Advances in Flight Control Systems Part 1 doc

ADVANCES IN FLIGHT CONTROL SYSTEMS Edited by Agneta Balint Advances in Flight Control Systems Edited by Agneta Balint Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Ivana Lorkovic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright Oshchepkov Dmitry, 2010. Used under license from Shutterstock.com First published March, 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Advances in Flight Control Systems, Edited by Agneta Balint p. cm. ISBN 978-953-307-218-0 free online editions of InTech Books and Journals can be found at www.intechopen.com Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Preface IX Adaptive Fight Control Actuators and Mechanisms for Missiles, Munitions and Uninhabited Aerial Vehicles (UAVs) 1 Ronald Barrett Adaptive Backstepping Flight Control for Modern Fighter Aircraft 23 L. Sonneveldt, Q.P. Chu and J.A. Mulder Hybrid Adaptive Flight Control with Model Inversion Adaptation 53 Nhan Nguyen Application of Evolutionary Computing in Control Allocation 77 Hammad Ahmad, Trevor Young, Daniel Toal and Edin Omerdic Fault Tolerant Flight Control, a Physical Model Approach 93 Thomas Lombaerts, Ping Chu, Jan Albert (Bob) Mulder and Olaf Stroosma Design of Intelligent Fault-Tolerant Flight Control System for Unmanned Aerial Vehicles 117 Yuta Kobayashi and Masaki Takahashi Active Fault Diagnosis and Major Actuator Failure Accommodation: Application to a UAV 137 François Bateman, Hassan Noura and Mustapha Ouladsine Fault-Tolerance of a Transport Aircraft with Adaptive Control and Optimal Command Allocation 159 Federico Corraro, Gianfranco Morani and Adolfo Sollazzo Contents Contents VI Acceleration-based 3D Flight Control for UAVs: Strategy and Longitudinal Design 173 Iain K. Peddle and Thomas Jones Autonomous Flight Control System for Longitudinal Motion of a Helicopter 197 Atsushi Fujimori Autonomous Flight Control for RC Helicopter Using a Wireless Camera 217 Yue Bao, Syuhei Saito and Yutaro Koya Hierarchical Control Design of a UAV Helicopter 239 Ali Karimoddini, Guowei Cai, Ben M. Chen, Hai Lin and Tong H. Lee Comparison of Flight Control System Design Methods in Landing 261 S.H. Sadati, M.Sabzeh Parvar and M.B. Menhaj Oscillation Susceptibility of an Unmanned Aircraft whose Automatic Flight Control System Fails 275 Balint Maria-Agneta and Balint Stefan Chapter 9 Chapter 10 Chapter 11 Chapter 12 Chapter 13 Chapter 14 Pref ac e Nonlinear problems in fl ight control have stimulated cooperation among engineers and scientists from a range of disciplines. Developments in computer technology al- lowed for numerical solutions of nonlinear control problems, while industrial recogni- tion and applications of nonlinear mathematical models in solving technological prob- lems is increasing. The aim of the book Advances in Flight Control is to bring together reputable research- ers from diff erent countries in order to provide a comprehensive coverage of advanced and modern topics in fl ight control not yet refl ected by other books. This product com- prises 14 contributions submi ed by 38 authors from 11 diff erent countries and ar- eas. It covers most of the currents main streams of fl ight control researches, ranging from adaptive fl ight control mechanism, fault tolerant fl ight control, acceleration based fl ight control, helicopter fl ight control, comparison of fl ight control systems and funda- mentals. According to these themes the 14 contributions are grouped in six categories, corresponding to six parts of the book. The fi rst part of the book is a collection of four chapters (1, 2, 3, 4) dedicated to the adap- tive fl ight control. In Chapter 1 the purpose is to introduce the technical community to some of the adap- tive fl ight control mechanisms and structures which have either lead directly to or ac- tually fl own in various classes of missiles, munitions and unhabited aircra . Although many programs are not open for publication, glimpses of a select fl ow have made it to the public arena at various level. This chapter is centered on airing several supersys- tem-level advances to fl ight-proven missiles, munitions and UAVs. Toward that end, basic models were used to lay out proof-of-concept fl ight hardware which was then fabricated, bench and/or ground tested and incorporated in fl ight vehicles. In the early years the adaptive aircra were o en simply fl own, just to prove the concept worked. More recently, aircra using adaptive fl ight control mechanisms have been fl own off against conventional