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Data-Driven Approach for Current Control in DC-DC Boost Converters

机译:DC-DC升压转换器中电流控制的数据驱动方法

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This work addresses the control of the inductor current in DC-DC boost converter using a data-driven approach. Model-based approaches tend to be either conservative or complex tasks when considering intrinsic non-linearities. In that sense, data-driven solutions to the control design of such processes come in handy as they do not need a plant model and, given a sufficiently rich experiment, all information needed from the system at a given operation point is obtained from data. Even for a specific data-driven method - in this work, the Virtual Reference Feedback Tuning (VRFT) - there are different ways to implement it, which allow tuning of different controller structures. In this work, we compare and apply these approaches on the control of the inductor current in a DC-DC boost converter directly on an actual plant and show that, for this kind of plant, the VRFT approach in which the inverse of the controller is identified along with the “derivative” pole outperforms the standard one.
机译:该工作解决了使用数据驱动方法控制DC-DC升压转换器中的电感电流的控制。基于模型的方法在考虑内在非线性时往往是保守的或复杂的任务。从这种感知,数据驱动的解决方案对这种过程的控制设计方便,因为它们不需要植物模型,并且给定足够丰富的实验,从数据处获得来自给定操作点处的系统所需的所有信息。即使对于特定的数据驱动方法 - 在这项工作中,虚拟参考反馈调整(VRFT) - 也有不同的方法来实现它,这允许调整不同的控制器结构。在这项工作中,我们将这些方法进行比较,并直接在实际工厂上控制电感器电流的电感电流,并表明,对于这种工厂,控制器的倒数的VRFT方法与“衍生”极点一起识别,优于标准一个。

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