Presentation for Dr Haitham Taha Colligues Aug2017 Dynamics

Presentation for Dr Haitham Taha & Colligues Aug-2017 Dynamics, Optimization & Control of Biologically Inspired Dynamic Soaring Maneuvers for a Morphing Capable UAV 1

Presentation Outline • Introduction • UAS – Problem of energy deficiency in s. UAS • Dynamic soaring a potential solution • Biological Inspiration: Dynamic soaring under morphing conditions • Area of research : Integration of two concepts • Research results • Task accomplished till date • Future work to be carried out in next six months at UCI 2

Introduction 3

Introduction : s. UAS • s. UAS ØUtility surveillance, communication relay & loitering dominated missions Ølow radar cross section area, ability to perform agile maneuvers close to the proximity of ground, reduced vulnerability, low fuel consumption, low cost 4

Introduction : s. UAS • Diverse set of mission requirement necessitates • s. UAS to improve the time aloft • Speed, range and endurance Much larger platform • Possible Solution • Upgrade battery/fuel system Elevated cost and space requirement • Tapping energy from atmosphere though Soaring (Biological inspiration) 5

Dynamic Soaring § • The extraction of energy from atmospheric wind shear Has four characteristic phases 6

Dynamic Soaring Initial Orientation Yaw movement Dynamic Soaring Roll movement 7 Pitch movement

USEFUL STUDIES 8

Some Useful studies : Gottfried Sachs § Gottfried Sachs : 12 relevant publications from 1991 to 2017 [1] G. Sachs and B. Grüter, "Dynamic Soaring− Kinetic Energy and Inertial Speed, " in AIAA Atmospheric Flight Mechanics Conference, 2017, p. 1862. Ø Kinetic energy plays an important role in the energy management of dynamic soaring Ø important to use an appropriate kinetic energy concept Ø Utilized kinetic energy based on inertial speed 9

Some Useful studies : Gottfried Sachs [2] G. Sachs, "In-flight measurement of upwind dynamic soaring in albatrosses, " Progress in Oceanography, vol. 142, pp. 47 -57, 2016. [3] G. Sachs, J. Traugott, A. Nesterova, and F. Bonadonna, "Experimental verification of dynamic soaring in albatrosses, " The Journal of experimental biology, vol. 216, pp. 4222 -4232, 2013. [4] G. Sachs, J. Traugott, A. P. Nesterova, G. Dell'Omo, F. Kuemmeth, W. Heidrich, et al. , "Flying at No Mechanical Energy Cost: Disclosing the Secret of Wandering Albatrosses, " Plos One, vol. 7, Sep 5 2012. [5] G. Sachs, J. Traugott, and F. Holzapfel, "Progress against the Wind with Dynamic Soaring-Results from In-Flight Measurements of Albatrosses, " in AIAA Guidance Navigation and Control Conference, AIAA, 2011, p. 2011. [6] G. Sachs, J. Traugott, and F. Holzapfel, "In-flight measurement of dynamic soaring in albatrosses, " in AIAA Guidance, Navigation, and Control Conference, Toronto, Ontario Canada, 2010, pp. 2 -5. 10

Some Useful studies : Gottfried Sachs § Dynamic soaring is a small-scale flight maneuver which is the basis for the extreme flight performance of albatrosses and other large seabirds to travel huge distances in sustained nonflapping flight. § Experimental data with sufficient resolution of these smallscale movements are not available § In-house developments of GPS logging units for recording raw phase observations and of a dedicated mathematical method for post processing these measurements 11

Some Useful studies : Gottfried Sachs § Experimental results from tracking 16 wandering albatrosses show the characteristic pattern of dynamic soaring throughout their flight 12

