Extended phase space description of human-controlled systems dynamics

TL;DR

This paper introduces an extended phase space model for human-controlled systems, capturing the fuzzy perception and delayed correction behavior of operators, which standard models fail to represent accurately.

Contribution

It proposes a novel extended phase space framework that incorporates operator perception, providing a better representation of human control dynamics in unstable systems.

Findings

Model captures fuzzy perception of actions.

Analytical and numerical analysis confirms model effectiveness.

Extended phase space improves understanding of human control behavior.

Abstract

Humans are often incapable of precisely identifying and implementing the desired control strategy in controlling unstable dynamical systems. That is, the operator of a dynamical system treats the current control effort as acceptable even if it deviates slightly from the desired value, and starts correcting the actions only when the deviation has become evident. We argue that the standard Newtonian approach does not allow to model such behavior. Instead, the physical phase space of a controlled system should be extended with an independent phase variable characterizing the operator motivated actions. The proposed approach is illustrated via a simple non-Newtonian model capturing the operators fuzzy perception of their own actions. The properties of the model are investigated analytically and numerically; the results confirm that the extended phase space may aid in capturing the intricate dynamical properties of human-controlled systems.