Iterative Learning Control of an Electrostatic Microbridge Actuator With Polytopic Uncertainty Models

In this brief, a robust control design is presented for an electrostatic microbridge actuator. For this system, a spatially distributed electrostatic force serves as control input. Moreover, a spatially distributed measurement of the bridge displacement is assumed to be available. For an accurate tracking of a reference trajectory-repeated periodically during the operation of the microbridge-an iterative learning control (ILC) approach is proposed based on so-called wave repetitive processes. The design procedure represents an efficient combination of linear matrix inequalities and an appropriate parameter optimization. By explicitly considering polytopic parameter uncertainty, the ILC becomes robust against uncertain parameters such as the squeeze film damping coefficient, the mass density, and the time constant of the electrostatic actuator. Convincing simulation results provide a numerical validation of the proposed ILC scheme as a prestage for a future experimental implementation.