2012 年 132 巻 6 号 p. 897-906
Switching and ON/OFF controls are effective control techniques for control systems equipped with low-resolution actuators. They can be modeled as control systems that restrict the control input to discrete values. In this paper, a controller design method based on a machine learning technique is discussed. The relation between the current situation (previous input sequence and previous output sequence), applied input, and output evolution is learned on the basis of some machine learning methods. Specifically, different machine learning methods, such as approximate nearest neighbour (ANN) method and support vector machine (SVM) are used in this study. The trained classifier will be a controller that connects current situation and suitable control input that can drive the current output to the desired one. The effectiveness of the proposed method is verified for discrete input systems via some simulations and experiments.
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