A unique patented mechanism, termed ‘RotaFlap’, which can move its wings in a figure-eight shape kinematically similar to insects or hummingbirds, has been investigated through the design, construction, integration and testing of various prototypes. In this paper, the most recent prototype is presented whereby the RotaFlap kinematics is characterised to understand some of its most pertinent parameters. A host of variations have been identified and in this study a subset of these have been tested. A preliminary characterisation of the force production, especially the vertical lift coefficient, has been completed. It is concluded that this mechanism produces vertical lift coefficient values similar to insect and hummingbird flight for similar Reynolds numbers.

This paper presents a methodology that permits accounting for acoustic fatigue effects when sizing safe-life structural skin-stringer panels at the conceptual design stage of aircraft product development. The approach is based upon estimation of the maximum noise radiated from an entry-into-service year 2020 turbofan. Sonic fatigue endurance is assessed for different skin-stringer panels having different values of skin thickness, rib pitch and stringer pitch. Three different materials were considered in this study: aluminium 2024-T3 alloys (Al 2024-T3); carbon fibre-reinforced plastics (CFRP); and, glass reinforced fibre metal laminate (Hybrid Glare-3). The study resulted in CFRP having the most favourable sonic fatigue performance. In order to link economic considerations into technical decision making, the sonic endurance methods were coupled with an industry grade costing analysis tool (SEER-HTM) to examine the impact of safe-life design on the panel cost and weight. The presented methodology has been shown to be sufficiently generic in nature and robust. This will not only assist in identifying acoustic fatigue as a potential critical design scenario, but will also increase throughput during conceptual design sizing and optimisation.

This paper presents the design and implementation of automatic flight controllers for a fixed-wing unmanned air vehicle (UAV) by using a linear-quadratic-Gaussian (LQG) control approach. The LQG design is able to retain the guaranteed closed-loop stability of the linear-quadratic regulator (LQR) while having incomplete state measurement. Instead of feeding back the actual states to form the control law, the estimated states provided by a separately designed optimal observer, i.e. the Kalman filter are used. The automatic flight controllers that include outer-loop controls are constructed based on two independent LQG regulators which govern the longitudinal and lateral dynamics of the UAV respectively. The resulting controllers are structurally simple and thus efficient enough to be easily realized with limited onboard computing resource. In this paper, the design of the LQG controllers is described while the navigation and guidance algorithm based on Global Positioning System (GPS) data is also outlined. In order to validate the performance of the automatic flight control system, a series of flight tests have been conducted. Significant results are presented and discussed in detail. Overall, the flight-test results show that it is highly feasible and effective to apply the computationally efficient LQG controllers on a fixed-wing UAV system with a relatively simple onboard system. On the other hand, a fully automatic 44km cross-sea flight demonstration was successfully conducted using the LQG-based flight controllers. Detailed description regarding the event and some significant flight data are given.

An integrated artificial immune system-based scheme that can operate over extended areas of the flight envelope is proposed in this paper for the detection and identification of a variety of aircraft sensor, actuator, propulsion, and structural failures/damages. A hierarchical multi-self strategy has been developed in which different self configurations are selected for detection and identification of specific abnormal conditions. Data collected using a motion-based flight simulator were used to define the self for a wide area of the flight envelope and to test and validate the scheme. The aircraft model represents a supersonic fighter, including model-following direct adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The proposed detection scheme achieves low false alarm rates and high detection and identification rates for all the categories of failures considered.

Flying under degraded visual environments is a challenging task in helicopter operations. The brownout phenomenon, caused by the rotor downwash on a dusty or sandy underground has caused several critical incidences and accidents in the past. In contrast to an extensive free wake analysis of the rotor vortices, this paper presents a computer graphical solution to simulate brownout conditions. The animation approach builds upon a particle system with a basic aerodynamic assumption of a permanent ground vortex and additional turbulence. The created brownout effect module is a part of the RealTime Image Generator software, used in DLR’s ground based helicopter flight simulator. The object oriented structure of the underlying application programming interface OpenSceneGraph facilitates the development of a generic effect interface for future improvements. An overview of the developed module, the particle system engine and the physical dependencies is provided. To overcome the challenge of capturing the visual realism, a pilot test course with brownout typical tasks is presented. Criteria focussing on the visual and physical parameters are defined to build up a questionnaire. It is used to improve the visual standard and to meet the future pilot’s needs.