28TH INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES
|
|
- Moses Evans
- 6 years ago
- Views:
Transcription
1 8 TH INTERNATIONAL CONGRESS OF O THE AERONAUTICAL SCIENCES AUTOPILOT DESIGN FOR AN AGILE MISSILE USING L ADAPTIVE BACKSTEPPING CONTROL Chang-Hun Lee*, Min-Jea Tahk* **, and Byung-Eul Jun*** *KAIST, **KAIST, ***Agency for Defensee Development ac.kr;mjtahk@fdcl.kat.ac.kr;mountrees@gmail.com Keywords: Agile msile, L adaptive control, backstepping control, msile autopilot Abstract Th paper deals with an agile msile pitch autopilot design using L adaptive backstepping control methodology. The flight phases of the agile msile systems can be classified into three phases; launch, agile turn, and end-game. Th paper focused on the agile turn phase, which a fast 8 degree turn to engage a rear- under the presence of the aerodynamic uncertainties es. To attain a fast response, the hemphere located target after launch l phase, angle-of-atta ack chosen to be the control variable. Since L adaptive control can guarantee robustness against uncertainty andd a fast response during the transient phase, itt suitable for a control methodology of the agile turn. The performances of the t proposed controller are investigated and demonstrated through numerical simulations. Introduction During the course of years, the control systems of the agile msiles have been extensively studied by many researchers [-6]. In general, the flight phases of the agile msile systems const of three different phases; launch, agile turn, and end-game []. Among three t different phases, the controller design of the agile turn phase introduces many challenging problems. The agile turn defined to be a fast 8 degree turn maneuver to engage a rear-hemphere located target after launch phase. The reason, why handling of the agile turn difficult, the presence of a large variation of the aerodynamic uncertainties induced by a high angle-of-atta ack maneuver. Therefore, a robust control approach needed inn order to compensate such the aerodynamic uncertainties. One of solution that the controller predicts the model m uncertainties and adapts the model parameters, whichh called the adaptive control methodology [-6]. Although th approach can have robustness under the presences off the model uncertainties, the transient performance poor due to the adaptation time nullifying the model error. Hence, the conventional adaptive control methodology may not be suitable for a control method of thee agile msile systemss that require a fast transient performance. As a remedy, in th paper, we propose an agile msile controller based on backsteppin ng control methodology with L adaptive scheme. From previous works [8-9], it has been shown that L adaptive scheme can provide the robustness and a a fast t response during the transient phase. In addition, since the normal acceleration control c of the msile systems s faces with the nonminimum phase phenomena, we choose the angle-of-attack for the control variable. Additionally, according to t references [8-9], the commandingg of angle-of-attack more desirable than thatt of normal acceleration for achievingg a fast response. Finally, the performance of the proposed controller demonstrated by numerical simulations. Th paper consts of five sections. In section, a nonlinear msile modell explained. The proposedd controller providedd in section. The simulation results are shown in section 4. In section, we conclude th study. Nonlinear Msile Model
2 CHANG-HUN LEE, MIN-JEA TAHK, AND BYUNG-EUL JUN In th study, a nonlinear model of the longitudinal msile motion considered as shown in Fig.. and the notations of Δ represents the model error caused by the aerodynamic uncertainties in the high angle-of-attack regime. L Adaptive Backstepping Controller. Model Derivation Fig. The msile geometry Under the assumptions that the msile body rigid and the gravity force compensated, the equations of motion are determined as follows: QS α = ( C N ( α, ) (, ) ) M + C N α δ M δ + q () mv QSl lq q = Cm ( α, M) + C (, ) m M + C q m α M δ δ () Iyy V where α, q, and δ denote the angle-of-attack, the pitch rate, and the fin deflection angle, respectively. The notations of m, I yy, S, and l indicate the mass, the pitching moment of inertia, the reference area, and the reference length, respectively. The velocity, the dynamic pressure, and Mach number are denoted by V, Q, and M, respectively. The aerodynamic coefficients in Eqs. () and () are given by the function of the angle-of-attack and Mach number. There coefficients are computed form the predetermined data tables, which are obtained by the wind tunnel test. In the high angle-of-attack regime, the msile undergoes the aerodynamic uncertainties. From Eq. (), we have the following equations under the presence of the aerodynamic uncertainties. x = f+δ f+ x + ( g+δg) u () x = f +Δ f + ( g +Δg) u (4) where, x = α, x = q, u = δ () f = KC, f = K C + C ( ql/v) (6) α N q m m q g = KC α N δ, g = KC q m δ (7) K QS / mv K = QSl / I (8) = α, q ( yy) In order to apply the backstepping control methodology, a strict feedback form of system equation required. In the msile systems, the magnitude of control force ( g+δ g) u in the right hand side of Eq. () can be generally negligible due to ( g +Δ g) u ( g+δg) u. Therefore, Eqs. () and (4) can be rewritten in a strict feedback form as follows: x = f+ x +Δ (9) x = f + gωu+δ () where Δ = Δ f+ ( g+δ g) u, Δ =Δ f () ω = +Δ g / g () In Eqs. (9) and (), Δ and Δ can be regarded as the total model errors due to the aerodynamic uncertainties and the neglecting term of ( g+δ g) u. By introducing the linear parameterization [9], the model uncertainties can be parameterized as follows: Δ = θ x + σ () Δ = θ x + σ (4) Substituting Eqs. () and (4) into Eqs. (9) and () yields the following equation. x = f+ x + θ x + σ () x = f + g ωu+ θ x + σ (6) where θ, θ, and ω are unknown parameters. The adaptation schemes of these variables will be dcussed in section... State Predictor Design In th section, we dcuss the state predictor design. First, let us define the desired error dynamics of state predictor as follows: x = Kx, x = Kx (7)
