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A Design Method of a Model-following Control System
Hiroki Shibasaki,Rubiyah Yusof,Yoshihisa Ishida 제어·로봇·시스템학회 2015 International Journal of Control, Automation, and Vol.13 No.4
This paper describes and demonstrates a model-following control system that is based on a switching function where an optimal gain matrix is determined by the LQR method. In our proposed method, the optimal gain matrix is derived such that it does not depend on the plant parameters. Simulation results show various cases including the nominal plant and the plant with a modeling error. The experimental study is also performed using a DC motor. The simulation and experimental results show that the proposed method has superior effectiveness.
Parvaneh Shabanzadeh,Rubiyah Yusof,Kamyar Shameli 한국공업화학회 2015 Journal of Industrial and Engineering Chemistry Vol.24 No.-
In this study, artificial neural network (ANN) was used to develop an approach for evaluation of silver nanoparticles (Ag–NPs) size in the bionanocomposites substrate. A multi-layer feed forward ANN was applied to correlate the output as size of Ag–NPs, with four inputs include of AgNO3 concentration, temperature of reaction, weight percentage of starch, and MMT amount. The results of proposed methodology were compared for its predictive capabilities in terms of coefficient determination (R2) and mean square error (MSE) based on the validation data set. The model finding revealed that AgNO3 concentration content has significant effect on size of Ag–NPs.