Research on Intelligent Control of a 10-Channel Microwave Input Heating Microwave Oven

Abstract

The increasing demand for precise temperature control and specialized process control in industrial microwave ovens has led to the exploration of advanced control algorithms. To address these challenges, innovative neural network control algorithms have been introduced. This article delves into the heating mechanism of a 10-channel high-power industrial microwave oven and offers a mathematical explanation for the microwave heating process in the chamber. Through MATLAB simulations, the heating process and the RBF neural network adaptive control system were investigated, demonstrating promising performance. An intelligent control system was then designed, incorporating components such as a 10-channel magnetron, microwave cavity, temperature sensor, and STM-32 microcontroller. Utilizing an RBF neural network adaptive control algorithm, this system independently adjusts 10 microwave inputs to achieve heating and maintain the desired temperature. Subsequently, a 10kW 10-channel high-power industrial microwave oven RBF neural network adaptive control system was implemented and experimentally validated for its effectiveness. This innovative approach offers adaptive intelligent control, enhancing performance across diverse operating conditions.