Some Useful studies : Gottfried Sachs [7] G. Sachs, "Minimum shear wind strength required for dynamic soaring of albatrosses, " Ibis, vol. 147, pp. 1 -10, 2005. [8] G. Sachs and O. da Costa, "Optimization of dynamic soaring at ridges, " in AIAA Atmospheric Flight Mechanics Conference and Exhibit, Austin, Texas, 2003, pp. 11 -14. [9] G. Sachs and M. Mayrhofer, "Shear wind strength required for dynamic soaring at ridges, " Technical Soaring, vol. 25, pp. 209 -215, 2001. [10] G. Sachs, "Optimal Wind Energy Extraction for Dynamic Soaring, " in Applied Mathematics in Aerospace Science and Engineering, ed: Springer, 1994, pp. 221 -237. [11] G. Sachs, A. Knoll, and K. Lesch, "Optimal utilization of wind energy for dynamic soaring, " Technical Soaring, vol. 15, pp. 48 -55, 1991. [12] G. Sachs, "MINIMUM CONDITIONS FOR DYNAMIC SOARING, " Zeitschrift Fur Flugwissenschaften Und Weltraumforschung, vol. 13, pp. 188198, May-Jun 1989. 13

Some Useful studies: Gottfried Sachs § A mathematical optimization method (GESOP and ALTOS) is used for computing minimum shear wind energy-neutral trajectories § The minimum shear wind strength is of a magnitude that often exists or is exceeded in areas in which albatrosses are found Ø 5 m/s close to sea level (0. 79 m height) § The mechanism of energy transfer from the shear flow to the bird is considered, and it is shown that there is a significant energy gain in the upper curve and a loss in the lower curve. 14

Some Useful studies Evaluation of dynamic soaring flight characteristics § Dynamic soaring flight characteristics have been investigated actively by various researchers to determine the fundamentals of soaring flight. § Parameters such as the peak altitude/speeds attained during the soaring maneuvers, cycle time, minimum wind shear required for birds /UAVs were subsequently determined 15

Some Useful studies § Zhao investigated Ø Optimal dynamic soaring patterns (loiter, travel and basic modes) of a glider in wind gradients [1] Ø Minimum fuel powered dynamic soaring of UAV utilizing wind gradients [2] 1. Y. J. Zhao, "Optimal patterns of glider dynamic soaring, " Optimal control applications and methods, vol. 25, pp. 2. 16 67 -89, 2004. 1. Y. Y. J. Zhao and Y. C. Qi, "Minimum fuel powered dynamic soaring of unmanned aerial vehicles utilizing wind gradients, " Optimal Control Applications & Methods, vol. 25, pp. 211 -233, Sep-Oct 2004.

Some Useful studies: Optimal dynamic soaring patterns § Min cycle time § Max altitude gain 17

Some Useful studies: Minimum fuel (min thrust for jet and min power for prop) powered dynamic soaring trajectories § When the wind gradient is sufficiently steep, a UAV can perform dynamic soaring without using any thrust. § If the wind gradient is not sufficient to maintain powerless dynamic soaring, on the other hand, a UAV can still take advantage of the wind gradient to reduce fuel consumptions by performing powered dynamic soaring flights. § In this case, the largest wind condition parameter at which powerless dynamic soaring is still possible sets a bound on the range of wind conditions 18 1. Y. Y. J. Zhao and Y. C. Qi, "Minimum fuel powered dynamic soaring of unmanned aerial vehicles utilizing wind gradients, " Optimal Control Applications & Methods, vol. 25, pp. 211 -233, Sep-Oct 2004.

Some Useful studies § Sachs investigated dynamic soaring at ridges and determined that significant shear wind conditions exists behind ridges to successfully perform dynamic soaring § Zhao & Lissaman evaluated that shear layers over the ocean contain sufficient energy to provide continuous or assisted flight for small (< 10 kg) UAVs 1. Zhao dynamic soaring of of UAVs utilizingsoaring wind gradients, “ 2004. G. "Minimum Sachs andfuel O. powered da Costa, "Optimization dynamic at ridges, " in AIAA P. Lissaman, "Wind energy by Conference birds and flight vehicles, " paper, Texas, vol. 241, 2005 pp. Atmospheric Flight extraction Mechanics and Exhibit, AIAA Austin, 2003, 11 -14. 19

Some Useful studies § For full-scale aircraft Ø Sachs and da Costa showed that dynamic soaring by full-size sailplanes is possible with values of wind shear found near mountain ridges Ø Gordan showed full size sailplanes could extract energy from horizontal wind shears, although the utility of the energy extraction could be marginal depending on the flight conditions and type of sailplane used 20 R. J. Sachs G. Gordon, and O. "Optimal da Costa, dynamic "Optimization soaring for of dynamic full size sailplanes, " soaring at ridges, “ 2003 DTIC Document 2006.

