Design and Experimental Validation of a Combined PI and Bi-Positional Laws Controller for Delaying the Transition from Laminar Flow to Turbulent Flow over a Morphing Wing

This chapter presents the design and the validation of the actuators control system for a morphing wing application. Some smart materials, like Shape Memory Alloy (SMA), are used as actuators to modify the upper surface of the wing made of a flexible skin. The finally adopted control law is a combination of a bi-positional law and a PI law. The controller is validated in two experimental ways: bench test and wind tunnel test. All optimized airfoil cases, used in the design phase, are converted into actuators vertical displacements which are used as inputs reference for the controller. In the wind tunnel tests a comparative study is realized around of the transition point position for the reference airfoil and for each optimized airfoil.

[1]  Tyler Lee Hinshaw,et al.  Analysis and Design of a Morphing Wing Tip using Multicellular Flexible Matrix Composite Adaptive Skins , 2009 .

[2]  Ruxandra Botez,et al.  Adaptive neuro-fuzzy inference system-based controllers for smart material actuator modelling , 2009 .

[3]  Teodor Lucian Grigorie,et al.  A Morphing Wing used Shape Memory Alloy Actuators New Control Technique with Bi-positional and PI Laws Optimum Combination - Part 2: Experimental Validation , 2010, ICINCO.

[4]  Sergey Y. Yurish,et al.  Data Acquisition and Signal Processing for Smart Sensors , 2002 .

[5]  Ruxandra Botez,et al.  Closed-loop control validation of a morphing wing using wind tunnel tests , 2010 .

[6]  Ruxandra Botez,et al.  Real Time Morphing Wing Optimization Validation Using Wind-Tunnel Tests , 2010 .

[7]  John L. Junkins,et al.  Design of a morphing wing: Modeling and experiments , 2007 .

[8]  Teodor Lucian Grigorie,et al.  A Morphing Wing used Shape Memory Alloy Actuators New Control Technique with Bi-positional and PI Laws Optimum Combination - Part 1: Design Phase , 2010, ICINCO.

[9]  Michael R. von Spakovsky,et al.  A Study of the Benefits of Using Morphing Wing Technology in Fighter Aircraft Systems , 2007 .

[10]  Sergey Y. Yurish,et al.  Data Acquisition and Signal Processing for Smart Sensors: Kirianaki/Data , 2002 .

[11]  Ruxandra Botez,et al.  Closed-loop control simulations on a morphing wing , 2008 .

[12]  Howard Austerlitz,et al.  Data Acquisition Techniques Using PCs , 1991 .

[13]  Timo Brander,et al.  Shape Control of a FRP Airfoil Structure Using SMA-Actuators and Optical Fiber Sensors , 2008 .

[14]  John Park,et al.  Practical Data Acquisition for Instrumentation and Control Systems , 2003 .

[15]  M. Khalid,et al.  Navier-Stokes investigation of blunt trailing-edge airfoils using O grids , 1993 .

[16]  A. V. Popov,et al.  Controller optimization in real time for a morphing wing in a Wind Tunnel , 2010, Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference.

[17]  Vladimir Brailovski,et al.  Design of Shape Memory Alloy Actuators for Morphing Laminar Wing With Flexible Extrados , 2009 .

[18]  Andrei Vladimir Popov Design of an active controller for delaying the transition from laminar flow to turbulent flow over a morphing wing in wind tunnel , 2010 .

[19]  Vladimir Brailovski,et al.  Non-isothermal finite element modeling of a shape memory alloy actuator using ANSYS , 2006 .

[20]  A. Lyrintzis,et al.  Aerodynamic optimization of a morphing airfoil using energy as an objective , 2007 .