论文标题
使用核密度估计的微粒对微粒的2D密度控制
2D Density Control of Micro-Particles using Kernel Density Estimation
论文作者
论文摘要
我们解决了2D粒子密度控制的问题。颗粒浸入介电液中，并通过操纵电场作用。电场由电极阵列控制，并用于将颗粒密度带到所需的图案中。我们使用描述粒子运动的集团，2D，基于电容的非线性模型。使用静电COMSOL模拟估算电容的空间依赖性。我们制定了一个最佳控制问题，其中损失函数是根据粒子密度在最后时间和目标密度之间的误差来定义的。我们使用内核密度估计器（KDE）作为真实粒子密度的代理。 KDE是使用通过改变电极电位更改的粒子位置来计算的。我们通过数值模拟展示了我们的方法，在该模拟中，我们演示了粒子位置和电极电势在将粒子位置从均匀到高斯分布形成时的变化。
We address the problem of 2D particle density control. The particles are immersed in dielectric fluid and acted upon by manipulating an electric field. The electric field is controlled by an array of electrodes and used to bring the particle density to a desired pattern using dielectrophoretic forces. We use a lumped, 2D, capacitive-based, nonlinear model describing the motion of a particle. The spatial dependency of the capacitances is estimated using electrostatic COMSOL simulations. We formulate an optimal control problem, where the loss function is defined in terms of the error between the particle density at some final time and a target density. We use a kernel density estimator (KDE) as a proxy for the true particle density. The KDE is computed using the particle positions that are changed by varying the electrode potentials. We showcase our approach through numerical simulations, where we demonstrate how the particle positions and the electrode potentials vary when shaping the particle positions from a uniform to a Gaussian distribution.
