Nonlinear System Identification of Variable-Pitch Propellers Using a Wiener Model

TL;DR

This paper develops a Wiener model-based system identification approach for variable-pitch propeller powertrains, enabling accurate, interpretable, and computationally efficient models for real-time control and digital twin applications.

Contribution

It introduces a Wiener-like model structure that captures the full actuation chain of VPPs, validated with experimental data for static and dynamic responses.

Findings

The model accurately reproduces measured dynamics.

The approach is computationally light and interpretable.

It is suitable for real-time digital twin integration.

Abstract

This work presents the system identification of a variable-pitch propeller (VPP) powertrain, encompassing the full actuation chain from PWM signals to thrust generation, with the aim of developing compact models suitable for real-time digital twinning and control applications. The identification is grounded in experimental data covering both static and dynamic responses of the system. The proposed model takes the form of a Wiener-like architecture, where the PWM inputs are first processed through linear first-order dynamics describing the motor and pitch actuation, and the resulting states are then mapped via a static nonlinear relation to the generated thrust. This structure naturally arises under the assumptions that the electronic actuation operates on a much faster time scale than the mechanical response, and that the contribution of the aerodynamically induced torque is negligible in the tested regime. The resulting parsimonious representation is shown to reproduce the measured dynamics with good accuracy while remaining interpretable and computationally light, thereby providing a practical basis for integration in control-oriented digital twin frameworks.