Variable Determined for Optimization of Alternating Energy on the Load by the Adaptive Taguchi Method

Abstract

It is important to find the optimum point in terms of energy quality in the studies for electrical energy conversions with the converter and inverter circuits. In such studies, it has been tried to find the optimum operating point by using control systems such as PID and Fuzzy Logic in closed-loop controls. When a large number of variables are involved in finding the optimum point, closed-loop control methods such as these may be insufficient to find the optimum point. Therefore, in this study, the Adaptive Taguchi Method (ATM) with the maximum-minimum value is used for the estimation of variables providing the optimum point for energy quality by using it in a multilevel inverter with a double dc-dc converter. While in traditional Taguchi Methods, dependent variables predict the results by revealing their effects on independent variables, in ATM, besides the effects of the independent variables, the effects of different dependent variables on each other are also estimated. First, the system to which the ATM will be applied is introduced. Then, the principles of applying the ATM are explained. In the known Taguchi method, variable values to be found with 34 = 81 trials, variables are estimated with 27 trials, while the values of two different dependent variables in the system can be found with 54 trials instead of 2x34 = 2x81 trials. The resulting values to be estimated with the proposed ATM method are estimated with 27 trials instead of 2x81 or 54 trials. Finally, the observation results to be used for estimation are analyzed and evaluated. By trying the prediction results, it is seen that the proposed system is quite effective because the estimated result value that is %3.71 in the experiments gives a lesser distortion value than the values used for prediction.

Determination of Optimized Mix Design of Reactive Powder Concrete

“…Te Taguchi method which was used in previous studies [29][30][31][32][33] is applicable to RPC mix designs and related issues. Studies that have used this approach include assessing the optimal mixture of recycled aggregate concrete [34], analyzing the fexural strength of concrete pavement using fy ash and silica fume [35], optimizing the concrete mix design [36,37], optimizing the compressive strength [38], investigating the efect of high temperature on RPC compressive strength [39], optimizing the mechanical properties of glass fber-reinforced concrete mixtures [22], and investigating the heating degree on concrete compressive strength and its crack length [40].…”