Comparison of approaches for the design of closed-loop micromachined accelerometers

Traditionally, closed-loop actuation has been used for many sensors to increase the bandwidth, dynamic range and to linearise the response of the transducer. In this paper, three control approaches are described with application to a bulk-micromachined accelerometer with capacitive signal pick-off. This device has inherent nonlinear properties in open-loop operation. All three approaches rely on balancing the inertial force acting on the proof mass by electrostatic actuation, the magnitude of which provides a measure of the acceleration signal. The first approach is a simple, analogue, linear control strategy based on proportional, integral and derivative control action. The second approach uses a digital control strategy, based on proportional, integral control action. The third approach employs a novel strategy based upon an artificial neural network. Simulation results suggest that a closed-loop accelerometer with neural network control will have a more stable behaviour and a wider dynamic range than its analogue or digital counterparts.