Reduced order system identification for UAVs

Reduced order models representing the dynamic behaviour of symmetric aircraft are well known and can be easily derived from the standard equations of motion. In flight testing, accurate measurements of the dependent variables which describe the linearised reduced order models for a particular flight condition are vital for successful system identification. However, not all the desired measurements such as the rate of change in vertical velocity (W. ) can be accurately measured in practice. In order to determine such variables two possible solutions exist: reconstruction or differentiation. This paper addresses the effect of both methods on the reliability of the parameter estimates. The methods are used in the estimation of the aerodynamic derivatives for the Aerosonde UAV from a recreated flight test scenario in Simulink. Subsequently, the methods are then applied and compared using real data obtained from flight tests of the Cranfield University Jetstream 31 (G-NFLA) research aircraft

Simulated pilot-in-the-loop testing of handling qualities of the flexible wing aircraft

© 2020 The Author(s). Published by VGTU Press. This article aims to indicate the differences between rigid and flexible wing aircraft flying (FQ) and handling (HQ) qualities. The Simulation Framework for Flexible Aircraft was used to provide a generic cockpit environment and a piloted mathematical model of a bare airframe generic high aspect ratio wing aircraft (GA) model. Three highly qualified test pilots participated in the piloted simulation trials campaign and flew the GA model with both rigid and flexible wing configurations. The results showed a negligible difference for the longitudinal HQs between rigid and flexible wing aircraft. However, significant changes were indicated for the lateral/directional HQs of the flexible wing aircraft. A wing ratcheting phenomenon manifested itself during the roll mode tests, the spiral mode exhibited neutral stability and the Dutch roll mode shape changed from a horizontal to a vertical ellipse. The slalom task flight tests, performed to assess the FQs of the aircraft, revealed the degradation of both the longitudinal and lateral/directional FQs

Development of a pilot model suitable for the simulation of large aircraft

Effects of aeroservoelasticity on the manual control of large civil aircraft are investigated through a pilot modelling approach based on the modified optimal control model. A synopsis of modelling techniques is presented, followed by the description of the adopted technique. A simulation environment suitable for investigating pilot-vehicle dynamics in the longitudinal axis has been developed. The derivation of the pilot model was based on limiting the bandwidth. This approach showed that the pilot-vehicle system satisfied the crossover law between 3rad/s to 10rad/s for normal acceleration response. It was found that the pilot model and the low frequency tailplane bending mode introduced a resonant peak in the pilotvehicle frequency response that may be a cause for concern in high gain scenarios. Gust response simulations highlighted the contribution of fuselage bending mode on pilot perceived normal acceleration

Gust rejection properties of VTOL multirotor aircraft

The effect of rotor aerodynamics on the stability and control of multi-rotor aircraft is explored by analysis of a conceptual planar birotor aircraft. In particular, the effect of rotor tilt on the stability and zero-location is investigated. Furthermore, it is shown that designing the vehicle with outwards rotor tilt potentially results in dramatic improvement in the gust rejection properties of the vehicle

Neural network based dynamic model and gust identification system for the Jetstream G-NFLA

Artificial neural networks are an established technique for constructing non-linear models of multi-input-multi-output systems based on sets of observations. In terms of aerospace vehicle modelling, however, these are currently restricted to either unmanned applications or simulations, despite the fact that large amounts of flight data are typically recorded and kept for reasons of safety and maintenance. In this paper, a methodology for constructing practical models of aerospace vehicles based on available flight data recordings from the vehicles’ operational use is proposed and applied on the Jetstream G-NFLA aircraft. This includes a data analysis procedure to assess the suitability of the available flight databases and a neural network based approach for modelling. In this context, a database of recorded landings of the Jetstream G-NFLA, normally kept as part of a routine maintenance procedure, is used to form training datasets for two separate applications. A neural network based longitudinal dynamic model and gust identification system are constructed and tested against real flight data. Results indicate that in both cases, the resulting models’ predictions achieve a level of accuracy that allows them to be used as a basis for practical real-world applications

Regressor time-shifting to identify longitudinal stability and control derivatives of the Jetstream 3102

