The purpose of this paper is to present aspects of an integrated micromachi
ned sensor-neural network transducer development. Micromachined sensors exh
ibit particular problems such as non-linear characteristics, manufacturing
tolerances and the need for complex electronic circuitry. The novel transdu
cer design described here, based on a mathematical model of the micromachin
ed sensor, is aimed at improving in-service performance and facilitating de
sign and manufacture over conventional transducers. The proposed closed-loo
p transducer structure incorporates two modular artificial neural networks:
a compensating neural network, which performs a static mapping, and a feed
back neural network, which both linearizes and demodulates the feedback sig
nal. Simulation results to date show an excellent linearity, wide dynamic r
ange and robustness to shocks for the proposed system. The design was appro
ached from a control engineering perspective due to the closed-loop structu
re of the transducer.