Closed Loop Dynamic System Identification of a Manned Classical Configuration Helicopter

Date

2024-1-23

Author

Okcu, Ilgaz Doğa

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Rotary-wing air vehicles present unique advantages over their fixed wing counterparts. Their operation capability in low flight speeds and ability to take-off and land from tight spaces make rotary wing air vehicles indispensable for military and commercial customers around the world. Despite these evident advantages, rotary wing aircraft are complex dynamical systems whose flight dynamics mathematical models are generally difficult to construct and validate. Classical type rotocrafts exhibit sophisticated phenomena that makes the mathematical modelling process troublesome. System identification methods for dynamical system modelling, can provide a solution to this modeling challenges. Both frequency and time domain identification methods have been used extensively either for directly modelling air vehicle motion or for validating the previously constructed physics-based models. Lately the academia and industry focus more on advanced methods that can work under an active feedback regulation. Identification with closed loop data not only makes system identification tests ever more safe than before but also makes identification possible for systems that has redundant controls or systems with control allocation strategies. This thesis work focuses on the system identification of a rotary wing helicopter using closed loop test data. A classical configuration rotorcraft is the system sought to be identified. The applicability and performance of joint input output approach, which can be used to identify both bare airframe and controller, is evaluated with simulation data and flight test data. A linear mathematical model for the bare airframe flight dynamics is identified and verified using closed loop flight test data.

Subject Keywords

Rotorcraft, Helicopter, Flight Mechancis Modeling, Closed Loop System Identification, Frequency Domain System Identification, Joint Input Output Approach

URI

https://hdl.handle.net/11511/108723

Collections

Graduate School of Natural and Applied Sciences, Thesis