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首页> 外文期刊>Journal of control, automation and electrical systems >Flatness-Based Decentralized Adaptive Backstepping Control of Cascaded DC DC Boost Converters Using Legendre Polynomials
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Flatness-Based Decentralized Adaptive Backstepping Control of Cascaded DC DC Boost Converters Using Legendre Polynomials

机译:使用Legendre多项式的级联直流DC升压转换器的平面基于平面的分散自适应反转控制器

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In this paper, decentralized adaptive backstepping control of cascaded DC DC boost converters is studied in the presence of load and voltage uncertainties and interactions between the converters. First, a cascaded boost converter average model that covers both continuous and discontinuous conduction modes is extracted. Afterward, flatness property is applied to transfer the cascaded system states into a semi-canonical form. Further, a novel decentralized backstepping controller is proposed to track the reference voltages. In this control strategy, Legendre polynomials are utilized to estimate the uncertainties and interactions adaptively. The control method is simple and robust with less computational burden due to the polynomial estimator s application. Various simulations are performed for the cascaded DC DC boost converters to indicate the effectiveness and performance of the proposed controller under the load and supply voltage changes.
机译:在本文中,在负载和电压不确定性的存在和转换器之间的相互作用中研究了级联DC DC升压转换器的分散式自适应反转器。首先,提取覆盖连续和不连续传导模式的级联升压转换器平均模型。之后,将平坦度特性应用于将级联的系统状态转移成半规范形式。此外,提出了一种新颖的分散的反向控制器以跟踪参考电压。在该控制策略中,使用Legendre多项式用于自适应地估计不确定性和相互作用。由于多项式估计器S应用,控制方法简单且坚固,具有较少的计算负担。对级联的DC DC升压转换器执行各种模拟,以指示所提出的控制器在负载和电源电压变化下的有效性和性能。

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