Dynamic Force Sensing Using an Optically Trapped Probing System.
Dynamic Force Sensing Using an Optically Trapped Probing System.
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DOI：
10.1109/tmech.2010.2082557
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发表时间：
2011-12-01
期刊：
影响因子：
--
通讯作者：
Menq CH
中科院分区：
文献类型：
--
作者：
Huang Y;Cheng P;Menq CH
本文提出了一种自适应观测器的设计，实现了光捕获探测系统中实时动态力传感和参数估计。根据估计与控制分离的原则，在光阱的线性范围内，该观测器的设计与反馈控制器的设计是独立的。因此，动态力传感、探针转向/夹紧和布朗运动控制可以单独开发并同时激活。自适应观测器利用捕获探针的测量运动和输入控制努力实时递归估计探针-样本相互作用力，以及探测系统捕获带宽的估计。这种能力对于在时变过程中实现精确的动态力传感非常重要，其中由于周围介质的局部变化，捕获动力学是非平稳的。自适应估计器利用卡尔曼滤波算法实时计算时变增益，使力探测的估计误差最小。通过一系列实验验证了自适应观测器的设计，并对其性能进行了评估。
This paper presents the design of an adaptive observer that is implemented to enable real-time dynamic force sensing and parameter estimation in an optically trapped probing system. According to the principle of separation of estimation and control, the design of this observer is independent of that of the feedback controller when operating within the linear range of the optical trap. Dynamic force sensing, probe steering/clamping, and Brownian motion control can, therefore, be developed separately and activated simultaneously. The adaptive observer utilizes the measured motion of the trapped probe and input control effort to recursively estimate the probe–sample interaction force in real time, along with the estimation of the probing system’s trapping bandwidth. This capability is very important to achieving accurate dynamic force sensing in a time-varying process, wherein the trapping dynamics is nonstationary due to local variations of the surrounding medium. The adaptive estimator utilizes the Kalman filter algorithm to compute the time-varying gain in real time and minimize the estimation error for force probing. A series of experiments are conducted to validate the design of and assess the performance of the adaptive observer.