Hybrid neural network models of transducers

Abstract

A hybrid neural network (NN) approach is proposed and applied to modeling of transducers in the paper. The modeling procedures are also presented in detail. First, the simulated studies on the modeling of single input–single output and multi input–multi output transducers are conducted respectively by use of the developed hybrid NN scheme. Secondly, the hybrid NN modeling approach is utilized to characterize a six-axis force sensor prototype based on the measured data. The results show that the hybrid NN approach can significantly improve modeling precision in comparison with the conventional modeling method. In addition, the method is superior to NN black-box modeling because the former possesses smaller network scale, higher convergence speed, higher model precision and better generalization performance.