3 AUTOPILOT DESIGN FOR AN AGILE MISSILE USING L ADAPTIVE BACKSTEPPING CONTROL where x xˆ x represents the prediction error. ˆx and x are the predicted state and the true state, respectively. The gains of K and K decide the convergence speed of the prediction error. Substituting Eqs. () and (6) into Eq. (7) provides the following state predictor. ˆx = Kx + f+ x + θ x + σ (8) ˆx = Kx + f + gωu+ θ x + σ (9) Since θ, θ, and ω are unknown parameters in Eqs. (8) and (9), they should be estimated as follows: xˆ = Kx ˆ ˆ + f+ x + θ x + σ () x ˆ = K x + f + g ωu+ ˆ θ x + ˆ σ (). Adaptive Law Design Th section derives the adaptive law based on Lyapunov function. By using Eqs. (), (6), (), and (), the prediction error dynamics in Eq. (7) can be rewritten as follows: x = xˆ x = Kx+ θ x + σ () x = xˆ x = Kx + g ωu+ θ x + σ () where θ ˆ = θ θ, θ = ˆ θ θ, σ = ˆ σ σ σ ˆ = σ σ, and ω = ˆ ω ω. Let us consider the following Lyapunov function. V = ( ) x + x + ω + θ + θ + σ + Γ σ (4) Taking the time-derivative of V yields: V = Kx Kx + C+ C+ C+ C4+ C() where C = θx x + ( / Γ) θθ (6) C = θx x + ( / Γ) θθ (7) C = σx+ ( / Γ) σσ (8) C = σ x + / Γ σσ (9) 4 ωxgu / C = + Γ ωω () In order to guarantee the asymptotic stability of the prediction error, we enforce C through C to be zero. Then, the time-derivative of V always negative definite as follows: V K x K x () = < From the condition of nullifying C to C, the following adaptive law can be obtained. ˆ θ = θ = Γx x, ˆ θ = θ = Γ x x () ˆ σ = σ = Γx, ˆ σ = σ = Γx () ˆ ω = ω = Γxgu (4) where Γ represents the adaptation gain. In the conventional adaptive control, the increase of the adaptation gain introduces the chattering effect. However, L adaptive control relieves th limitation by introducing a low pass filter rejecting the high frequency signal induced by high adaptation gain..4 Control Law Design For convenience, let new residuals be defined as follows: z = x xd, z = x xd () Then, the residual dynamics can be expressed as: z = f+ x ˆ ˆ + θ x + σ x (6) d z = f ˆ ˆ ˆ + gωu+ θ x + σ x d (7) where x d and x d are the desired state values. We consider the following Lyapunov function to derive the outer loop control law in the backstepping methodology. V = z (8) The time-derivative of V can be determined by using Eq. (6) as follows: V = z( f+ x ˆ ˆ + θ x + σ x ) (9) d In order to enforce V <, the desired value of x chosen as: ( ˆ θ ˆ σ ) xd = Kz f+ x + + x d (4) In order to design the inner loop control law, the following Lyapunov function introduced. V = z + z (4) After taking time-derivative of V and substituting Eqs. (6) and (7) into V gives the following result.
4 CHANG-HUN LEE, MIN-JEA TAHK, AND BYUNG-EUL JUN V = z Kz+ z (4) + z( f ˆ ˆ ˆ + gωu+ θ x + σ x d ) From Eq. (4), we can obtain the inner loop control law that satfies V < as follows: u = ( Kz z ˆ ˆ f θ x σ + x d )(4) g ˆ ω In Eqs. (4) and (4), K and K represents the control gain, which are identical values of the state predictor. If the adaptation gains increase, the adaptation parameters of ˆ θ, ˆ θ, ˆ σ, ˆ σ, and ˆω contain the high frequency signals which cause the chattering effect during the transient phase. In L adaptive control methodology, low pass filters are introduced in the inner loop and the outer loop control law in order to cutoff the high frequency signal. Therefore, the uses of the high adaptation gains are possible in th method. By introducing a low pass filter, the outer loop control law can be obtained as follows: x ˆ d = Kz η C + x d (44) where ˆ η ˆ C C s η in the frequency domain. A second-order low pass filter C ( s ) and the variable ˆ η are defined as follows: C ω ( s) = s + ζ ωs+ ω (4) ˆ η = f + ˆ θ x + ˆ σ (46) where ω and ζ represent the design parameters of low pass filter. In a similar way, the inner loop control law modified by using a first-order low pass filter. uc ( s) = C ( s) u (47) where g ˆ ωk C ( s) = (48) s + g ˆ ωk u= ( Kz z ˆ ˆ f θx σ+ x d ) (49) g ˆ ω where k represents the design parameter of a first-order low pass filter. Fig. shows the overall configuration of the proposed controller. Fig. The configuration of controller 4 Simulation Results In order to demonstrate the performance of the proposed controller, numbers of simulations are carried out. In these simulations, a second-order actuator model with ω act = rad/ s, ζ act =.7, and δ = 4 deg/ s considered. The controller parameters are chosen as K = K = and Γ =. The low pass filter parameters are defined as ω = rad/ s, ζ =.7, and k =. 4. Case : Step Input Command In th simulation, the proposed controller tested with a step input command. Figs. and 4 show the step input response of angle-of-attack and the fin deflection angle in the nominal case. Figs. and 6 provide the simulation results under the presence of % model uncertainties during the flight. The results indicate that the proposed controller can provide a good tracking performance even in the presence of the model uncertainties. 4. Case : Agile Turn Scenario In th simulation, the applicability of the proposed method determined under an agile turn scenario (i.e., 8 degree heading reversal turn). The angle-of-attack command [] which obtained from the trajectory optimization to achieve the terminal velocity after agile turn used. Figs. 7 and 8 give the angle-of-attack response and the fin deflection angle during the agile turn. The results show that the proposed controller can maintain a sound tracking performance. Therefore, the proposed method can be applied to the challenging sues of the agile msile systems. 4
