Teodor Lucian Grigorie

Modeling and Testing of a Morphing Wing in Open-Loop Architecture

This paper presents the modeling and experimental testing of the aerodynamic performance of a morphing wing in open-loop architecture. We show the method used to acquire the pressure data from the external surface of the flexible wing skin, using incorporated Kulite pressure sensors and the instrumentation of the morphing controller. The acquired pressure data are analyzed through fast Fourier transforms to detect the magnitude of the noise in the surface airflow. Subsequently, the data are filtered by means of high-pass filters and processed by calculating the root mean square of the signal to obtain a plot diagram of the noise in the airflow. This signal processing is necessary to remove the inherent noise electronically induced from the Tollmien-Schlichting waves, which are responsible for triggering the transition from laminar to turbulent flow. The flexible skin is required to morph the shape of the airfoil through two actuation points to achieve an optimized airfoil shape based on the theoretical flow conditions similar to those tested in the wind tunnel. Two shape memory alloy actuators with a nonlinear behavior drive the displacement of the two control points of the flexible skin toward the optimized airfoil shape. Each of the shape memory actuators is activated by a power supply unit and controlled using the Simulink/MATLAB® software through a self-tuning fuzzy controller. The methodology and the results obtained during the wind-tunnel test proved that the concept and validity of the system in real time are discussed in this paper. Real-time acquisition and signal processing of pressure data are needed for further development of the closed-loop controller to obtain a fully automatic morphing wing system.

A hybrid fuzzy logic proportional- integral-derivative and conventional on-off controller for morphing wing actuation using shape memory alloy Part 1: Morphing system mechanisms and controller architecture design

The present paper describes the design of a hybrid actuation control concept, a fuzzy logic proportional-integral-derivative plus a conventional on-off controller, for a new morphing mechanism using smart materials as actuators, which were made from shape memory alloys (SMA). The research work described here was developed for the open loop phase of a morphing wing system, whose primary goal was to reduce the wing drag by delaying the transition (from laminar to fully turbulent flows) position toward the wing trailing edge. The designed controller drives the actuation system equipped with SMA actuators to modify the flexible upper wing skin surface. The designed controller was also included, as an internal loop, in the closed loop architecture of the morphing wing system, based on the pressure information received from the flexible skin mounted pressure sensors and on the estimation of the transition location. The controller’s purposes were established following a comprehensive presentation of the morphing wing system architecture and requirements. The strong nonlinearities of the SMA actuators’ characteristics and the system requirements led to the choice of a hybrid controller

A hybrid fuzzy logic proportional- integral-derivative and conventional on-off controller for morphing wing actuation using shape memory alloy Part 2: Controller implementation and validation

The paper presents the numerical and experimental validation of a hybrid actuation control concept – fuzzy logic proportional-integral-derivative (PID) plus conventional on-off – for a new morphing wing mechanism, using smart materials made of shape memory alloy (SMA) as actuators. After a presentation of the hybrid controller architecture that was adopted in the Part 1, this paper focuses on its implementation, simulation and validation. The PID on-off controller was numerically and experimentally implemented using the Matlab/Simulink software. Following preliminary numerical simulations which were conducted to tune the controller, an experimental validation was performed. To implement the controller on the physical model, two programmable switching power supplies (AMREL SPS100-33) and a Quanser Q8 data acquisition card were used. The data acquisition inputs were two signals from linear variable differential transformer potentiometers, indicating the positions of the actuators, and six signals from thermocouples installed on the SMA wires. The acquisition board’s output channels were used to control power supplies in order to obtain the desired skin deflections. The experimental validation utilised an experimental bench test in laboratory conditions in the

On–off and proportional–integral controller for a morphing wing. Part 2: Control validation – numerical simulations and experimental tests

The second part of this article describes the numerical simulation and experimental validations of actuators control system for a morphing wing application, which was developed and designed in the first part of this article. After the description of the finally adopted control architecture, the validation for the non-linear system model is presented. First, the integrated controller is validated numerically with MATLAB/Simulink software, followed by a physical implementation of the control and experimental validation in the wind tunnel. To implement the controller on the physical model, two programmable switching power supplies, AMREL SPS100-33, and Quanser Q8 data acquisition card were used. The inputs of the data acquisition card were the two signals issued by the linear variable differential transformer potentiometers, indicating the positions of the actuators, and the six signals recorded by thermocouples installed on the SMA wires. The acquisition board output channels were used to control the required power supply to obtain the desired skin deflections. The control experimental validation was performed first on a bench test and then in the wind tunnel test. A number of optimized airfoil shapes, used in the design phase, were translated into actuators vertical displacements which were used as input signals for the controller. In the wind tunnel tests, a comparative study was realized around the transition point position for the reference airfoil and for each optimized airfoil.

