用伺服控制提升非完整车辆寻源速度，通过新扰动方式加速局部地图探索。
Servos for Local Map Exploration Onboard Nonholonomic Vehicles for Extremum Seeking
- 将扰动从正弦扩展为有界周期函数，支持多变量高阶导数估计。
- 在仿真与实测中，伺服辅助探索使车辆寻源收敛速度显著加快。
- 适用于需快速定位信号源的移动机器人系统，如环境监测或搜救。
极值搜索控制（ESC）通常采用基于扰动的导数估计方法，通过将单个传感器输出与时间变化函数相乘来实现。以往研究多使用正弦扰动，可估计标量映射的任意阶导数或多元映射的三阶以下导数。本文将扰动扩展至有界周期或几乎周期函数，考虑多元映射情形。给出了判定是否存在时间变化函数以估计任意阶多元映射导数的充要条件。该结果被应用于非完整车辆的源寻址控制器，车辆配备由伺服驱动的传感器。仿真与真实实验表明，通过将局部地图探索任务分配给伺服装置，非完整车辆实现了更快的源定位收敛。
原文摘要 · Abstract (English)
Extremum seeking control (ESC) often employs perturbation-based estimates of derivatives for some sensor field or cost function. These estimates are generally obtained by simply multiplying the output of a single-unit sensor by some time-varying function. Previous work has focused on sinusoidal perturbations to generate derivative estimates with results for arbitrary order derivatives of scalar maps or higher up to third-order derivatives of multivariable maps. This work extends the perturbations from sinusoidal to bounded periodic or almost periodic functions and considers multivariable maps. A necessary and sufficient condition is given for determining if time-varying functions exist for estimating arbitrary order derivatives of multivariable maps for any given bounded periodic or almost periodic dither signal. These results are then used in a source seeking controller for a nonholonomic vehicle with a sensor actuated by servo. The conducted simulation and real-world experiments demonstrate that by distributing the local map exploration to a servo, the nonholonomic vehicle was able to achieve a faster convergence to the source.
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