5 AUTOPILOT DESIGN FOR AN AGILE MISSILE USING L ADAPTIVE BACKSTEPPING CONTROL Response Command Angle-of-Attack 4 Angle-of-Attack Response Command α ( ) - α ( ) Fig. Angle-of-attack (nominal) Fig. 7 Angle-of-attack (agile turn) Control Input Control Input - -4 δ ( ) - δ ( ) Fig. 4 Fin deflection angle (nominal) Fig. 8 Fin deflection angle (agile turn) Angle-of-Attack Conclusion α ( ) - - Response Command Fig. Angle-of-attack (% uncertainty) Control Input In th paper, we propose the agile msile autopilot based on backstepping control in conjunction with L adaptive scheme. In the proposed method, the commanding of angle-ofattack was considered for accomplhing a fast turn of the msile s heading angle. The simulation results indicated that the proposed controller can provide the sound performance under the presence of the model uncertainties in high angle-of-attack regime. It can also be applicable to the agile turn maneuver. δ ( ) - - Acknowledgments Th research was supported by Agency for Defense Development under the contract UDCD Fig. 6 Fin deflection angle(% uncertainty) References
6 CHANG-HUN LEE, MIN-JEA TAHK, AND BYUNG-EUL JUN [] Kevin A. We and David J. Broy. Agile Msile Dynamics and Control. Journal of Guidance, Control, and Dynamics, Vol., No., pp , 998. [] A. Thukral and M. Innocenti. A Sliding Mode Msile Pitch Autopilot Synthes for High Angle of Attack Maneuvering. IEEE Transactions on Control System Technology, Vol. 6, No., pp. 9-7, 998. [] D. J. Leith, A. Tsourdos, B. A. White and W. E. Leithead. Application of Velocity-based Gainscheduling to Lateral Auto-pilot Design for an Agile Msile. Control Engineering Practice, Vol. 9, pp. 79-9,. [4] H. Buschek. Full Envelope Msile Autopilot Design Using Gain Scheduled Robust Control. Journal of Guidance, Control, and Dynamics, Vol., No., pp. -, 999. [] M. B. McFarland and A. J. Cale. Neural Networks and Adaptive Nonlinear Control of Agile Antiair Msiles. Journal of Guidance, Control, and Dynamics, Vol., No., pp. 47-,. [6] L. Zhong, X. G. Liang, B. G. Cao and J. Y. Cao. An Optimal Backstepping Design for Blended Aero and Reaction-Jet Msile Autopilot. Journal of Applied Sciences, Vol. 6, No., pp. 6-68, 6. [7] E. Slotin. Applied Nonlinear Control. Prentice Hall International, Inc., 99. [8] C. Cao and N. Hovakimyan. L Adaptive Controller for a Class of System with Unknown Nonlinearities: Part I. American Control Conference, Washington, pp , 8. [9] N. Hovakimyan and C. Cao. L Adaptive Control Theory: Guaranteed Robustness with Fast Adaptation. Society for Industrial and Applied Mathematics,. [] C. H. Lee, T. H. Kim, S. M. Ryu and M. J. Tahk. Analys of Turning Maneuver for Agile Msile using Trajectory Optimization. Proceeding of KSAS Spring Conference, Pyeongchang, Korea, pp. 69-7, 9. (in Korean) Copyright Statement The authors confirm that they, and/or their company or organization, hold copyright on all of the original material included in th paper. The authors also confirm that they have obtained permsion, from the copyright holder of any third party material included in th paper, to publh it as part of their paper. The authors confirm that they give permsion, or have obtained permsion from the copyright holder of th paper, for the publication and dtribution of th paper as part of the ICAS proceedings or as individual off-prints from the proceedings. 6
Agile Missile Controller Based on Adaptive Nonlinear Backstepping Control
Agile Missile Controller Based on Adaptive Nonlinear Backstepping Control Chang-Hun Lee, Tae-Hun Kim and Min-Jea Tahk 3 Korea Advanced Institute of Science and Technology(KAIST), Daejeon, 305-70, Korea
More informationINTEGRATED INTERCEPT MISSILE GUIDANCE AND CONTROL WITH TERMINAL ANGLE CONSTRAINT
6th INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES INTEGRATED INTERCEPT MISSILE GUIDANCE AND CONTROL WITH TERMINAL ANGLE CONSTRAINT H. S. Shin*, T. W. Hwang**, A. Tsourdos***, B. A. White***, M. J.
More informationSUM-OF-SQUARES BASED STABILITY ANALYSIS FOR SKID-TO-TURN MISSILES WITH THREE-LOOP AUTOPILOT
SUM-OF-SQUARES BASED STABILITY ANALYSIS FOR SKID-TO-TURN MISSILES WITH THREE-LOOP AUTOPILOT Hyuck-Hoon Kwon*, Min-Won Seo*, Dae-Sung Jang*, and Han-Lim Choi *Department of Aerospace Engineering, KAIST,
More informationNew Parametric Affine Modeling and Control for Skid-to-Turn Missiles
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 9, NO. 2, MARCH 2001 335 New Parametric Affine Modeling and Control for Skid-to-Turn Missiles DongKyoung Chwa and Jin Young Choi, Member, IEEE Abstract
More informationOuter-Loop Sliding Mode Control Approach to Longitudinal Autopilot Missile Design. B. Kada*
Outer-Loop Sliding Mode Control Approach to Longitudinal Autopilot Missile Design B. Kada* *Aeronautical Engineering Department, King Abdulaziz University, P O Box 80204, Jeddah, 21589 KSA (Tel: 966-2-640-2000
More informationAUGMENTED POLYNOMIAL GUIDANCE FOR TERMINAL VELOCITY CONSTRAINTS
AUGMENTED POLYNOMIAL GUIDANCE FOR TERMINAL VELOCITY CONSTRAINTS Gun-Hee Moon*, Sang-Woo Shim*, and Min-Jea Tah* *Korea Advanced Institute Science and Technology Keywords: Polynomial guidance, terminal
More informationADAPTIVE NEURAL NETWORK CONTROLLER DESIGN FOR BLENDED-WING UAV WITH COMPLEX DAMAGE
ADAPTIVE NEURAL NETWORK CONTROLLER DESIGN FOR BLENDED-WING UAV WITH COMPLEX DAMAGE Kijoon Kim*, Jongmin Ahn**, Seungkeun Kim*, Jinyoung Suk* *Chungnam National University, **Agency for Defense and Development
More informationA Simple Design Approach In Yaw Plane For Two Loop Lateral Autopilots
A Simple Design Approach In Yaw Plane For Two Loop Lateral Autopilots Jyoti Prasad Singha Thakur 1, Amit Mukhopadhyay Asst. Prof., AEIE, Bankura Unnayani Institute of Engineering, Bankura, West Bengal,
More informationDesign of a Missile Autopilot using Adaptive Nonlinear Dynamic Inversion