The Jetstream 31 G-NFLA aircraft is used as a national flying laboratory test vehicle for flight dynamics research and teaching purposes. It has been the subject of much theoretical and experimental modelling and therefore, the need for generating validation data through flight testing is critical. In this paper, the aircraft's short period pitch oscillation mode characteristics are identified using data from sixteen flight tests. An identification procedure based on the least squares method and reduced order state-space model is used and the need for pre-processing regressors due to the effects of sensor location and instrumentation delays is highlighted. It has been shown that time-shifting the regressors based on relative locations of the angle of attack vanes and the inertial measurement unit results in significant reductions in uncertainty bounds of the estimated aeroderivatives and also a model that provides a closer match to flight test data. The estimated models are validated using separate flight test data and the variations in aeroderivatives over a range of airspeeds and centre of gravity positions are also presented

CFD simulation of flow around angle of attack and sideslip angle vanes on a BAe Jetstream 3102 - Part 1

CFD modelling techniques are exploited to investigate the local velocity field around angle of attack and sideslip angle sensors fitted to the nose of a modified BAe Jetstream 3102 small airliner. Analysis of the flow angularity at the vane locations has allowed the vanes response to varying flight conditions to be predicted and errors in the readings to be quantified. Subsequently, a more accurate calibration of the system is applied to the current configuration on the Jetstream, and a better understanding of the position error with respect to the vane locations is obtained. The above aircraft was acquired by Cranfield University in 2003 with subsequent flow angle vane modifications taking place in 2005. The aircraft is currently in operation with the National Flying Laboratory Centre (NFLC) for research and demonstration purposes

A prototype of an autonomous controller for a quadrotor UAV

The paper proposes a complete real-time control algorithm for autonomous collision-free operations of the quadrotor UAV. As opposed to fixed wing vehicles the quadrotor is a small agile vehicle which might be more suitable for the variety of specific applications including search and rescue, surveillance and remote inspection. The developed control system incorporates both trajectory planning and path following. Using a differential flatness property the trajectory planning is posed as a constrained optimization problem in the output space (as opposed to the control space), which simplifies the problem. The trajectory and speed profile are parameterized to reduce the problem to a finite dimensional problem. To optimize the speed profile independently of the trajectory a virtual argument is used as opposed to time. A path following portion of the proposed algorithm uses a standard linear multi-variable control technique. The paper presents the results of simulations to demonstrate the suitability of the proposed control algorithm

Effect of rotor tilt on the gust rejection properties of multirotor aircraft

In order to operate safely in windy and gusty conditions, multirotor VTOL aircraft require gust resilience. This paper shows that their gust rejection properties can be improved by applying a small amount of fixed outward rotor tilt. Standard aerodynamic models of the rotors are incorporated into two dynamic models to assess the gust rejection properties. The first case is a conceptual birotor planar VTOL aircraft. The dependence of the trim and stability on the tilt angle are analyzed. The aircraft is stabilized using a pole-placement approach in order to obtain consistent closed-loop station-keeping performance in still air. The effect of gusts on the resulting response is determined by simulation. The second case study is for a quadrotor with a 10∘" role="presentation" style="max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">10∘ outward rotor tilt. The aerodynamic coefficients are analyzed for trimmed station-keeping over a range of steady wind speeds. An LQR controller is used to apply station-keeping that includes integral action, and the gust responses are again obtained using simulation. The results show that the outward rotor tilt causes the aircraft to pitch down into a lateral gust, providing lateral force that opposes the gust and so significantly improving the gust rejection properties

Jetstream 31 National Flying Laboratory: Lift and Drag Measurement and Modelling

Lift and drag flight test data is presented from the National Flying Laboratory Centre, Jetstream 31 aircraft. The aircraft has been modified as a flying classroom for completing flight test training courses, for engineering degree accreditation. The straight and level flight test data is compared to data from 10% and 17% scale wind tunnel models, a Reynolds Averaged Navier Stokes steady-state computational fluid dynamics model and an empirical model. Estimated standard errors in the flight test data are ±2.4%±2.4% in lift coefficient, ±2.7%±2.7% in drag coefficient. The flight test data also shows the aircraft to have a maximum lift to drag ratio of 10.5 at Mach 0.32, a zero lift drag coefficient of 0.0376 and an induced drag correction factor of 0.0607. When comparing the characteristics from the other models, the best overall comparison with the flight test data, in terms of lift coefficient, was with the empirical model. For the drag comparisons, all the models under predicted levels of drag by up to 43% when compared to the flight test data, with the best overall match between the flight test data and the 10% scale wind tunnel model. These discrepancies were attributed to various factors including zero lift drag Reynolds number effects, omission of a propeller system and surface excrescences on the models, as well as surface finish differences