Some Useful studies § Gao [1] , Lawrence [2] implemented DS trajectories utilizing piece wise controllers for each of the four phases of DS for a fixed-wing gliding UAV Ø Computationally simple Ø Not accurate 1. X. Z. Gao, Z. X. Hou, Z. Guo, R. F. Fan, and X. Q. Chen, "Analysis and design of guidance-strategy for dynamic soaring with UAVs, " Control Engineering Practice, vol. 32, pp. 218 -226, Nov 2014. 2. 21 Lawrance and Sukkarieh, "A guidance and control strategy for dynamic soaring in a gliding UAV, “ 2009

Some Useful studies § Zhu (2015) performed trajectory optimization for Long Endurance (loiter mode) and Long Distance (forward flight) for Engineless UAV by Dynamic Soaring B. Zhu, Z. Hou, X. Wang, and Q. Chen, "Long Endurance and Long Distance Trajectory Optimization for Engineless UAV by Dynamic Soaring, " CMES: Computer Modeling in 22 Engineering & Sciences, vol. 106, pp. 357 -377, 2015.

Some Useful studies § Akhtar [1, 2] developed dynamic soaring trajectories employing nonlinear constrained optimization method where some reference polynomials Ø The trajectories are defined by the coefficients of the polynomials. The coefficients are determined analytically from the boundary conditions and the final time. [1] N. Akhtar, J. F. Whidborne, and A. K. Cooke, "Wind shear energy extraction using dynamic soaring techniques, " 2009 23 [2] N. Akhtar, J. F. Whidborne, and A. K. Cooke, "Real-time optimal techniques for unmanned air vehicles fuel saving, " 2012

Critical Observation § Dynamic soaring maneuver has never been attempted for a morphing platform § Soaring birds rests on its wings with a shoulder lock, skillfully vary wing planform and twist, during dynamic soaring [1, 2, 3] § Biologically inspired UAV will be able to acquire maximum energy from the atmosphere 24 1. J. P. Barnes, "How Flies the Albatross–the Flight Mechanics of Dynamic Soaring, " SAE Technical Paper 2004. 2. X. -Z. Gao, Z. -X. Hou, Z. Guo, and X. -Q. Chen, "Energy extraction from wind shear: Reviews of dynamic soaring, " Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 229, pp. 2336 -2348, 2015. 3. D. Lentink, U. Müller, E. Stamhuis, R. De Kat, W. Van Gestel, L. Veldhuis, et al. , "How swifts control their glide performance with morphing wings, " Nature, vol. 446, pp. 1082 -1085, 2007.

Research Neech • For UAV Ø Majority of the studies utilize off-line numerical optimization techniques Ø Confined to fixed planform configurations • Requirement existed Ø to compute optimal trajectories in near real time environment for on board utilization Ø to perform analysis for dynamic soaring under morphing conditions 1. Zhao, Y. Y. J. and Y. C. Qi, Minimum fuel powered dynamic soaring of unmanned aerial vehicles utilizing wind Optimal Control Applications 2004. 25(5): soaring, " p. 211 -233. Optimal control applications 1. gradients. Y. J. Zhao, "Optimal patterns &of. Methods, glider dynamic 1. Sachs, Minimumvol. shear 25, wind strength required and G. , methods, pp. 67 -89, 2004. for dynamic soaring of albatrosses. Ibis, 2005. 147(1): p. 1 -10. 2. Sachs, G. and O. da Costa. Optimization of dynamic soaring at ridges. in AIAA Atmospheric Flight Mechanics 2. Conference N. Akhtar, J. F. Whidborne, and A. K. Cooke, "Real-time optimal techniques for and Exhibit, Austin, Texas. 2003. unmanned vehicles. Shear fuelwind saving, " Proceedings of thesoaring Institution of Technical Mechanical 3. Sachs, G. and M. air Mayrhofer, strength required for dynamic at ridges. Soaring, 2001. 25(4): p. 209 -215. Engineers 2 Y. J. Zhao, "Optimal patterns of glider dynamic soaring, " Optimal control applications and methods, vol. 25, pp. 6789, 2004. üMorphing has significant impact on aircraft performance & flight dynamics characteristics 25

