Application of Neural Network to Identify Black box Model of Twin Rotor MIMO System Based on Mean Squared Error Method


Authors : Huong T.M. Nguyen; Mai Trung Thai

Volume/Issue : Volume 6 - 2021, Issue 7 - July

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/3lUWwQY

In model predictive control, building the correct model and solving the optimal problem are two jobs that always require lots of time. These are also two issues that many scientists are interested in studying when applying model-driven reporting control to certain objects. With a TRMS object, we can build a white box model, a gray box model or a black box model. Some authors have built TRMS model published in [2], [3], [4], [5]. We have studied the solving methods of optimal problem in model predictive control in [6], [7], [8]. In [9], we built a white box model of TRMS object according to Newton method. Studying the effects of the interchannel effects of the white box model TRMS. In [10], we used Gradient descent back-propagation, and some of its conjugate algorithms to identify the TRMS model. In this paper, we applicate the neural network in order to identify black box model of twin rotor MIMO system based on mean squared error method, using these results compare to the real model so as to choose a suitable algorithm and provide the ability to apply that model in simulation and object control.

Keywords : Black Box Model, Neural Network, Yaw Angle, Pitch Angle, Identify, Mean Squared Error.

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