2005 American Control Conference June 8-10,2005. Portland, OR, USA WeA11.1 Design of a Missile Autopilot using Adaptive Nonlinear Dynamic Inversion Rick Hindman, Ph.D. Raytheon Missile Systems Tucson,
More informationChapter 2 Review of Linear and Nonlinear Controller Designs
Chapter 2 Review of Linear and Nonlinear Controller Designs This Chapter reviews several flight controller designs for unmanned rotorcraft. 1 Flight control systems have been proposed and tested on a wide
More informationRobust Nonlinear Design of Three Axes Missile Autopilot via Feedback Linearization
Robust Nonlinear Design of Three Axes Missile Autopilot via Feedback Linearization Abhijit Das, Ranajit Das and Siddhartha Mukhopadhyay, Amit Patra 1 1 Abstract The nonlinearity and coupling of the missile
More informationDifferential Game Missile Guidance with Impact Angle and Time Constraints
Differential Game Missile Guidance with Impact Angle and Time Constraints Seonhyeok Kang H. Jin Kim School of Mechanical and Aerospace Engineering, Seoul National University, Seoul, Korea, (e-mail: hkkang@snu.ac.kr)
More informationDesign and modelling of an airship station holding controller for low cost satellite operations
AIAA Guidance, Navigation, and Control Conference and Exhibit 15-18 August 25, San Francisco, California AIAA 25-62 Design and modelling of an airship station holding controller for low cost satellite
More informationThe Role of Zero Dynamics in Aerospace Systems
The Role of Zero Dynamics in Aerospace Systems A Case Study in Control of Hypersonic Vehicles Andrea Serrani Department of Electrical and Computer Engineering The Ohio State University Outline q Issues
More informationTHE ANALYSIS OF LAMINATE LAY-UP EFFECT ON THE FLUTTER SPEED OF COMPOSITE STABILIZERS
THE ANALYSIS OF LAMINATE LAY-UP EFFECT ON THE FLUTTER SPEED OF COMPOSITE STABILIZERS Mirko DINULOVIĆ*, Boško RAŠUO* and Branimir KRSTIĆ** * University of Belgrade, Faculty of Mechanical Engineering, **
More informationA Model-Free Control System Based on the Sliding Mode Control Method with Applications to Multi-Input-Multi-Output Systems
Proceedings of the 4 th International Conference of Control, Dynamic Systems, and Robotics (CDSR'17) Toronto, Canada August 21 23, 2017 Paper No. 119 DOI: 10.11159/cdsr17.119 A Model-Free Control System
More informationPosition and Velocity Profile Tracking Control for New Generation Servo Track Writing
Preprints of the 9th World Congress The International Federation of Automatic Control Cape Town, South Africa. August 24-29, 24 Position and Velocity Profile Tracking Control for New Generation Servo Track
More informationMECH 6091 Flight Control Systems Final Course Project
MECH 6091 Flight Control Systems Final Course Project F-16 Autopilot Design Lizeth Buendia Rodrigo Lezama Daniel Delgado December 16, 2011 1 AGENDA Theoretical Background F-16 Model and Linearization Controller
More informationAdaptive Augmentation of a Fighter Aircraft Autopilot Using a Nonlinear Reference Model
Proceedings of the EuroGNC 13, 2nd CEAS Specialist Conference on Guidance, Navigation & Control, Delft University of Technology, Delft, The Netherlands, April -12, 13 Adaptive Augmentation of a Fighter
More informationThree-dimensional Guidance Law for Formation Flight of UAV
ICCAS25 Three-dimensional Guidance aw for Formation Flight of UAV Byoung-Mun Min * and Min-Jea Tahk ** * Department of Aerospace Engineering KAIST Daejeon Korea (Tel : 82-42-869-3789; E-mail: bmmin@fdcl.kaist.ac.kr)
More informationBackstepping Designs for Aircraft Control What is there to gain?
Backstepping Designs for Aircraft Control What is there to gain? Ola Härkegård Division of Automatic Control Department of Electrical Engineering Linköpings universitet, SE-581 83 Linköping, Sweden WWW:
More informationLongitudinal Flight Control Systems
Longitudinal Flight Control Systems 9 Basic Longitudinal Autopilots (I) Attitude Control System First idea: A Displacement Autopilot Typical block diagram: Vertical e g e δ Elevator δ A/C θ ref Amplifier
More information6-DOF simulation and the vulnerable area of the Air-to-Air missile to develop an End-game simulator
DOI: 1.139/EUCASS217-33 7 TH EUROPEAN CONFERENCE FOR AERONAUTICS AND SPACE SCIENCES (EUCASS) 6-DOF simulation and the vulnerable area of the Air-to-Air missile to develop an End-game simulator Eui-Gyu
More informationGain-scheduled Linear Quadratic Control of Wind Turbines Operating at High Wind Speed
16th IEEE International Conference on Control Applications Part of IEEE Multi-conference on Systems and Control Singapore, 1-3 October 7 Gain-scheduled Linear Quadratic Control of Wind Turbines Operating
More informationA Sliding Mode Controller Using Neural Networks for Robot Manipulator
ESANN'4 proceedings - European Symposium on Artificial Neural Networks Bruges (Belgium), 8-3 April 4, d-side publi., ISBN -9337-4-8, pp. 93-98 A Sliding Mode Controller Using Neural Networks for Robot
More informationL 1 Adaptive Control of a UAV for Aerobiological Sampling
Proceedings of the 27 American Control Conference Marriott Marquis Hotel at Times Square New York City, USA, July 11-13, 27 FrA14.1 L 1 Adaptive Control of a UAV for Aerobiological Sampling Jiang Wang
More informationLongitudinal Automatic landing System - Design for CHARLIE Aircraft by Root-Locus
International Journal of Scientific and Research Publications, Volume 3, Issue 7, July 2013 1 Longitudinal Automatic landing System - Design for CHARLIE Aircraft by Root-Locus Gaber El-Saady, El-Nobi A.Ibrahim,
More informationModelling the Dynamics of Flight Control Surfaces Under Actuation Compliances and Losses
Modelling the Dynamics of Flight Control Surfaces Under Actuation Compliances and Losses Ashok Joshi Department of Aerospace Engineering Indian Institute of Technology, Bombay Powai, Mumbai, 4 76, India
