differential operator. With the help of model-reduction techniques, the dominant dynamics of temperature distribution are subsequently captured with a reasonable Galerkin truncation. The simulation results on microwave heating a water prototype show that the temporal and the spatial evolution of the temperature profile can be described by solving the temperature-dependent electromagnetic field and the finite-dimensional ODE model. Moreover, the effectiveness of the model is verified by comparing with the numerical results from the traditional COMSOL model. A further development of this ODE model may provide a useful numerical tool for the design and synthesis of microwave heaters to avoid thermal runaway phenomena. [ABSTRACT FROM PUBLISHER]

In this paper, the problems of two-dimensional temperature distribution for the microwave heating process are analyzed and discussed. Different from the traditional models in previous literature, the paper proposes several two-dimensional global temperature models which consist of explicit dissipation powers. By analyzing microwave propagation characteristics and spatial distribution of dominant modes into the rectangular medium, the different dissipation powers in different microwave applications are derived, such as the short waveguide, long waveguide and resonant cavity. Then, substituting the proposed dissipation powers into heat transport equation, the simplified temperature models are obtained. For further validation, traditional finite element models in COSMOL Multiphysics are used to compare the proposed temperature models in the same parameters. The comparative results show that the mathematical models can approximately predict the global temperature variation and hot spot distribution in two-dimensional rectangular medium. [ABSTRACT FROM AUTHOR]

In microwave heating applications, Lambert’s law is a common way to calculate power distribution. However, because of the complex application environment, Lambert’s law is not precise for the unknown power distribution on material surfaces. During the microwave heating process, the system process parameters can only be partly known by experience. Therefore, for such situations, to make the entire heating process safe, a sliding mode combined with a neural network algorithm is proposed. The algorithm is designed to calculate the suitable input power at each control period to make the material temperature follow the reference trajectory, which is determined by experience. The simulation and actual application results demonstrate that the proposed algorithm can commendably control the heating process. The difference between the reference trajectory and the material sampling temperature may exceed 1°C initially. However, as time progresses, the difference gradually decreases. Nonetheless, due to the low conduction coefficient, a single microwave heating process may take a long time. Therefore, many actual applications combine convective heat transfer with microwave. This article also discusses the control method of multiple inputs including microwave power and convective heat transfer with unknown model parameters. Another neural network is constructed to identify the unknown parameters. The algorithm is designed to obtain the suitable input power and input convective heat transfer at each control period. The simulation results show that the control algorithm can work well under multiple inputs. The material temperature on both the surfaces and the interior can follow the reference trajectory with a satisfactory difference, and suitable inputs can be obtained with few fluctuations during the learning process. [ABSTRACT FROM PUBLISHER]