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arXiv 1303.4474math.OC
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寻轨的大增益稳定性与高阶平均理论

Large Gain Stability of Extremum Seeking and Higher-Order Averaging Theory

Gabriel Bousquet, Jean-Jacques Slotine

摘要:

在小增益的限制下,证明了搜索算法的收敛性。使用平均理论和收缩分析,我们提出了一个框架,用于计算明确的界限偏离ES计划从其理想的优势阶平均动态。对于可能的大增益,界限仍然有效。它们使我们能够建立稳定性和估计收敛速度,他们开辟了选择“最佳”的ES计划的有限增益的方式。

英文摘要:

Convergence of Extremum Seeking (ES) algorithms has been established in the limit of small gains. Using averaging theory and contraction analysis, we propose a framework for computing explicit bounds on the departure of the ES scheme from its ideal dominant-order average dynamics. The bounds remain valid for possibly large gains. They allow us to establish stability and estimate convergence rates, and they open the way to selecting "optimal" finite gains for the ES scheme.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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