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Robust control of nonlinear uncertain systems under generalized matching conditions using neuro-compensator

机译:使用神经补偿器的广义匹配条件下非线性不确定系统的鲁棒控制

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The robust adaptive control scheme with neural-compensator is developed for a class of uncertain systems satisfied the generalized matching condition. In the control procedure, the neural compensator is combined with the feedback linearization method, and the neural network is implemented to learn and compensate the uncertainty, rescale the uncertainty of nonlinear systems to the reconstruction error of the network, and a sliding mode controller is used to deal with the uncertainty due to the reconstruction of the network. No property of the uncertainty is used for the design, it is more practical than the existing ones in the literature.
机译:针对一类满足广义匹配条件的不确定系统,开发了带有神经补偿器的鲁棒自适应控制方案。在控制过程中,将神经补偿器与反馈线性化方法相结合,并采用神经网络来学习和补偿不确定性,将非线性系统的不确定性重新定标为网络的重构误差,并使用滑模控制器。应对由于网络重建带来的不确定性。该设计没有使用不确定性的属性,它比文献中的现有属性更实用。

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