The superiorities of microwave heating technology have attracted many researchers for further development. Designing a satisfying temperature control system for the microwave system is one of them. To confirm that the controller can work with good system performance, the adjustment of controller parameters is important. Most previous research about microwave control systems did not focus on the tuning problem which is presented in this work. This paper provides the use of a genetic algorithm to adjust the best parameters for a PID controller. A microwave heating system with a single microwave power input and a single output temperature probe which is identified using the ARX model is examined. Evaluation of the proposed controller was conducted in the simulation environment using MATLAB. The result shows that the genetic algorithm can obtain the most optimized parameter for PID controller which can follow a certain heating pattern. The parameters for Kp, Ki, and Kd are 998.94, 79.42, and 79.78, respectively. It can minimize the value of integral absolute error for the given setpoint to 446.11.
As one of the complex technologies in the heating process, microwave heating system has gained attentions in the recent years. A further development of microwave heating control technology becomes necessary considering its superiorities in less energy consumption, volumetric heating ability and satisfying mechanical properties. Several studies on microwave heating system modelling were conducted to encourage the controller design. This work presents the modelling of a microwave heating system using autoregressive with exogenous variables or so-called ARX. The modelling conducted in this research applied the approach of input-output identification method. The generation of input-output datasets for the identification of microwave heating system was carried out in COMSOL simulation environment using symmetrical octagonal tube cavity design with two magnetrons as the inputs and five temperature sensors as the output measurement devices. For the validation and evaluation of the approach, MATLAB identification system toolbox was utilized to find the best ARX model based on the given input-output datasets. The validation test shows that the best ARX model can reach more than 93% in the fit value given all the datasets for all the outputs, while for the evaluation using the perturbed signals from the outside of datasets, the chosen model can obtain 97.35% in the average of the fit value for all the outputs.
<p><em>Quadrocopter is an aerial vehicle platform that has become very popular among researchers from the past because it has advantages compared to conventional helicopters. The quadrocopter design is very simple and unique but seen from an unstable aerodynamic standpoint. From existing research, researchers have proposed many control system designs for quadrocopter. In this study, the author presents a fuzzy logic controller for quadrocopter. The method in this research is by designing hardware. After that the design for fuzzy controllers. Then the designed fuzzy controller is tested in the Hardware In Loop (HIL) setting. The experimental results and validation of the controller application functions are considered satisfactory and it is concluded that it is possible to stabilize quadrocopter with fuzzy logic controller.</em></p>
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