Area of Research Dynamics, Optimization & Control of Biologically Inspired Dynamic Soaring Maneuvers for a Morphing Capable UAV 26

Area of Research • Optimal Dynamic soaring maneuvers will be implemented for a morphing capable platform which can alter its planform configuration (span and sweep variations) 27

Problem Formulation 28

Description of Platform • Modal Specifications Geometric Attribute Dimensions Mass 1. 25 kg Aerodynamic coefficient (k) 0. 08 Fuselage Length 1 m Zero Lift Drag coefficient 0. 004 (CDo) 29 Span Variation 1. 25 m ± 50% velocity range 3 - 30 m/s MAC Area 0. 48 m 0. 6 m 2 Azimuth (ψ) range -540° to 90° Flight path angle (γ) range -60° to 60° Aspect Ratio 4. 31 Bank Angle range Sweep variation 0 -25° Cycle time 1 -30 s Wing Airfoil NACA 0012 Max Load factor 5 -70° to 70°

Mathematical Modeling • Non Linear UAV Dynamics model 30

Mathematical Modeling • State vector • Control vector 31

Mathematical Modeling • Boundary Constraints • Wind Model 32

Mathematical Modeling • Path Constraints 33

Software Utilized • Trajectory Optimization – Dyn. Opt – GPOPS II • Utilization of direct collocation methods, the optimal control problem is transcribed to a nonlinear programming problem (NLP) by parameterizing the state and control using global polynomials – IPOPT (NLP Solver) – Matlab 34

Comparative Analysis: Morphing Vs Fixed Wing • Trajectory optimization for dynamic soaring is formulated for UAV with fixed planform and than morphing configurations. • Evaluation of various aspects of dynamic soaring parameters – cycle time – maximum achievable velocity – minimum required wind shear – maximum altitude gain – energy (total, potential and kinetic) gain – distances covered in the east / north direction 35

• General Aspects 36

Load Factor constraint affects Velocity and Span Max velocity in the DS loop is constrained by load factor constraint Max velocity occurs – max permissible load factor – min CL, min span, max sweep 37

Dynamic Soaring Heuristics: Zho • Shear layer is being considered as a limited height structure (that is, the horizontal wind speed increases linearly to some altitude and is constant for higher altitudes) ho is the surface correctness factor 38

Morphing Impact • At higher speeds, high sweep/ low span improves aerodynamic wing performance by reducing drag whereas low sweep/ high span wings contributes in better performance at low velocities by providing more lift • At lower speeds, low sweep/ high span wings deliver superior glide ratios and at higher speeds glide ratio is higher for high sweep/low span wings 39 [1] D. Lentink, U. Müller, E. Stamhuis, R. De Kat, W. Van Gestel, L. Veldhuis, et al. , "How swifts control their glide performance with morphing wings, " Nature, vol. 446, pp. 10821085, 2007.

Dynamic Soaring Cycle • During the climb phase – The K. E is traded for P. E and velocity starts decreasing 40

Span Morphing Results 41

Comparative Analysis: Morphing Vs Fixed Wing • Optimized Trajectory 42

Altitude Gain 43

East Distance Coverage 44

North Distance Coverage 45

Load Factor constraint affects Velocity and Span • Max velocity in the DS loop is constrained by load factor constraint • Max velocity occurs – max permissible load factor – min CL, min span, max sweep 46

Velocity Vs Altitude 47

Control Effort : Span morphing 48

Normalized energies 49

Dynamic Soaring Heuristics: Zho • Shear layer is being considered as a limited height structure (that is, the horizontal wind speed increases linearly to some altitude and is constant for higher altitudes) ho is the surface correctness factor 50

Minimum wind shear requirement Fixed 1. 25 m span Fixed 1. 75 m span Morphing configuration Minimum wind speeds required for dynamic soaring at sea level conditions are 6. 6 m/s (for 1. 25 m span), 6. 8 m/s (for 1. 75 m span) and 5. 6 m/s (for morphing platform). 51

