Eduardo Morgado Belo

Application of time-delay neural and recurrent neural networks for the identification of a hingeless helicopter blade flapping and torsion motions

System identification consists of the development of techniques for model estimation from experimental data, demanding no previous knowledge of the process. Aeroelastic models are directly influence of the benefits of identification techniques, basically because of the difficulties related to the modelling of the coupled aero- and structural dynamics. In this work a comparative study of the bilinear dynamic identification of a helicopter blade aeroelastic response is carried out using artificial neural networks is presented. Two neural networks architectures are considered in this study. Both are variations of static networks prepared to accomodate the system dynamics. A time delay neural networks (TDNN) for response prediction and a typical recurrent neural networks (RNN) are used for the identification. The neural networks have been trained by Levemberg-Marquardt algorithm. To compare the performance of the neural networks models, generalization tests are produced where the aeroelastic responses of the blade in flapping and torsion motions at its tip due to noisy pitching angle are presented. An analysis in frequency of the signals from simulated and the emulated models are presented. In order to perform a qualitative analysis, return maps with the simulation results generated by the neural networks are presented.

Aeroelastic parameter identification in wind tunnel testing via the extended eigensystem realization algorithm

Aeroelastic instability may occur in aircraft during flight, therefore their prediction represents an important issue within aerospace engineering. Experimental aeroelasticity is still an important field in providing the tools to validate and understand instability phenomena analysis. As many industrial practices require fast evaluations of critical conditions, e.g. flight flutter testing, there exists a natural demand for on-line aeroelastic identification. A number of different methods have been proposed to characterize systems, but recently those showing most success for on-line identification have been based on subspace approaches. The eigensystem realization algorithm (ERA) represents one of the first subspace methods for identification, with the advantage of dealing with multi-input, multi-output data. However, its need for repeated application of the singular value decomposition and a dependence on impulse response functions implies limitations to on-line identification. Generalization studies of the ERA method have led to recursive forms of that algorithm. A recursive form closely related to ERA has been developed in terms of a modified batch estimation approach, and it is denoted as the extended eigensystem realization algorithm (EERA). This work presents results on the application of extended EERA method viewing on-line aeroelastic parameters identification of an experimental apparatus in the wind tunnel. Designed to reproduce the conditions for typical section aeroelastic behavior, an apparatus has been used to show the EERA capabilities in identifying on-line aeroelastic frequency and damping parameters. Results have shown that the approach is robust and adequate for aeroelastic characterization during experimental activities.

A modified contour error controller for a high speed XY table

This article deals with a contour error controller (CEC) applied in a high speed biaxial table. It works simultaneously with the table axes controllers, helping them. In the early stages of the investigation, it was observed that its main problem is imprecision when tracking non-linear contours at high speeds. The objectives of this work are to show that this problem is caused by the lack of exactness of the contour error mathematical model and to propose modifications in it. An additional term is included, resulting in a more accurate value of the contour error, enabling the use of this type of motion controller at higher feedrate. The response results from simulated and experimental tests are compared with those of common PID and non-corrected CEC in order to analyse the effectiveness of this controller over the system. The main conclusions are that the proposed contour error mathematical model is simple, accurate, almost insensible to the feedrate and that a 20:1 reduction of the integral absolute contour error is possible.

Application of H∞ theory to a 6 DOF flight simulator motion base

The purpose of this study is to apply inverse dynamics control for a six degree of freedom flight simulator motion system. Imperfect compensation of the inverse dynamic control is intentionally introduced in order to simplify the implementation of this approach. The control strategy is applied in the outer loop of the inverse dynamic control to counteract the effects of imperfect compensation. The control strategy is designed using H∞ theory. Forward and inverse kinematics and full dynamic model of a six degrees of freedom motion base driven by electromechanical actuators are briefly presented. Describing function, acceleration step response and some maneuvers computed from the washout filter were used to evaluate the performance of the controllers.

Numerical model for the simulation of fixed wings aeroelastic response

A numerical model for the simulation of fixed wings aeroelastic response is presented. The methodology used in the work is to treat the aerodynamics and the structural dynamics separately and then couple them in the equations of motion. The dynamic characterization of the wing structure is done by the finite element method and the equations of motion are written in modal coordinates. The unsteady aerodynamic loads are predicted using the vortex lattice method. The exchange of information between the aerodynamic and structural meshes is done by the surface splines interpolation scheme, and the equations of motion are solved iteratively in the time domain, employing a predictor-corrector method. Numerical simulations are performed for a prototype aircraft wing. The aeroelastic response is represented by time histories of the modal coordinates for different airspeeds, and the flutter occurrence is verified when the time histories diverge (i.e. the amplitudes keep growing). Fast Fourier Transforms of these time histories show the coupling of frequencies typical of the flutter phenomenon.

