Discrete data-based state feedback model of human operator

Abstract

Modeling human operator's dynamic characteristics has been an active research area for several decades. Previously the author has proposed data-based state feedback model (DBSFM) concept whose structure is based on the controlled system but the parameters can be identified from experimental data by using the frequency domain approach. This paper proposes a discrete version of DBSFM (DDBSFM) whose parameters can be effectively identified in the time domain using the gradient-based optimization algorithms. The method is implemented for identification of the dynamics of a human operator in trolley crane control.