Spinning gasodynamic projectile system identification experiment design

2020 ◽  
Vol 92 (3) ◽  
pp. 452-459 ◽  
Author(s):  
Piotr Lichota ◽  
Mariusz Jacewicz ◽  
Joanna Szulczyk
Keyword(s):  
System Identification ◽  
High Speed ◽  
Content Type ◽  
Stability And Control ◽  
Novel Approach ◽  
Control Derivatives ◽  
Designed Experiment ◽  
Regions Of Stability ◽  
Short Time ◽  
And Control

Purpose The purpose of this paper is to present the methodology that was used to design a system identification experiment of a generic spinning gasodynamic projectile. For this object, because the high-speed spinning motion, it was not possible to excite the aircraft motion along body axes independently. Moreover, it was not possible to apply simultaneous multi-axes excitations because of the short time in which system identification experiments can be performed (multi-step inputs) or because it is not possible to excite the aircraft with a complex input (multi-sine signals) because of the impulse gasodynamic engines (lateral thrusters) usage. Design/methodology/approach A linear projectile model was used to obtain information about identifiability regions of stability and control derivatives. On this basis various sets of lateral thrusters’ launching sequences, imitating continuous multi-step inputs were used to excite the nonlinear projectile model. Subsequently, the nonlinear model for each excitation set was identified from frequency responses, and the results were assessed. For comparison, the same approach was used for the same projectile exited with aerodynamic controls. Findings It was found possible to design launching sequences of lateral thrusters that imitate continuous multi-step input and allow to obtain accurate system identification results in specified frequency range. Practical implications The designed experiment can be used during polygonal shooting to obtain a true projectile aerodynamic model. Originality/value The paper proposes a novel approach to gasodynamic projectiles system identification and can be easily applied for similar cases.

scholarly journals Multi-Axis Inputs for Identification of a Reconfigurable Fixed-Wing UAV

Aerospace ◽  
2020 ◽  
Vol 7 (8) ◽  
pp. 113
Author(s):  
Piotr Lichota
Keyword(s):  
System Identification ◽  
Optimality Criterion ◽  
Likelihood Principle ◽  
Stability And Control ◽  
Input Design ◽  
Relative Standard ◽  
Control Derivatives ◽  
Flight Controls ◽  
Aircraft System ◽  
And Control

Designing a reconfiguration system for an aircraft requires a good mathematical model of the object. An accurate model describing the aircraft dynamics can be obtained from system identification. In this case, special maneuvers for parameter estimation must be designed, as the reconfiguration algorithm may require to use flight controls separately, even if they usually work in pairs. The simultaneous multi-axis multi-step input design for reconfigurable fixed-wing aircraft system identification is presented in this paper. D-optimality criterion and genetic algorithm were used to design the flight controls deflections. The aircraft model was excited with those inputs and its outputs were recorded. These data were used to estimate stability and control derivatives by using the maximum likelihood principle. Visual match between registered and identified outputs as well as relative standard deviations were used to validate the outcomes. The system was also excited with simultaneous multisine inputs and its stability and control derivatives were estimated with the same approach as earlier in order to assess the multi-step design.

Identification of gyroplane lateral/directional stability and control characteristics from flight test

1998 ◽  
Vol 212 (4) ◽  
pp. 271-285 ◽  
Author(s):  
S S Houston
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Flight Test ◽  
Accident Rate ◽  
Stability And Control ◽  
Directional Stability ◽  
Control Derivatives ◽  
Limited Application ◽  
And Control ◽  
Rotary Wing

This paper presents an analysis of test data recorded during flight trials of a gyroplane. This class of rotary-wing aircraft has found limited application in areas other than sport or recreational flying. However, the accident rate is such that a study of the configuration's stability and control characteristics is timely, and in addition substantive data are required for a new airworthiness and design standard that is under development. The paper complements previous work on the longitudinal degrees of freedom and, as a consequence, serves to consolidate the understanding of gyroplane stability and control. The identified derivatives are related to specific aspects of the layout of the gyroplane, and hence the influence of design on the static and dynamic behaviour is quantified. It is concluded that robust estimates of the lateral and directional stability and control derivatives have been identified. This analysis has focused on ‘high-speed’ flight, and the identified derivatives highlight benign and ‘conventional’ characteristics in this part of the flight envelope.

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

Rotorcraft Lateral-Directional Oscillations: The Anatomy of a Nuisance Mode

2021 ◽  
Author(s):  
Dheeraj Agarwal ◽  
Linghai Lu ◽  
Gareth D. Padfield ◽  
Mark D. White ◽  
Neil Cameron
Keyword(s):  
Simulation Model ◽  
Simulation Models ◽  
Flight Test ◽  
Flight Simulation ◽  
Stability And Control ◽  
Systems Research ◽  
Control Derivatives ◽  
Research Aircraft ◽  
Level Of Understanding ◽  
And Control

High-fidelity rotorcraft flight simulation relies on the availability of a quality flight model that further demands a good level of understanding of the complexities arising from aerodynamic couplings and interference effects. One such example is the difficulty in the prediction of the characteristics of the rotorcraft lateral-directional oscillation (LDO) mode in simulation. Achieving an acceptable level of the damping of this mode is a design challenge requiring simulation models with sufficient fidelity that reveal sources of destabilizing effects. This paper is focused on using System Identification to highlight such fidelity issues using Liverpool's FLIGHTLAB Bell 412 simulation model and in-flight LDO measurements from the bare airframe National Research Council's (Canada) Advanced Systems Research Aircraft. The simulation model was renovated to improve the fidelity of the model. The results show a close match between the identified models and flight test for the LDO mode frequency and damping. Comparison of identified stability and control derivatives with those predicted by the simulation model highlight areas of good and poor fidelity.

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