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Training method for a sliding mode controller and quantified robustness against uncertainty

机译:滑模控制器的训练方法和针对不确定性的量化鲁棒性

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Proposes a design method of a sliding mode controller by training a neural network. The singular solution of the optimal control problem is applied to training the neural network. We focus on the robustness of the trained controller against uncertainties, and we propose a method to quantify the robustness of any kind of controllers by training another neural network. Moreover, methods to train a quantified robust controller are proposed, and they can also improve the robustness. Some numerical simulations show the effectiveness of proposed methods.
机译:通过训练神经网络提出了一种滑模控制器的设计方法。最优控制问题的奇异解被用于训练神经网络。我们专注于针对不确定性的训练好的控制器的鲁棒性,并且我们提出了一种通过训练另一个神经网络来量化任何种类的控制器的鲁棒性的方法。此外,提出了一种训练量化鲁棒控制器的方法,它们还可以提高鲁棒性。一些数值模拟表明了所提出方法的有效性。

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