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池荣虎
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教师拼音名称:chironghu

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A data-driven optimal ILC method incorporated with extended state observer for nonlinear discrete-time repetitive systems

关键字:Two term control systems;Controllers - Iterative methods - Learning systems - State estimation

摘要:In this work, a novel data-driven optimal ILC with an extended state observer for a class of nonlinear non-affine discrete-time repetitive system has been proposed. The main feature of the approach is that the controller design depends merely on the I/O data, and an ESO has been introduced for the estimation of disturbance and uncertainty. The final simulation results verify the effectiveness of the proposed method.<br/> &copy; 2018 IEEE.

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