Development and Validation of a Comprehensive Helicopter Flight Dynamics Code

TL;DR

This paper presents TRAC, a modular, comprehensive helicopter flight dynamics code based on UH-60 data, capable of trim analysis, autonomous flight simulation, and linear model generation, validated against real flight tests.

Contribution

The development of TRAC, a modular and adaptable helicopter simulation software that integrates various components and supports autonomous flight modeling.

Findings

TRAC accurately predicts helicopter dynamic responses.

Trim results validated with US Army UH-60 flight data.

Successfully simulated autonomous ship landing using LQR control.

Abstract

A comprehensive helicopter flight dynamics code is developed based on the UH-60 helicopter and named Texas A\&M University Rotorcraft Analysis Code (TRAC). This is a complete software package, which could perform trim analysis to autonomous flight simulation and the capability to model any helicopter configuration. Different components of the helicopter such as the main rotor, tail rotor, fuselage, vertical tail, and horizontal tail are modeled individually as different modules in the code and integrated to develop a complete UH-60 model. Since the code is developed on a module basis, it can be easily modified to adopt another component or configure a different helicopter. TRAC can predict the dynamic responses of both the articulated rotor blades and the helicopter fuselage and yields the required pilot control inputs to achieve trim condition for different flight regimes such as hover, forward flight, coordinated turn, climb/descent, etc. These trim results are validated with the test data obtained from the UH-60 flight tests conducted by the US Army. Beyond trim analysis, TRAC can also generate linearized models at various flight conditions based on a first-order Taylor series expansion. The extracted linear models show realistic helicopter dynamic behavior and were used to simulate a fully autonomous flight that involves a UH-60 helicopter approaching a ship and landing on the deck by implementing a Linear Quadratic Regulator (LQR) optimal controller.