Novel extremum seeking algorithm using Wiener process
Novel extremum seeking algorithm using Wiener process
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DOI：
10.1109/med.2011.5983143
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发表时间：
2011-06
期刊：
影响因子：
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通讯作者：
K. Hoshino;Y. Yamashita
中科院分区：
文献类型：
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作者：
K. Hoshino;Y. Yamashita
提出了一种新的随机连续时间极值搜索算法。该算法比传统的随机连续时间极值搜索算法简单。该算法直接使用维纳过程来提取目标函数的梯度。三个方案，即，描述了简单方案、退火参数方案和高通滤波器方案。我们开发了一种方法来估计简单方案中系统解的概率密度的时间演化。高通滤波器方案的稳定性分析进行了讨论。仿真结果表明，所提出的系统可以获得系统的极值。
We propose a new stochastic continuous time extremum seeking algorithm. The proposed algorithm is simpler to use than conventional stochastic continuous time extremum seeking algorithms. The proposed algorithm uses the Wiener process directly to extract gradients of objective functions. Three schemes, i.e., the simple scheme, the annealing parameter scheme, and the high-pass-filter scheme, are described. We develop a method for estimating the time evolution of the probability density of the solution of the system in the simple scheme. The stability analysis is discussed for the high-pass filter scheme. It is shown that the extreme value of the system is obtained with the proposed system in simulation results.