Bell 412 System Identification and Model Fidelity Assessment for Hover and Forward Flight

2021 ◽  
Vol 66 (1) ◽  
pp. 1-13
Author(s):  
Seher-Weiß ◽  
Mark B. Tischler ◽  
Pavle Scepanovic ◽  
Arthur Gubbels
Keyword(s):  
System Identification ◽  
Rigid Body ◽  
Degrees Of Freedom ◽  
Flight Test ◽  
Vertical Axis ◽  
Forward Flight ◽  
Engine Model ◽  
Model Following Control ◽  
Fidelity Assessment ◽  
Six Dof

Frequency domain system identification of higher order models for the Bell 412 helicopter was performed. First, a frequency response database was derived from flight-test data. For hover, a combination of sweep and 2311-multistep maneuvers had to be used to achieve good results. In addition to the classical six-DoF (degrees of freedom) rigid body states, the identified hover model includes dynamic inflow, rotor coning dynamics, and uses a Padé approximation for the influence of engine dynamics, to improve the response in the vertical axis. The forward flight (60 kn) model includes as extension first-order flapping dynamics, mainly to improve the roll and pitch response. Besides the simple Padé approach used in the hover model, two different engine model structures were investigated but they provided no significant improvement compared to the Padé solution when coupled to the rigid-body model. Finally, a method derived from feedforward principles of model following control is shown, to use the identified hover model to analytically derive an "input filter" correction that improves the fidelity of a linearized FLIGHTLAB simulation model.

Vibration of a Spring-Supported Body

1965 ◽  
Vol 7 (2) ◽  
pp. 185-192 ◽  
Author(s):  
P. Grootenhuis ◽  
D. J. Ewins
Keyword(s):  
Rigid Body ◽  
Degrees Of Freedom ◽  
Equations Of Motion ◽  
Vertical Axis ◽  
The Body ◽  
Stiffness Ratio ◽  
Six Degrees Of Freedom ◽  
Centre Of Gravity ◽  
Longitudinal Stiffness ◽  
The Matrix

The equations of motion for a rigid body supported on four springs are derived for the general case of the centre-of-gravity being anywhere within the body and allowing for the sideways as well as the longitudinal stiffnesses of the springs. This constitutes a six-degrees-of-freedom case with three degrees of asymmetry. Coupling between motions in all directions occurs even when the centre-of-gravity is at the geometric centre with the exception then of vertical oscillations and rotation about the vertical axis. Any number of additional springs can be allowed for by adding terms to the expression for the potential energy stored in the springs. Allowance is made in the expression for kinetic energy for the products of inertia which arise with an offset centre-of-gravity. The real case is simulated for purposes of analysis by replacing the rigid body by a rectangular box with a light framework and all the mass concentrated at the eight corners. The matrix solution is changed into dimensionless parameters and the effect of an offset centre-of-gravity upon the eigenvalues and eigenvectors studied. Only the proportions of the box and the stiffness ratio between sideways to longitudinal stiffness of the springs remain as factors. The numerical example given is for proportions of height to width to length of 3/4/5 and for a stiffness ratio of 5. Small amounts of offset of the centre-of-gravity from the geometric centre do not alter the dynamic behaviour of the system much but displacing the total mass towards either a lower or an upper corner has marked effects. Some of the natural frequencies associated with motion in rotation when the system is symmetric become less than the frequencies connected with motion in translation for the centre-of-gravity being close to a corner connected to a spring. A large region free from any natural frequency arises when the centre-of-gravity is moved towards a corner furthest removed from the plane containing the springs. The asymptotic conditions for the position of the centre-of-gravity are also considered.

System Identification Methods for Improving Flutter Flight Test Techniques

2004 ◽  
Author(s):  
David Klyde ◽  
Chuck Harris ◽  
Peter M. Thompson ◽  
Edward N. Bachelder
Keyword(s):  
System Identification ◽  
Flight Test ◽  
Identification Methods

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.

A Hybrid Highly Parallelizable Algorithm for the Dynamics of Rigid Body Chain Systems

1999 ◽  
Author(s):  
Shanzhong Duan ◽  
Kurt S. Anderson
Keyword(s):  
Rigid Body ◽  
Degrees Of Freedom ◽  
High Efficiency ◽  
Equations Of Motion ◽  
Constraint Forces ◽  
Dynamics Of Rigid Body ◽  
A Chain ◽  
Explicit Determination ◽  
Order Algorithm

Abstract The paper presents a new hybrid parallelizable low order algorithm for modeling the dynamic behavior of multi-rigid-body chain systems. The method is based on cutting certain system interbody joints so that largely independent multibody subchain systems are formed. These subchains interact with one another through associated unknown constraint forces f¯c at the cut joints. The increased parallelism is obtainable through cutting the joints and the explicit determination of associated constraint loads combined with a sequential O(n) procedure. In other words, sequential O(n) procedures are performed to form and solve equations of motion within subchains and parallel strategies are used to form and solve constraint equations between subchains in parallel. The algorithm can easily accommodate the available number of processors while maintaining high efficiency. An O[(n+m)Np+m(1+γ)Np+mγlog2Np](0<γ<1) performance will be achieved with Np processors for a chain system with n degrees of freedom and m constraints due to cutting of interbody joints.