More informationDesign of Nonlinear Autopilots for High Angle of Attack Missiles. P. K. Menon * and M. Yousefpor. Optimal Synthesis. Palo Alto, CA 94306, USA
1 Design of Nonlinear Autopilots for High Angle of Attack Missiles By P. K. Menon * and M. Yousefpor Optimal Synthesis Palo Alto, CA 9436, USA Abstract Two nonlinear autopilot design approaches for a tail-controlled
More informationA Blade Element Approach to Modeling Aerodynamic Flight of an Insect-scale Robot
A Blade Element Approach to Modeling Aerodynamic Flight of an Insect-scale Robot Taylor S. Clawson, Sawyer B. Fuller Robert J. Wood, Silvia Ferrari American Control Conference Seattle, WA May 25, 2016
More informationWe are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors
e are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists 3,8 116, 12M Open access books available International authors and editors Downloads Our authors
More informationVortex Model Based Adaptive Flight Control Using Synthetic Jets
Vortex Model Based Adaptive Flight Control Using Synthetic Jets Jonathan Muse, Andrew Tchieu, Ali Kutay, Rajeev Chandramohan, Anthony Calise, and Anthony Leonard Department of Aerospace Engineering Georgia
More informationHover Control for Helicopter Using Neural Network-Based Model Reference Adaptive Controller
Vol.13 No.1, 217 مجلد 13 العدد 217 1 Hover Control for Helicopter Using Neural Network-Based Model Reference Adaptive Controller Abdul-Basset A. Al-Hussein Electrical Engineering Department Basrah University
More informationDynamic backstepping control for pure-feedback nonlinear systems
Dynamic backstepping control for pure-feedback nonlinear systems ZHANG Sheng *, QIAN Wei-qi (7.6) Computational Aerodynamics Institution, China Aerodynamics Research and Development Center, Mianyang, 6,
More informationA GLOBAL SLIDING MODE CONTROL WITH PRE-DETERMINED CONVERGENCE TIME DESIGN FOR REUSABLE LAUNCH VEHICLES IN REENTRY PHASE
IAA-AAS-DyCoSS-4 -- A GLOBAL SLIDING MODE CONTROL WITH PRE-DETERMINED CONVERGENCE TIME DESIGN FOR REUSABLE LAUNCH VEHICLES IN REENTRY PHASE L. Wang, Y. Z. Sheng, X. D. Liu, and P. L. Lu INTRODUCTION This
More informationTarget tracking and classification for missile using interacting multiple model (IMM)
Target tracking and classification for missile using interacting multiple model (IMM Kyungwoo Yoo and Joohwan Chun KAIST School of Electrical Engineering Yuseong-gu, Daejeon, Republic of Korea Email: babooovv@kaist.ac.kr
More informationTTK4150 Nonlinear Control Systems Solution 6 Part 2
TTK4150 Nonlinear Control Systems Solution 6 Part 2 Department of Engineering Cybernetics Norwegian University of Science and Technology Fall 2003 Solution 1 Thesystemisgivenby φ = R (φ) ω and J 1 ω 1
More informationFinal Exam TTK4190 Guidance and Control
Trondheim Department of engineering Cybernetics Contact person: Professor Thor I. Fossen Phone: 73 59 43 61 Cell: 91 89 73 61 Email: tif@itk.ntnu.no Final Exam TTK4190 Guidance and Control Friday May 15,
More informationNONLINEAR BACKSTEPPING DESIGN OF ANTI-LOCK BRAKING SYSTEMS WITH ASSISTANCE OF ACTIVE SUSPENSIONS
NONLINEA BACKSTEPPING DESIGN OF ANTI-LOCK BAKING SYSTEMS WITH ASSISTANCE OF ACTIVE SUSPENSIONS Wei-En Ting and Jung-Shan Lin 1 Department of Electrical Engineering National Chi Nan University 31 University
More informationNMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582
NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING NMT EE 589 & UNM ME 482/582 Simplified drive train model of a robot joint Inertia seen by the motor Link k 1 I I D ( q) k mk 2 kk Gk Torque amplification G
More informationAircraft Pitch Attitude Control Using Backstepping
Aircraft Pitch Attitude Control Using Backstepping Ola Härkegård and Torkel Glad Department of Electrical Engineering Linköping University, SE-581 83 Linköping, Sweden WWW: http://www.control.isy.liu.se
More informationGUIDANCE AND CONTROL FOR D-SEND#2
GUIDANCE AND CONTROL FOR D-SEND#2 Jun ichiro Kawaguchi, Tetsujiro Ninomiya, Hirokazu Suzuki Japan Aerospace Exploration Agency kawaguchi.junichiroh@jaxa.jp; ninomiya.tetsujiro@jaxa.jp; suzuki.hirokazu@jaxa.jp
More informationROBUST NONLINEAR CONTROL DESIGN FOR A HYPERSONIC AIRCRAFT USING SUM OF SQUARES METHOD
Proceedings of the ASME 21 Dynamic Systems and Control Conference DSCC21 September 12-15, 21, Cambridge, Massachusetts, USA DSCC21- ROBUST NONLINEAR CONTROL DESIGN FOR A HYPERSONIC AIRCRAFT USING SUM OF
More informationONE of the challenges in the design of attitude control
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY 1 Adaptive Sliding Mode Fault Tolerant Attitude Tracking Control for Flexible Spacecraft Under Actuator Saturation Bing Xiao, Qinglei Hu, Member, IEEE, YouminZhang,
More informationAdaptive Control of Hypersonic Vehicles in Presence of Aerodynamic and Center of Gravity Uncertainties
Control of Hypersonic Vehicles in Presence of Aerodynamic and Center of Gravity Uncertainties Amith Somanath and Anuradha Annaswamy Abstract The paper proposes a new class of adaptive controllers that
More informationQuaternion-Based Tracking Control Law Design For Tracking Mode
A. M. Elbeltagy Egyptian Armed forces Conference on small satellites. 2016 Logan, Utah, USA Paper objectives Introduction Presentation Agenda Spacecraft combined nonlinear model Proposed RW nonlinear attitude
More informationA Backstepping Design for Flight Path Angle Control
A Backstepping Design for Flight Path Angle Control Ola Härkegård and S. Torkel Glad Division of Automatic Control Department of Electrical Engineering Linköpings universitet, SE-581 83 Linköping, Sweden
More informationAircraft Stability & Control
Aircraft Stability & Control Textbook Automatic control of Aircraft and missiles 2 nd Edition by John H Blakelock References Aircraft Dynamics and Automatic Control - McRuler & Ashkenas Aerodynamics, Aeronautics
More informationGAIN SCHEDULING CONTROL WITH MULTI-LOOP PID FOR 2- DOF ARM ROBOT TRAJECTORY CONTROL
