Auto-calibration and -compensation of a capacitive pressure sensor using multilayer perceptrons

Using multilayer perceptrons (MLPs), a smart model for a capacitive pressur e sensor (CPS) is proposed. When the ambient temperature changes, the nonli near response characteristics of a CPS may vary widely. Under such conditio ns, calibration of the sensor and compensation of the nonlinear sensor char acteristics to obtain correct readout becomes a difficult task. The propose d MLP model can provide automatic nonlinear compensation and calibration of the CPS characteristics. A microcontroller unit (MCU)-based implementation scheme for this model is also considered. Simulation results show that thi s model can estimate the pressure with a maximum full-scale error of +/-1% over a variation of temperature from -50 to 150 degrees C. (C) 2000 Elsevie r Science Ltd. All rights reserved.