Development of six-DOF welding robot with machine vision

2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840079
Author(s):  
Wensheng Huang ◽  
Hongli Xu
Keyword(s):  
Machine Vision ◽  
High Speed ◽  
Degrees Of Freedom ◽  
High Efficiency ◽  
Target Location ◽  
Industrial Robots ◽  
Welding Robot ◽  
Edge Pixel ◽  
Six Dof ◽  
Hardware Processing

The application of machine vision to industrial robots is a hot topic in robot research nowadays. A welding robot with machine vision had been developed, which is convenient and flexible to reach the welding point with six degrees-of-freedom (DOF) manipulator, while the singularity of its movement trail is prevented, and the stability of the mechanism had been fully guaranteed. As the precise industry camera can capture the optical feature of the workpiece to reflect in the camera’s CCD lens, the workpiece is identified and located through a visual pattern recognition algorithm based on gray scale processing, on the gradient direction of edge pixel or on geometric element so that high-speed visual acquisition, image preprocessing, feature extraction and recognition, target location are integrated and hardware processing power is improved. Another task is to plan control strategy of control system, and the upper computer software is programmed in order that multi-axis motion trajectory is optimized and servo control is accomplished. Finally, prototype was developed and validation experiments show that the welding robot has high stability, high efficiency, high precision, even if welding joints are random and workpiece contour is irregular.

scholarly journals Reduced order system identification for UAVs

2015 ◽  
Vol 119 (1218) ◽  
pp. 961-980 ◽  
Author(s):  
P-D. Jameson ◽  
A. K. Cooke
Keyword(s):  
System Identification ◽  
Equations Of Motion ◽  
Real Data ◽  
Flight Test ◽  
Rate Of Change ◽  
Order System ◽  
Parameter Estimates ◽  
Reduced Order Models ◽  
Test Scenario ◽  
Reduced Order

Abstract 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 (Ẇ) 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.

Visual servoing framework using Gaussian process for an aerial parallel manipulator

2018 ◽  
Vol 233 (9) ◽  
pp. 3408-3425
Author(s):  
Sungwook Cho ◽  
David Hyunchul Shim
Keyword(s):  
Gaussian Process ◽  
Parallel Manipulator ◽  
Visual Servoing ◽  
Degrees Of Freedom ◽  
Flight Test ◽  
Control Input ◽  
Body Velocity ◽  
Aerial Vehicle ◽  
Three Degrees Of Freedom ◽  
Traditional Image

This paper proposes a Gaussian process based visual servoing framework for an aerial parallel manipulator. Our aerial parallel manipulator utilizes the on-board eye-in-hand vision sensor system attached on the end-effector of three-degrees-of-freedom parallel manipulator. There are three major advantages: small, light in weight, and linearity with respect to the host vehicle rather than the serial manipulator, but it has a critical drawback that its workspace is too small to perform the mission itself during the hovering. In order to overcome the limited workspace problem and perform the mission more actively, proposed visual servoing framework is proposed to generate relative body velocity commands of the host vehicle by using the interpolated and extrapolated feature path between the initial and desired features to fed into the underactuated aerial parallel manipulator. It can generate not only numerical stable but also feasible control input. Furthermore, it can overcome the weakness of the traditional image-based visual servoing such as singularities, uncertainties, and local minimums during calculating image Jacobian under the large disparity environment between the target and the unmanned aerial vehicle. As a result of the proposed contribution, we show that our contribution is reliable to perform the picking-and-replacement autonomously, and it shows that it can be applied in the large displacement environments throughout the flight test.

Modal Simulation and Testing of a Micro-Manipulator

2004 ◽  
Vol 127 (3) ◽  
pp. 515-519 ◽  
Author(s):  
Yongjun Lai ◽  
Marek Kujath ◽  
Ted Hubbard
Keyword(s):  
Numerical Simulations ◽  
Degrees Of Freedom ◽  
Compliant Mechanism ◽  
Dynamic Properties ◽  
Experimental Results ◽  
Mass Model ◽  
Thermal Actuators ◽  
Micro Manipulator ◽  
Six Dof

A micro-machined manipulator with three kinematic degrees-of-freedom (DOF): x, y, and φ is presented. The manipulator is driven by three thermal actuators. A six DOF discrete spring-mass model of the compliant mechanism is developed which manifests the dynamic properties of the device. Numerical simulations are compared with experimental results.

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