benchmark aircra so as to demonstrate systematic superiority, thereby proving that fl ight control systems employing adaptive aerostructures result in some combination of lower power consumption, higher bandwidth, reduction in total aircra empty weight, greater fl ight-speed, shock resistance, lower part count, lower cost etc. On normal occasions, adaptive aerostructures have ever been shown to be “enabling” that is, the aircra class would not be able to fl y without them. In Chapter 2 an integrated, though cascaded Lyapunov-based adaptive backstepping approach is taken and used to design a fl ight path controller for nonlinear high-fi delity X Preface F-16 model. Adaptive backstepping allows assuming that the aerodynamic force and moment models may not be known exactly, and even that they may change in fl ight due to causes as structural damage and control actuator failness. To simplify the math- ematical approximation partition the fl ight envelope into multiple connecting operat- ing regions, called hyperboxes, is proposed. In each hyperbox a locally valid linear- in-parameters nonlinear model is defi ned. The coeffi cients of these local models can be estimated using the update laws of the adaptive backstepping control laws. The num- ber and size of the hyperboxes should be based on a priori information on the physical properties of the vehicle on hand, and may be defi ned in terms of state variables as Mach number, angle of a ack and engine thrust. To interpolate between the local mod- els to ensure smooth model transitions B-spline neural networks are used. Numerical simulations of various maneuvers with aerodynamic uncertainties in the model and actuator failures are presented. The maneuvers are performed at several fl ight condi- tions to demonstrate that the control laws are valid for the entire fl ight envelope. In Chapter 3 a hybrid adaptive fl ight control method as another possibility to reduce the eff ect of high-gain control, is investigated. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion fl ight control architecture. The blending of both direct and indirect adaptive control is sometimes known as composite adaptation. The indirect adaptive control is used to update the model inversion con- troller by two parameter estimation techniques: 1) an indirect adaptive law based on the Lyapunov theory and 2) a recursive least-squares indirect adaptive law. The model inversion controller generates a command signal using estimates of the unknown plant dynamics to reduce the model inversion error. This directly leads to a reduced tracking error. Because the direct adaptive control only needs to adapt to a residual uncertainity, its adaptive gain can be reduced in order to improve stability robustness. Simulations of the hybrid adaptive control for a damaged generic transport aircra and a pilot-in- loop fl ight simulator study show that the proposed method is quite eff ective in provid- ing improved command tracking performance for a fl ight control system. In Chapter 4 the purpose is to design a compensator using an evolutionary computing technique (i.e. generic algorithms) to compensate the interaction between control al- location and actuator dynamics. The interaction of fi rst order actuator dynamics and control allocation and the struc- ture of the compensator is established for fi rst order and second order actuator dynam- ics. The tuning of the compensator parameters using generic algorithm is described. Simulation and results for tuned compensator are shown for a range of fi rst and second order actuator dynamics. At the end conclusions are established. The second part of this book consists on four chapters (5, 6, 7, 8) dedicated to the fault tolerant fl ight control. In Chapter 5 a physical modular approach, where focus is placed on the use of math- ematical representation based on fl ight dynamics., is used. All variables and quanti- ties which appear in the model have a physical meaning and thus are interpretable in this approach, and on avoids so called black and grey box models, where the con- tent has no clear physical meaning. Besides the fact that this is a more transparent approach, allowing the designers and engineers to interpret data of each step, it is assumed that these physical models will facilitate certifi cation for eventual future real [...]