Multi-step strategy for rotorcraft model identification from flight data

The availability of suitable methods for system identification from flight data of rotorcraft models is a key factor to enhance the competitiveness of the rotorcraft industry in the development process of new vehicles. Indeed, reliable simulation models provided by the identification techniques can be used for the design and validation of the vehicle flight control system. It allows minimizing the number of in flight experimental tests and consequently reducing costs and risks related to flight testing. Identification methodologies generally fall into two categories: frequency-domain and time-domain. Each approach has inherent strengths and weaknesses. Much of the published works on rotorcraft identification deals primarily with frequency-domain methods, which work well at mid and high frequencies associated with the dynamics of the vehicle control inputs and the aero-elastic behaviour of the blades. On the other hand, time-domain methods, which are well assessed for the identification of fixed wing aircraft, provide accurate models at the low frequency scale that is related to the vehicle flight mechanics. In this paper a hybrid time-frequency identification approach is described. The identification process was carried out in the framework of a multi-step strategy and a specific methodology was selected to comply with each step objective. The hybrid time-frequency approach allowed exploiting the advantage of both time and frequency methods, maximizing the information content extracted from the flight data and obtaining an identified model applicable in the whole frequency range of interest. Furthermore the multi-step strategy decomposed the complex starting problem in simplified sub-problems, which are easier to be solved. The proposed methodology was applied to simulated data of the UH60 Black Hawk, generated using the FLIGHTLAB multi-body simulation environment. Preliminary results showed the effectiveness of the proposed identification strategy in terms of convergence and capability of extracting from flight data relevant information on the vehicle dynamic behaviour. Future works will be focused on the refinement of the structure of the rotorcraft model used for identification purpose and on the application of the proposed methodology to set of data gathered during actual rotorcraft flight tests

Development of a Male Turbo-Prop Unmanned Aerial Vehiche for Civil Application

Unmanned Aerial Vehicles (UAV) increasingly are seen as the next step in aircraft evolution with the potential to replace manned aircraft over a broad range of civilian roles. Industry, who recognise the cost effectiveness of UAV, is keen to grasp this potential and the technology is rapidly developing with numerous projects currently in operation of development throughout Europe and worldwide. In response to this needs University of Naples has developed a MALE configuration TurboProp engined using innovative structural and aerodynamic solutions. Regarding the structural aspect the extensive use of composite materials led to the definition of a weight efficient vehicle capable to carry on up to 500 kg of payloads covering a wide range of medium altitude missions. With reference to aerodynamic solution, an Eppler modified profile, numerically optimized, has been adopted for its efficiency that has granted long endurance and, coupled with the power provided by the chosen engine (PT6A – 67 B), high performance. The aeroelastic assessment has revealed that no critical phenomena occur in the flight envelope. Once defined the aerodynamic and structural aspects, an analysis of reliability and safety has been performed aimed to evaluate MTBL (Mean Time Between Loss) and MTBCF (Mean Time Between Critical Failure) features

Autonomous Take Off System: Development and Experimental Validation

This paper describes the design and validation process of an innovative Autonomous Take Off system, developed by the Italian Aerospace Research Center (CIRA) in the framework of the Italian national funded project TECVOL (Technologies for the Autonomous Flight). The autonomous take-off module is part of the autonomous Guidance, Navigation and Control prototype worked out by CIRA in the same project, where significant research effort has been devoted to achievement of high automation during all the flight phases, from take off to landing. The developed automated system allows take off, navigation through three-dimensional waypoints and landing of an aircraft without human intervention, also in presence of environmental disturbances and/or subsystem failures. In aerospace research and development activities not only functional requirements play an important role in the project, also process requirements and system engineering methods are fundamental for project success. In particular, the autonomous take off system development and validation process has been designed in order to be highly reliable but with a substantial reduction of needed time and costs. In the paper the process of design and validation applied to the proposed system development is examined in details, while providing also a description of the automatic take off system

Hybrid Approach for Rotorcraft Identification from Flight Data

The availability of suitable methods for rotorcraft model identification from flight data is a key factor to enhance the competitiveness of the rotorcraft industry in the development process of new vehicles. Indeed, reliable simulation models provided by the identification techniques can be used for the design and validation of the vehicle flight control system. It allows minimizing the number of in flight experimental tests and consequently reducing costs and risks related to flight testing. In this paper the complex problem of rotorcraft model identification is decomposed in simpler sub-problems and solved by means of multi-step hybrid time-frequency approach. The hybrid time-frequency approach allows exploiting the advantage of both time and frequency domains methods, maximizing the information content extracted from the flight data and obtaining an identified model applicable in the whole frequency range of interest. The proposed methodology was applied to simulated data of the UH60 Black Hawk generated using the FLIGHTLAB simulation environment both in hover and forward flight conditions. Preliminary results show the effectiveness of the proposed identification strategy in terms of convergence and capability of extracting from flight data relevant information on the vehicle dynamic behavior