GAIN SCHEDULING CONTROL WITH MULTI-LOOP PID FOR 2- DOF ARM ROBOT TRAJECTORY CONTROL 1 KHALED M. HELAL, 2 MOSTAFA R.A. ATIA, 3 MOHAMED I. ABU EL-SEBAH 1, 2 Mechanical Engineering Department ARAB ACADEMY
More informationL 1 Adaptive Controller for a Missile Longitudinal Autopilot Design
AIAA Guidance, Navigation and Control Conference and Exhibit 8-2 August 28, Honolulu, Hawaii AIAA 28-6282 L Adaptive Controller for a Missile Longitudinal Autopilot Design Jiang Wang Virginia Tech, Blacksburg,
More informationLinear Quadratic Integrated vs. Separated Autopilot-Guidance Design
Proceedings of the EuroGNC 2013, 2nd CEAS Specialist Conference on Guidance, Navigation & Control, Delft University of Technology, Delft, The Netherlands, April 10-12, 2013 WeCT2.1 Linear Quadratic Integrated
More informationThree loop Lateral Missile Autopilot Design in Pitch Plane using State Feedback & Reduced Order Observer (DGO)
International Journal of Engineering Research and Development ISSN: 78-67X, Volume, Issue 8 (June ), PP.-7 www.ijerd.com Three loop Lateral Missile Autopilot Design in Pitch Plane using State Feedback
More informationAFRL MACCCS Review. Adaptive Control of the Generic Hypersonic Vehicle
AFRL MACCCS Review of the Generic Hypersonic Vehicle PI: Active- Laboratory Department of Mechanical Engineering Massachusetts Institute of Technology September 19, 2012, MIT AACL 1/38 Our Team MIT Team
More informationLecture AC-1. Aircraft Dynamics. Copy right 2003 by Jon at h an H ow
Lecture AC-1 Aircraft Dynamics Copy right 23 by Jon at h an H ow 1 Spring 23 16.61 AC 1 2 Aircraft Dynamics First note that it is possible to develop a very good approximation of a key motion of an aircraft
More informationAdaptive Nonlinear Control Allocation of. Non-minimum Phase Uncertain Systems
2009 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA June 10-12, 2009 ThA18.3 Adaptive Nonlinear Control Allocation of Non-minimum Phase Uncertain Systems Fang Liao, Kai-Yew Lum,
More informationAdaptive Trim and Trajectory Following for a Tilt-Rotor Tricopter Ahmad Ansari, Anna Prach, and Dennis S. Bernstein
7 American Control Conference Sheraton Seattle Hotel May 4 6, 7, Seattle, USA Adaptive Trim and Trajectory Following for a Tilt-Rotor Tricopter Ahmad Ansari, Anna Prach, and Dennis S. Bernstein Abstract
More informationIntroduction. 1.1 Historical Overview. Chapter 1
Chapter 1 Introduction 1.1 Historical Overview Research in adaptive control was motivated by the design of autopilots for highly agile aircraft that need to operate at a wide range of speeds and altitudes,
More informationTRACKING CONTROL VIA ROBUST DYNAMIC SURFACE CONTROL FOR HYPERSONIC VEHICLES WITH INPUT SATURATION AND MISMATCHED UNCERTAINTIES
International Journal of Innovative Computing, Information and Control ICIC International c 017 ISSN 1349-4198 Volume 13, Number 6, December 017 pp. 067 087 TRACKING CONTROL VIA ROBUST DYNAMIC SURFACE
More informationSliding Mode Control for Active Suspension System Using ICA Evolutionary Algorithm
Life Science Journal 213;1(3s) Sliding Mode Control for Active Suspension System Using ICA Evolutionary Algorithm Mohammad Faraji sarir 1, Jafar Ghafouri 2, Larisa Khodadadi 3 1- Department of Mechatronic
More informationOptimized Trajectory Shaping Guidance for an Air-to-Ground Missile Launched from a Gunship. Craig Phillips Ernie Ohlmeyer Shane Sorenson
Optimized Trajectory Shaping Guidance for an Air-to-Ground Missile Launched from a Gunship Craig Phillips Ernie Ohlmeyer Shane Sorenson Overview Mission Scenario Notional Munition Concept Guidance Laws
More informationCDS 101/110a: Lecture 8-1 Frequency Domain Design
CDS 11/11a: Lecture 8-1 Frequency Domain Design Richard M. Murray 17 November 28 Goals: Describe canonical control design problem and standard performance measures Show how to use loop shaping to achieve
More informationEE363 Automatic Control: Midterm Exam (4 problems, 90 minutes)
EE363 Automatic Control: Midterm Exam (4 problems, 90 minutes) ) Block diagram simplification (0 points). Simplify the following block diagram.,i.e., find the transfer function from u to y. Your answer
More informationRobust Control For Variable-Speed Two-Bladed Horizontal-Axis Wind Turbines Via ChatteringControl
Robust Control For Variable-Speed Two-Bladed Horizontal-Axis Wind Turbines Via ChatteringControl Leonardo Acho, Yolanda Vidal, Francesc Pozo CoDAlab, Escola Universitària d'enginyeria Tècnica Industrial
More informationL 1 Adaptive Controller for a Class of Systems with Unknown
28 American Control Conference Westin Seattle Hotel, Seattle, Washington, USA June -3, 28 FrA4.2 L Adaptive Controller for a Class of Systems with Unknown Nonlinearities: Part I Chengyu Cao and Naira Hovakimyan
More informationMODULAR AEROPLANE SYSTEM. A CONCEPT AND INITIAL INVESTIGATION
28 TH INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES MODULAR AEROPLANE SYSTEM. A CONCEPT AND INITIAL INVESTIGATION Marcin Figat, Cezary Galiński, Agnieszka Kwiek Warsaw University of Technology mfigat@meil.pw.edu.pl;
More informationIntroduction to System Identification and Adaptive Control
Introduction to System Identification and Adaptive Control A. Khaki Sedigh Control Systems Group Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology May 2009 Introduction
More informationAerospace Science and Technology
Aerospace Science and Technology 77 218 49 418 Contents lists available at ScienceDirect Aerospace Science and Technology www.elsevier.com/locate/aescte Two-degree-of-freedom attitude tracking control
More informationPERFORMANCE ANALYSIS OF ISL S GUIDED SUPERSONIC PROJECTILE. Pierre Wey
3 RD INTERNATIONAL SYMPOSIUM ON BALLISTICS TARRAGONA, SPAIN 16- APRIL 7 PERFORMANCE ANALYSIS OF ISL S GUIDED SUPERSONIC PROJECTILE Pierre Wey French-German Research Institute of Saint-Louis (ISL) P.O.