New adaptive controller method for SMA hysteresis modelling of a morphing wing

A neuro-fuzzy controller method for smart material actuator (SMA) hysteresis modelling is presented, conceived for a morphing wing application. The controller correlates each set of forces and electrical currents that are applied to the smart material actuators with the actuator elongation. The actuator is experimentally tested for four forces, using a variable electrical current. The final controller is obtained through the Matlab/Simulink integration of three independent neuro-fuzzy controllers, designed for the increase and decrease of electrical current, and for null electrical current in the cooling phase of the actuator. This final controller gives a very small error with respect to the experimental values.

DESIGN AND VALIDATION OF A POSITION CONTROLLER IN THE PRICE-PAÏDOUSSIS WIND TUNNEL

Conventional or brushed DC motors are often used for many industrial applications. A large variety of these motors is found in automation, medical, robotics and aeronautical fields. In this paper, the design and experimental validation of a position controller for a morphing wing design application is presented. Matlab/Simulink was used to design the Proportional Integral Derivative controller. For experimental validation, tests were carried out in the Price-Paidoussis subsonic blow down wind tunnel. The upper wing surface was deformed by means of a mechanical system consisting of two eccentric shafts. Both are connected to electrical actuators. Comparisons of two sets of results are provided in this paper. The first set is related to control validation and the second set is related to aerodynamic validation.

Modelling and Simulation Based Matlab/Simulink of a Strap- Down Inertial Navigation System’ Errors due to the Inertial Sensors

Inertial navigation is a dead reckoning positioning method based on the measurement and 10 mathematical processing of the vehicle absolute acceleration and angular speed in order to 11 estimate its attitude, speed and position related to different reference. Due to the specific 12 operation principle, the positioning errors for this method result from the imperfection of the 13 initial conditions knowledge, from the errors due to the numerical calculation in the inertial 14 system, and from the accelerometers and gyros errors. Therefore, the inertial sensors perform‐ 15 ances play a main role in the establishment of the navigation system precision, and should be 16 considered in its design phase frames (Bekir, 2007; Farrell, 2008; Grewal et al., 2013; Grigorie, 17 2007; Salychev, 1998; Titterton and Weston, 2004). 18

How the Airfoil Shape of a Morphing Wing Is Actuated and Controlled in a Smart Way

AbstractThis paper presents a smart way to actuate and control the airfoil shape of a morphing wing in the open-loop architecture. The actuation system uses smart material actuators such as shape memory alloys, disposed in two parallel actuation lines, and its control is performed with a Mamdani-type fuzzy logic proportional derivative (PD) controller. The morphing wing project description, its actuation system structure, and the control design and validation are highlighted in this paper. The results obtained by both numerical simulation and experimental validation (bench tests and wind-tunnel tests) are presented as part of the control design and validation. An analysis of the wind flow characteristics, based on the information provided by the pressure sensors mounted on the flexible skin of the morphing wing in the wind-tunnel tests, is included as a supplementary validation; the transition between laminar and turbulent flows is real-time visualized, and the aerodynamic efficiency of the controlled mor...

The influences of the gyro sensors' errors on the attitude calculus

The paper presents a study about the weight of the different errors of the gyro sensors in the error of attitude angles calculus. For study three types of gyros are selected in order to emphasize the differences in performance currently existing between these categories and the way in which these performances are reflected on to the errors of the attitude angles. To evaluate the errors, the gyros are modeled in Matlab/Simulink using the information from the data sheets and a Savage method to integrate the attitude equation is used. We will further emphasize the influences of noise, bias, gyros accuracy to measure different accelerations and scale factors calibration error.

Controller and aeroelasticity analysis for a morphing wing

The main objectives of this research work are: the design and the wind tunnel testing of a controller for a new morphing mechanism using smart materials made of Shape Memory Alloy (SMA) for the actuators, and the aero-elasticity studies for the morphing wing. The finally obtained configuration for the controller is a combination of a bi-positional controller (on-off) and a PI (proportional-integral) controller, due to the two phases (heating and cooling) of the SMA wires’ interconnection. Firstly, the controller is used for the open loop development step of a morphing wing project, while, further, it is included as an internal loop in the closed loop architecture of the morphing wing system. In the controller design procedure four step are considered: 1) SMA actuators model numerical simulation for different loading force cases; 2) linear system approximation in the heating and cooling phases using Matlab’s System Identification Toolbox and the numerical values obtained in the first step; 3) selecting the controller type and its tuning for each of the two SMA actuators’ phases – heating and cooling; and 4) integration of the two controllers just obtained into a single controller. For the controller validation three actions are taken: 1) numerical simulation; 2) bench testing; and 3) wind tunnel testing. For the third part of this study, aeroelastic studies, the purpose is to determine the flutter conditions in order to be avoided during wind tunnel tests. These studies show that aeroelastic instabilities for the morphing configurations considered appears at Mach number 0.55, which is higher than the wind tunnel Mach number limit speed of 0.3.