Control Effort : Angle of attack 52

Lift Coefficient 53

Drag Coefficient variation wrt span 54

Drag Coefficient variation wrt velocity and altitude 55

Heading, FPA, and bank angle 56

Comparative Analysis: Span Morphing Vs Fixed Configurations S No Nom 1 2 3 4 5 57 Maximum altitude gain Distance covered in east direction Distance covered in north direction Normalized energy Maximum speed Worst case fixed Span Morphing span configuration Configuration value 150 ft 210 ft % Improvement (Morphing valuefixed value)/Fixed value 40% enhancement 210 ft 300 ft 42% enhancement 70 ft 100 ft 42% enhancement 5200 7200 38% higher energy 100 ft/sec 120 ft/sec 20% higher max velocity

Comparative Analysis: Span Morphing Vs Fixed Configurations S No Nom 6 Span Morphing Configuration Minimum wind shear at sear level (1 m) Maximum required Aoa 6. 8 m/s 5. 6 m/s 5. 2 3. 7 8 Maximum Cl requirement 0. 45 0. 4 9 Max Drag reduction 0. 0334 0. 023 7 58 Worst case fixed span configuration value % Improvement (Morphing valuefixed value)/Fixed value 18% lesser minimum wind shear requirement 29% lesser maximum Ao. A required 11% lesser AOA requirement 34% decrease in maximum drag

Sweep Morphing Results 59

Optimized Trajectory 60

Control Effort : Sweep morphing 61

Lift Coefficient 62

Comparative Analysis: Morphing Vs Fixed Wing • Drag Coefficient 63

Comparative Analysis: Morphing Vs Fixed Wing • Control Effort : Angle of attack 64

Comparative Analysis: Morphing Vs Fixed Wing • Control Effort : Bank angle 65

Comparative Analysis: Sweep Morphing Vs Fixed Wing S No Nomen 1 Maximum altitude gain 210 ft 2 Energy gain 7600 3 Maximum velocity 118 ft/sec 4 Maximum Angle of attack requirement 2. 2 ° 5 Minimum wind shear required Wind velocity of 5 m/s (close to se level) 6 Drag coefficient 66 Fixed 0° sweep configuration Morphing configuration (020° sweep) 230 ft 10% improvement 8200 6. 5 % improvement 125 ft/sec 6% improvement 2° 10% reduction 4. 2 m/s 15 % reduction 15% lesser

Work Task Accomplished till Date • Optimal dynamic soaring trajectories implemented for a fixed configuration UAV suitable for near real time implementations (computation time of under 4 sec) • Optimal dynamic soaring trajectories formulated for a morphing capable platform capable of – Span morphing (50% span variation) – Sweep morphing (0 -20°) – Hybrid morphing (span + sweep variations) 67

Publications Conference Papers • Optimization of Dynamic Soaring Maneuvers for a Morphing Capable UAV. AIAA Scitech 2017, Grapevine, USA (Published) • Dynamic Modeling & Stability Analysis of a generic UAV in Glide Phase. International conference on Mechanical, Material and Aerospace Engineering (2 MAE), 2017 (Published) • Optimization of Dynamic Soaring Maneuvers to Enhance Endurance of a fixed configuration UAV. International conference on Aerospace, Mechanical and Mechatronic Engineering (CAMME), 2017 Thailand (Published) • Autonomous Dynamic Soaring Maneuvers for a UAV Capable of Span Morphing. AIAA Scitech 2018, Florida, USA (submitted) 68

Publications Journal Papers (Under Review) • Real Time Trajectory Optimization of Dynamic Soaring Maneuvers Using Orthogonal Collocation Techniques. Submitted to Journal of Theoretical And Applied Mechanics (JTAM) , April 2017 (Under Review) • Dynamic Soaring Maneuvers for an unmanned aircraft capable of sweep morphing. IEEE Access , June 2017 (Under Review) • Dynamics, optimization and control of autonomous Aerial vehicles. IEEE Access , June 2017 (Under Review) • Autonomous dynamic soaring for a morphing capable UAV (under finalization stages at UCI) 69

Tasks for Next Six Months at UCI • To get familiarize with the ongoing research activities and the tools used at Flight Dynamics and Control Lab, UCI • To learn about various non-linear control techniques (such as Sliding Mode Control, Back stepping controller, Feed back linearization, Control lypnov function, Geometric control and so on). In specific those already employed to solve engineering problems by the research group • Synthesis of control law for implementing optimized dynamic soaring trajectories utilizing most relevant control technique • Publication of at least 02 Impact factor journal for the developed control architecture 70

THANK YOU 71