... Uninhabited Aerial Vehicles (UAVs) 5 Conventionally Attached Piezoelectric Actuators: ⎧N⎫ ⎨ ⎬ ⎩ M ⎭CAP ⎡ A 11 ⎢ ⎢ A12 ⎢ 0 =⎢ ⎢ B 11 ⎢ B12 ⎢ ⎣ 0 A12 A 11 0 B12 B 11 0 0 0 2A 66 0 0 2B 66 B 11 B12 0 D 11 D12 0 B12 B 11 0 D12 D 11 0 ⎧ Λ⎫ ⎧(A 11 + A12 )Λ⎫ 0 ⎤ ⎪ ⎥ ⎪ ⎪ ⎪ 0 ⎥ ⎪ Λ⎪ ⎪(A 11 + A12 )Λ⎪ ⎪ ⎪ 0⎪ ⎪ 2B 66 ⎥ 0 ⎨ ⎬=⎨ ⎬ ⎥ 0 ⎥ ⎪ 0 ⎪ ⎪(B 11 + B12 )Λ⎪ ⎪ 0 ⎪ ⎪(B + B )Λ⎪ 0 ⎥ ⎪ ⎪ ⎪ 11 12 ⎪ ⎥ 2D 66 ⎦CAP ⎩ 0 ⎭ ⎩ 0 ⎭CAP (1) ... 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 Advances in Flight Control Systems Project p=piezoelectric, s=shape memory alloy c=component testing only f =flight tested v=entire vehicle configuration tested with adaptive device Bending-Twist Coupled Aeroelastic PZT Plate (19 85-87) Adaptive Flap (19 87-89) Twist-Active Subsonic DAP Missile Wing... ⎭CAP (1) B12 B 22 B 26 D12 D 22 D 26 ⎧ Λ⎫ ⎧ (A 11 + A12 )Λ ⎫ 2B16 ⎤ ⎪ ⎥ ⎪ ⎪ ⎪ 2B 26 ⎥ ⎪ Λ⎪ ⎪(A 22 + A12 )Λ⎪ ⎪ 0 ⎪ ⎪(A16 + A 26 )Λ⎪ 2B 66 ⎥ ⎨ ⎬=⎨ ⎬ ⎥ 2D16 ⎥ ⎪ 0 ⎪ ⎪ (B 11 + B12 )Λ ⎪ ⎪ 0 ⎪ ⎪(B 22 + B12 )Λ⎪ 2D 26 ⎥ ⎪ ⎪ ⎪ ⎪ ⎥ 2D 66 ⎦DAP ⎩ 0 ⎭ ⎩(B16 + B 26 )Λ⎭ DAP (2) Directionally Attached Piezoelectric Actuators: ⎧N⎫ ⎨ ⎬ ⎩ M ⎭ DAP ⎡ A 11 ⎢ ⎢A12 ⎢A16 =⎢ ⎢ B 11 ⎢B12 ⎢ ⎣B16 A12 A 22 A 26 B12 B 22 B 26 2A16 2A 26... 66 2B16 2B 26 2B 66 B 11 B12 B16 D 11 D12 D16 In the late 19 80's it was not readily apparent which among the many approaches to adaptive flight control would actually work in a real flight environment Several important papers relating aeroelastic tailoring, geometric sweep and aeroelastic coupling were authored, comparing CAP and DAP elements.9 -11 These papers showed that with aeroelastic coupling, small... Missile Wing (19 89-90) Twist-Active DAP Rotor (19 90- 91) Aeroservoelastic Twist-Active Wing (19 90-92) Twist-Active Supersonic DAP Wing (19 91- 92) Constrained Spar Torque-Plate Missile Fin (19 91- 92) Free-Spar DAP Torque-Plate Fin (19 92-93) Pitch-Active DAP Torque-Plate Rotor (19 92-93) Subsonic Twist-Active DAP Wing (19 93-94) Subsonic Twist-Active SMA Wing (19 93-94) Subsonic Camber-Active DAP Wing (19 93-94)... could be in any direction This imposes nonlinearity, which can be modelled by a transformation To handle this semi-linearized model, the linear and nonlinear parts are separated, and then the linear part is controlled by the inner-loop and the nonlinear part by the outer-loop The fifth part of this book consists on one chapter (13 ) dedicated to the comparison of flight control systems In chapter 13 an overview... Flexspar: The first flight enabling adaptive system In an effort to dramatically increase control surface deflections of low aspect ratio fins and in keeping with principles i and ii above, a new flight control device was invented and reduced to practice This flight control system would be shown to be one of the most useful and widely used in aircraft employing adaptive materials for flight control Figure... applications, since monitoring of data is more meaningfull Adaptive nonlinear dynamic inversion is selected as the preferred adaptive control method in this modular or indirect approach The advantage of dynamic inversion is the absence of any need for gain scheduling and an input-output decoupling of all control channels Adaptation of the controller is achieved by providing up-to-date aerodynamic model information... (19 93-94) Subsonic Camber-Active SMA Wing (19 93-94) Supersonic Twist-Active DAP Wing (19 93-94) Supersonic Twist-Active SMA Wing (19 93-94) Supersonic Camber-Active DAP Wing (19 93-94) Supersonic Camber-Active SMA Wing (19 93-94) UAV with Flexspar Stabilator (Mothra 19 93-94) Flexspar TOW-2B Wing (19 93-94) Solid State Adaptive Rotor (SSAR) (19 94-95) Aeroservoelastic Flexspar Fin (19 94-95) UAV with Solid State Adaptive... a point mass with a steerable acceleration vector from a 3D guidance perspective This abstraction which is now valid over the entire flight envelope is the key to significantly reducing the complexity involved in solving the manoeuvre flight control problem The fourth part of this book consists on three chapters (10 , 11 , 12 ) dedicated to helicopter flight control XI XII Preface In chapter 10 a flight control . DAP = A 11 A 12 2A 16 B 11 B 12 2B 16 A 12 A 22 2A 26 B 12 B 22 2B 26 A 16 A 26 2A 66 B 16 B 26 2B 66 B 11 B 12 2B 16 D 11 D 12 2D 16 B 12 B 22 2B 26 D 12 D 22 2D 26 B 16 B 26 2B 66 D 16 D 26 2D 66 ⎡ . Actuators: N M ⎧ ⎨ ⎩ ⎫ ⎬ ⎭ CAP = A 11 A 12 0 B 11 B 12 0 A 12 A 11 0 B 12 B 11 0 002A 66 002B 66 B 11 B 12 0 D 11 D 12 0 B 12 B 11 0 D 12 D 11 0 002B 66 002D 66 ⎡ ⎣ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎢ ⎤. ADVANCES IN FLIGHT CONTROL SYSTEMS Edited by Agneta Balint Advances in Flight Control Systems Edited by Agneta Balint Published by InTech Janeza Trdine 9, 510 00 Rijeka, Croatia Copyright