Ozone has strong oxidation ability and very strong reactivity with organic and inorganic substances. It also leaves no secondary contaminants, which makes it applicable in a variety of ways in many fields including chemical industry, medicine, light industry, agriculture, water treatment, etc.
With the expansion of application of ozone generators over a long period since its appearance, the power supply of ozone generation has been made in various types and many achievements have been made in the research for power quality improvement.
Nowadays, an ozone generator based on dielectric barrier discharge (DBD) is popular and the high-voltage and high-frequency inverter power supply is essential in power mode.
Hwang Kum Song, a researcher at the Nano Physics Engineering Institute, has proposed a method for a feedback control of the discharge current in a DBD type high-frequency and high-voltage power supply to keep the discharge intensity of the ozone generator constant and to improve the power efficiency.
He mapped the discharge current model of the DBD inverter source, which is subject to strong nonlinearity and model uncertainty, to a dynamic linearization (DL) model to design a model-free adaptive control (MFAC) algorithm, and conducted a simulation on Matlab Simulink. He designed an MFA controller with the control object equivalent to the simplest dynamic linear model.
The strong nonlinearity and model uncertainty inherent in the control objective reduce the control effectiveness of conventional control approaches (PID control or fuzzy-PID control) and complicates the application of intelligent control approaches.
However, MFAC method, which requires no model of a plant and only controls the input and output data of the system, is more effective in constant-current control of the DBD ozone generator. MFA controller based on compact form dynamic linearization is convenient for implementation because of its simple structure and low computational cost. In addition, optimizing the parameters of the model-free adaptive controller can achieve more flexible adaptation of the controller, eliminate most of the overshoot and improve the response speed.
The simulation results showed the improved effectiveness of the model-free adaptive controller compared to the PID controller or the fuzzy-PID controller.
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