On the Investigation of State Space Reconstruction of Nonlinear Aeroelastic Response Time Series

Stall-induced aeroelastic motion may present severe non-linear behavior. Mathematical models for predicting such phenomena are still not available for practical applications and they are not enough reliable to capture physical effects. Experimental data can provide suitable information to help the understanding of typical non-linear aeroelastic phenomena. Dynamic systems techniques based on time series analysis can be adequately applied to non-linear aeroelasticity. When experimental data are available, the methods of state space reconstruction have been widely considered. This paper presents the state space reconstruction approach for the characterization of the stall-induced aeroelastic non-linear behavior. A wind tunnel scaled wing model has been tested. The wing model is subjected to different airspeeds and dynamic incidence angle variations. The method of delays is used to identify an embedded attractor in the state space from experimentally acquired aeroelastic response time series. To obtain an estimate of the time delay used in the state space reconstruction from time series, the autocorrelation function analyis is used. For the calculation of the embedding dimension the correlation integral approach is considered. The reconstructed attractors can reveal typical non-linear structures associated, for instance, to chaos or limit cycles.

Design of an experimental flutter mount system

Aeroelastic instabilities may occur in aircraft surfaces, leading then to failure. Flutter is an aeroelastic instability that results in a self-sustained oscillatory behaviour of the structure. A two-degree-of-freedom flutter can occur with coupling of bending and torsion modes. A flexible mount system has been developed for flutter tests in wind tunnels. This apparatus must provide a well-defined 2DOF system on which rigid wings encounter flutter. Simulations and Experimental Tests are performed during the design period. The dimensions of the system are determined by Finite Element analysis and verified with an Aeroelastic Model. The system is modified until first bending and torsion modes become the first and second modes and other modes become higher than these. After this, a Modal Analysis is performed. An identification algorithm, ERA, is used to determine modes shape and frequencies from experimental data. Detailed results are presented for first bending and torsion modes, which are involved in flutter. The flutter mechanism is demonstrated by Frequency Response Functions obtained in several wind tunnel velocities until flutter achievement and by a V-g-f plot obtained from an identification process performed with an extended ERA. Mode coupling, damping behaviour and the self-sustained oscillatory behaviour are verified characterising flutter.

Application of a Pid+fuzzy controller on the motion control system in machine tools

This work deals with an hybrid PID+fuzzy logic controller applied to control the machine tool biaxial table motions. The non-linear model includes backlash and the axis elasticity. Two PID controllers do the primary table control. A third PID+fuzzy controller has a cross coupled structure whose function is to minimise the trajectory contour errors. Once with the three PID controllers tuned, the system is simulated with and without the third controller. The responses results are plotted and compared to analyse the effectiveness of this hybrid controller over the system. They show that the proposed methodology reduces the contour error in a proportion of 70:1.

Model-Based Optimal

In this work the synthesis of a MIMO (Multiple Input Multiple Output) robust optimal model-based H∞ controller is proposed. The whole process takes into account the dynamic equations of a 2-DoF quadrotor Mini Aerial Vehicle (MAV) attached to a steel stand. We consider the gamma-iteration algorithm to find the controller. Our analysis focuses on the control of roll and pitch axes, thereby neglecting the yaw axis control. As our goal is, a priori, to observe the behavior of the H∞ controller while it is controlling the four motors individually in order to stabilize our MAV, this set up provides us with the possibility of a very close overview of the aircraft. Indeed, it allows the easy insertion of disturbances in both axes (individually and simultaneously) and then closely observe the behavior of the platform. Besides, and most important at any laboratory environment, it is an extremely safe mode to run indoor tests, avoiding the quadrotor from causing harm to the crew if any technical problem occurs. The optimal H∞ robust controller presents a high capability of rejecting noises and disturbances. The controller can also suppress the uncertainties of our model. Besides presenting the dynamical model of our MAV, we present the experimental results of both roll and pitch control using the dSpace™ 1103 high performance controller board to embed the designed H∞ MIMO controller.Copyright

Optimal H Infinity Controller Applied to a Stewart Platform

In recent years there has been great interest in studying parallel manipulators, mainly applied in flight simulators, with six degrees of freedom. The interest in parallel kinematic structures is motivated by its high stiffness and excellent positioning capability in relation to serial kinematic structures. This work presents the kinematic and dynamic modeling, design, development and identification of the parameters of motion platform with six degrees of freedom, electrically powered, for studies of flight simulators, is known as a Stewart Platform. It also presents the design of an H infinity controller with output feedback. The actuator model was obtained by a step voltage input to the engines and measuring its displacement by the encoders coupled, in each of the respective axes of the motors. Knowing the relation of motion transmission mechanism between the motor shaft and each actuator is obtained by the displacement rod from the rotation of motor which are measured by the corresponding encoder. The kinematics and dynamics platforms data compose the whole systems models simulations that are applied in the Stewart platform to validate the model and show the effectiveness of control techniques in which was applied to control the position and orientation of the platform were performed. An inertial sensor Xsens MTi-G measurement of the Euler angles of the platform was performed. The result obtained by the controller was satisfactory and illustrate the performance and robustness of the proposed methodology.