E-network hierarchical modeling of voluntary and involuntary movements of a human-operator using parametric neural network identification

Abstract

The building of the low-level simulation model of voluntary and involuntary hand movements with the help of the adaptive identification method is considered in the article. It is proposed to use the dynamic neural network as a mathematical apparatus for identifying the parameters of the regulation level of local movements. The presented solution allows carrying out parametric identification of complex objects, in real time as well. We propose the construction of the dynamic model of local voluntary and involuntary hand movements in three-dimensional space. The artificial neural network testing to solve the identification problem was carried out in the Matlab/Simulink simulation environment. The presented work illustrates the possibility of using the E-network apparatus as a mathematical apparatus for modeling heterogeneous interacting processes. The use of neural network identification is necessary for modeling the logical-dynamic level of a human-operator and elements of automated control systems for technological processes. For the construction of a top-level model, it is proposed to use modified Petri nets - E-networks, which allows solving the problem of analytical and simulation modeling of complex parallel processes efficiently. The specific feature of the proposed model is the hierarchy, that allows modeling the levels of object details and processes in the human machine system.