Modeling and Optimal Force Control of a Nonlinear Electrostatic Microgripper

Abstract

Microgrippers with integrated force sensors are very efficient tools for dexterous manipulation of objects in the microworld (size less than 100 μm). In this paper, we first propose a modeling approach of a nonlinear electrostatic microgripper with integrated force sensor while handling calibrated microglass balls of 80- μm diameter. Limit of the linear operating range of the microgripper is investigated and a nonlinear model is proposed and validated experimentally for large displacements. We then propose the design of an optimal force feedback controller to ensure reliable handling operations with appropriate gripping forces. To overcome the limitation caused by the low signal-to-noise ratio provided by the sensor, a Kalman filter is used to estimate the states of the process from noise measurements. The control law is implemented and validated using real-time experiments for 10 μN gripping force reference with a noise level (peak-to-peak magnitude of the noise) reaching 8 μN in the worst case. The effectiveness of the optimal filter is proven by comparison with external interferometric measurements.