Sensitivity analysis of a minimum lateral control speed prediction system

Abstract

Preventing Loss of Control In-flight (LOC-I) in commercial and general aviation is an active research area with numerous proposed solutions. One of these solutions aims to prevent lateral LOC-I, a special type of LOC-I, by presenting a roll-performance based minimum lateral control speed to the pilot in roll-limited situations, such as single-engine failure scenarios in multi-engine aircraft. This minimum lateral control speed is predicted by a system, named the Vc Prediction System (VPS), which continually predicts the minimum lateral control speed Vc at which an aircraft can still obtain a certain roll angle within a certain amount of time. It consists of three components; a linear model, a parameter estimation method and a Vc prediction model. These VPS components were designed for a simulation model of the Piper Seneca. This study analyzes the sensitivity of the VPS design to a change in aircraft dynamics and simulation model complexity by redesigning this system for a high-fidelity simulation model of the Fokker 50. The results show that both aircraft favor a small linear model and the Modified Kalman Method for parameter estimation. The original Vc prediction model however gives higher Vc prediction errors for the Fokker 50 than for the Piper Seneca. By simplifying the original Vc prediction model a stable, smooth and relatively accurate Vc prediction for the Fokker 50 can be obtained.