Automatic Control of Microwave Heating System Based on PID and Evolutionary Computation

The food and beverage industry has progressed in tandem with the evolution of communication technologies. Researchers are drawn to the developing stream of modern technology, particularly microwave heating technology, which offers good temperature control. In order to optimise system efficiency, it is important to adjust the controller parameters precisely. However, the system poses a bit of a challenge to control and stabilize the optimum temperature. This is due to the generated temperature is affected by several factors such as load variations, changes in material properties, and electromagnetic field distribution, making the conventional control process ineffective. This paper proposed the whale optimization algorithm (WOA) and particle swarm optimization (PSO) to determine the ideal tuning parameters for Proportional–Integral–Derivative (PID) controllers. An evaluation and comparison of the method's performance is conducted against genetic algorithm (GA). The results demonstrate that the proposed PID controller with WOA achieved superior performance compared to the GA and PSO. The WOA obtained the optimal values for the proportional gain (Kp), integral gain (Ki), and derivative gain (Kd) as 1000, 80, and 80, respectively, with the lowest integral absolute error (IAE) of 214.79 and fastest convergence rate compared to the GA and PSO.