More informationQuadrotor Modeling and Control
16-311 Introduction to Robotics Guest Lecture on Aerial Robotics Quadrotor Modeling and Control Nathan Michael February 05, 2014 Lecture Outline Modeling: Dynamic model from first principles Propeller
More informationFlight Dynamics and Control. Lecture 3: Longitudinal stability Derivatives G. Dimitriadis University of Liege
Flight Dynamics and Control Lecture 3: Longitudinal stability Derivatives G. Dimitriadis University of Liege Previously on AERO0003-1 We developed linearized equations of motion Longitudinal direction
More informationDISTURBANCES MONITORING FROM CONTROLLER STATES
DISTURBANCES MONITORING FROM CONTROLLER STATES Daniel Alazard Pierre Apkarian SUPAERO, av. Edouard Belin, 3 Toulouse, France - Email : alazard@supaero.fr Mathmatiques pour l Industrie et la Physique, Université
More informationFLIGHT DYNAMICS. Robert F. Stengel. Princeton University Press Princeton and Oxford
FLIGHT DYNAMICS Robert F. Stengel Princeton University Press Princeton and Oxford Preface XV Chapter One Introduction 1 1.1 ELEMENTS OF THE AIRPLANE 1 Airframe Components 1 Propulsion Systems 4 1.2 REPRESENTATIVE
More informationAdaptive control of time-varying systems with gain-scheduling
2008 American Control Conference Westin Seattle Hotel, Seattle, Washington, USA June 11-13, 2008 ThC14.5 Adaptive control of time-varying systems with gain-scheduling Jinho Jang, Anuradha M. Annaswamy,
More informationH 2 Adaptive Control. Tansel Yucelen, Anthony J. Calise, and Rajeev Chandramohan. WeA03.4
1 American Control Conference Marriott Waterfront, Baltimore, MD, USA June 3-July, 1 WeA3. H Adaptive Control Tansel Yucelen, Anthony J. Calise, and Rajeev Chandramohan Abstract Model reference adaptive
More informationAircraft Maneuver Regulation: a Receding Horizon Backstepping Approach
Aircraft Maneuver Regulation: a Receding Horizon Backstepping Approach Giuseppe Notarstefano and Ruggero Frezza Abstract Coordinated flight is a nonholonomic constraint that implies no sideslip of an aircraft.
More informationNONLINEAR CONTROL FOR HIGH-ANGLE-OF-ATTACK AIRCRAFT FLIGHT USING THE STATE-DEPENDENT RICCATI EQUATION
UDC 629.72.57 A. Prach, O. ekinalp Р о з д і л 3. 159 NONLINEAR CONROL FOR HIGH-ANGLE-OF-AACK AIRCRAF FLIGH USING HE SAE-DEPENDEN RICCAI EQUAION Introduction Flight control systems for aerospace vehicles
More informationNONLINEAR PATH CONTROL FOR A DIFFERENTIAL DRIVE MOBILE ROBOT
NONLINEAR PATH CONTROL FOR A DIFFERENTIAL DRIVE MOBILE ROBOT Plamen PETROV Lubomir DIMITROV Technical University of Sofia Bulgaria Abstract. A nonlinear feedback path controller for a differential drive
More informationAdaptive Robust Control (ARC) for an Altitude Control of a Quadrotor Type UAV Carrying an Unknown Payloads
2 th International Conference on Control, Automation and Systems Oct. 26-29, 2 in KINTEX, Gyeonggi-do, Korea Adaptive Robust Control (ARC) for an Altitude Control of a Quadrotor Type UAV Carrying an Unknown
More informationA Novel Finite Time Sliding Mode Control for Robotic Manipulators
Preprints of the 19th World Congress The International Federation of Automatic Control Cape Town, South Africa. August 24-29, 214 A Novel Finite Time Sliding Mode Control for Robotic Manipulators Yao ZHAO
More informationRobust Adaptive Attitude Control of a Spacecraft
Robust Adaptive Attitude Control of a Spacecraft AER1503 Spacecraft Dynamics and Controls II April 24, 2015 Christopher Au Agenda Introduction Model Formulation Controller Designs Simulation Results 2
More informationAdaptive Dynamic Inversion Control of a Linear Scalar Plant with Constrained Control Inputs
5 American Control Conference June 8-, 5. Portland, OR, USA ThA. Adaptive Dynamic Inversion Control of a Linear Scalar Plant with Constrained Control Inputs Monish D. Tandale and John Valasek Abstract
More informationOn-Line Approximation Control of Uncertain Nonlinear Systems: Issues with Control Input Saturation 1
On-Line Approximation Control of Uncertain Nonlinear Systems: Issues with Control Input Saturation Marios Polycarpou, Jay Farrell and Manu Sharma Department of ECECS, University of Cincinnati, Cincinnati,
More informationRobust Stabilization of Non-Minimum Phase Nonlinear Systems Using Extended High Gain Observers
28 American Control Conference Westin Seattle Hotel, Seattle, Washington, USA June 11-13, 28 WeC15.1 Robust Stabilization of Non-Minimum Phase Nonlinear Systems Using Extended High Gain Observers Shahid
More informationMulti-Model Adaptive Regulation for a Family of Systems Containing Different Zero Structures
Preprints of the 19th World Congress The International Federation of Automatic Control Multi-Model Adaptive Regulation for a Family of Systems Containing Different Zero Structures Eric Peterson Harry G.
