Approaches in a sensor model of error correction in dynamic measurements

The article describes three approaches in error correction of dynamic measurements. A sensor model is used in these approaches. The first one is based on the modal control of the dynamic behavior and adapting parameters of a sensor model by direct search. We propose a method of error evaluation in dynamic measurements with a priori information on characteristics of measured signal and noise of the sensor available. The second approach concerns the neural network representation of a sensor. Neural network inverse sensor model and the algorithm for its training by minimizing mean-squared dynamic measurements error criterion are proposed. The third approach is based on the introduction of sliding mode control into the measuring system with modal control of dynamic behavior to achieve the similarity of the sensor model output to the sensor output. (C) 2015 The Authors. Published by Elsevier Ltd.