Tracking Multiple Diffusing Particles Using Information Optimal Control.

We study the problem of tracking multiple diffusing particles using a laser scanning fluorescence microscope. The goal is to design trajectories for the laser to maximize the information contained in the measured intensity signal about the particles' trajectories. Our approach consists of a two level scheme: in the lower level we use an extremum seeking controller to track a single particle by first seeking it then orbiting around it. In the higher level controller, we decide which particle should be observed at each instant, with the goal of efficiently estimating each particle position while not losing track of any of them. Using simulations, we show that this technique is able to collect photons efficiently and to track multiple particles with low position estimation error.

Analysis of an Extremum Seeking Controller Under Bounded Disturbance.

One of the applications of Extremum Seeking (ES) is to localize the source of a scalar field by using a mobile agent that can measure this field at its current location. While the scientific literature has presented many approaches to this problem, a formal analysis of the behavior of ES controllers for source seeking in the presence of disturbances is still lacking. This paper aims to fill this gap by analyzing a specific version of an ES control algorithm in the presence of source movement and measurement disturbances. We define an approximate version of this controller that captures the main features but allows for a simplified analysis and then formally characterize the convergence properties of this approximation. Through simulations and physical experiments, we compare the theoretically-predicted regions of attraction of the simplified system with the behavior of the full system and show that the simplified version is a good predictor of the behavior of the initial ES controller.