More informationControl of industrial robots. Centralized control
Control of industrial robots Centralized control Prof. Paolo Rocco (paolo.rocco@polimi.it) Politecnico di Milano ipartimento di Elettronica, Informazione e Bioingegneria Introduction Centralized control
More informationAdaptive Pole Assignment Control for Generic Elastic Hypersonic Vehicle
Adaptive Pole Assignment Control for Generic Elastic Hypersonic Vehicle Yan Binbin he College of Astronautics, Northwestern Polytechnical University, Xi an, Shanxi, China Email: yanbinbin@ nwpu.edu.cn
More informationA NONLINEAR TRANSFORMATION APPROACH TO GLOBAL ADAPTIVE OUTPUT FEEDBACK CONTROL OF 3RD-ORDER UNCERTAIN NONLINEAR SYSTEMS
Copyright 00 IFAC 15th Triennial World Congress, Barcelona, Spain A NONLINEAR TRANSFORMATION APPROACH TO GLOBAL ADAPTIVE OUTPUT FEEDBACK CONTROL OF RD-ORDER UNCERTAIN NONLINEAR SYSTEMS Choon-Ki Ahn, Beom-Soo
More informationSwinging-Up and Stabilization Control Based on Natural Frequency for Pendulum Systems
9 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA June -, 9 FrC. Swinging-Up and Stabilization Control Based on Natural Frequency for Pendulum Systems Noriko Matsuda, Masaki Izutsu,
More informationDesign of an adaptive sliding mode controller for robust yaw stabilisation of in-wheel-motor-driven electric vehicles
98 Int. J. Vehicle Design, Vol. 67, No. 1, 2015 Design of an adaptive sliding mode controller for robust yaw stabilisation of in-wheel-motor-driven electric vehicles Kanghyun Nam* Samsung Electronics Co.,
More informationNEURAL NETWORK ADAPTIVE SEMI-EMPIRICAL MODELS FOR AIRCRAFT CONTROLLED MOTION
NEURAL NETWORK ADAPTIVE SEMI-EMPIRICAL MODELS FOR AIRCRAFT CONTROLLED MOTION Mikhail V. Egorchev, Dmitry S. Kozlov, Yury V. Tiumentsev Moscow Aviation Institute (MAI), Moscow, Russia Keywords: aircraft,
More informationDynamic Integral Sliding Mode Control of Nonlinear SISO Systems with States Dependent Matched and Mismatched Uncertainties
Milano (Italy) August 28 - September 2, 2 Dynamic Integral Sliding Mode Control of Nonlinear SISO Systems with States Dependent Matched and Mismatched Uncertainties Qudrat Khan*, Aamer Iqbal Bhatti,* Qadeer
More informationLYAPUNOV-BASED CONTROL OF LIMIT CYCLE OSCILLATIONS IN UNCERTAIN AIRCRAFT SYSTEMS
LYAPUNOV-BASED CONTROL OF LIMIT CYCLE OSCILLATIONS IN UNCERTAIN AIRCRAFT SYSTEMS By BRENDAN BIALY A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF
More informationAutomated Estimation of an Aircraft s Center of Gravity Using Static and Dynamic Measurements
Proceedings of the IMAC-XXVII February 9-, 009 Orlando, Florida USA 009 Society for Experimental Mechanics Inc. Automated Estimation of an Aircraft s Center of Gravity Using Static and Dynamic Measurements
More informationAdaptive Robust Tracking Control of Robot Manipulators in the Task-space under Uncertainties
Australian Journal of Basic and Applied Sciences, 3(1): 308-322, 2009 ISSN 1991-8178 Adaptive Robust Tracking Control of Robot Manipulators in the Task-space under Uncertainties M.R.Soltanpour, M.M.Fateh
More informationNeural Network-Based Adaptive Control of Robotic Manipulator: Application to a Three Links Cylindrical Robot
Vol.3 No., 27 مجلد 3 العدد 27 Neural Network-Based Adaptive Control of Robotic Manipulator: Application to a Three Links Cylindrical Robot Abdul-Basset A. AL-Hussein Electrical Engineering Department Basrah
More informationDesign and Stability Analysis of Single-Input Fuzzy Logic Controller
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS PART B: CYBERNETICS, VOL. 30, NO. 2, APRIL 2000 303 Design and Stability Analysis of Single-Input Fuzzy Logic Controller Byung-Jae Choi, Seong-Woo Kwak,
More informationPrediction of Aircraft s Longitudinal Motion Based on Aerodynamic Coefficients and Derivatives by Surrogate Model Approach
Journal of Mechanics Engineering and Automation 4 (2014) 584-594 D DAVID PUBLISHING Prediction of Aircraft s Longitudinal Motion Based on Aerodynamic Coefficients and Derivatives by Surrogate Model Approach
More informationDISTURBANCE OBSERVER BASED CONTROL: CONCEPTS, METHODS AND CHALLENGES
DISTURBANCE OBSERVER BASED CONTROL: CONCEPTS, METHODS AND CHALLENGES Wen-Hua Chen Professor in Autonomous Vehicles Department of Aeronautical and Automotive Engineering Loughborough University 1 Outline
More informationIncremental Backstepping for Robust Nonlinear Flight Control
Proceedings of the EuroGNC 2013, 2nd CEAS Specialist Conference on Guidance, Navigation & Control, Delft University of Technology, Delft, The Netherlands, April 10-12, 2013 FrBT1.3 Incremental Backstepping
More informationIntroduction to centralized control
ROBOTICS 01PEEQW Basilio Bona DAUIN Politecnico di Torino Control Part 2 Introduction to centralized control Independent joint decentralized control may prove inadequate when the user requires high task
More information