Volume 19, Issue 11 (November 2019)                   Modares Mechanical Engineering 2019, 19(11): 2761-2769 | Back to browse issues page

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Moghadasian M, Roshanian J. Optimal Landing of Unmanned Aerial Vehicle Using Vectorised High Order Expansions Method. Modares Mechanical Engineering 2019; 19 (11) :2761-2769
URL: http://mme.modares.ac.ir/article-15-27084-en.html
1- Department of Flight Dynamics & Control, Faculty of Aerospace Engineering, K.N. Toosi University of Technology, Tehran, Iran
2- Department of Flight Dynamics & Control, Faculty of Aerospace Engineering, K.N. Toosi University of Technology, Tehran, Iran , roshanian@kntu.ac.ir
Abstract:   (4642 Views)
In this research, an innovative approach has been proposed to the calculation of high order sensitivities and designing its guidance commands for an unmanned aerial vehicle landing strategy design. This method, which is called vectorised high order method, has been developed based on high order expansions method and its implementation using matrix-based mathematical calculations. In this research, a method is presented to design and extract the acceleration commands for landing maneuvers, by combining the vectorised high order expansions method and optimal control theory. Accordingly, the sensitivity variables for the given problem are calculated up to the 6th term and then the reference trajectory and acceleration command in the simulations are updated based on the initial deviations. In order to performance evaluation of the proposed method, 3 landing scenarios with the different initial deviations have been considered and the results of simulation of the proposed guidance law have been presented.
Full-Text [PDF 1025 kb]   (2053 Downloads)    
Article Type: Original Research | Subject: Control
Received: 2018/11/11 | Accepted: 2019/05/21 | Published: 2019/11/21

References
1. 1- Liao SJ. An approximate solution technique not dependent on small parameters: A special example. International Journal of Non Linear Mechanics. 1995;30(3):371-380. [Link] [DOI:10.1016/0020-7462(94)00054-E]
2. Liao Sh. Comparison between the homotopy analysis method and homotopy perturbation method. Applied Mathematics and Computation. 2005;169(2):1186-1194. [Link] [DOI:10.1016/j.amc.2004.10.058]
3. Motsa SS, Sibanda P, Shateyi S. A new spectral-homotopy analysis method for solving a nonlinear second order BVP. Communications in Nonlinear Science and Numerical Simulation. 2010;15(9):2293-2302. [Link] [DOI:10.1016/j.cnsns.2009.09.019]
4. Poorjamshidian M, Mahjoob Moghadas S, Mottalebi AA, Sheikhi J. Forced vibration analysis of a nonlinear marine riser using homotopy analysis method. Journal of Marine Engineering. 2014;10(19):67-74. [Persian] [Link]
5. Zamani E, Nazif HR. A novel semi analytical solution for the dynamic and heat transfer analysis of stagnation point flow using BK-HAM method. Modares Mechanical Engineering. 2017;17(3):270-280. [Persian] [Link]
6. Di Lizia P, Armellin R, Lavagna M. Application of high order expansions of two-point boundary value problems to astrodynamics. Celestial Mechanics and Dynamical Astronomy. 2008;102(4):355-375. [Link] [DOI:10.1007/s10569-008-9170-5]
7. Armellin R, Di Lizia P, Topputo F, Lavagna M, Bernelli-Zazzera F, Berz M. Gravity assist space pruning based on differential algebra. Celestial Mechanics and Dynamical Astronomy. 2010;106:1. [Link] [DOI:10.1007/s10569-009-9235-0]
8. Di Lizia P, Armellin R, Bernelli-Zazzera F, Berz M. High order optimal control of space trajectories with uncertain boundary conditions. Acta Astronautica. 2014;93:217-229. [Link] [DOI:10.1016/j.actaastro.2013.07.007]
9. Di Lizia P, Armellin R, Morselli A, Bernelli-Zazzera F. High order optimal feedback control of space trajectories with bounded control. Acta Astronautica. 2014;94(1):383-394. [Link] [DOI:10.1016/j.actaastro.2013.02.011]
10. Morselli A, Armellin R, De Lizia P, Bernelli-Zazzera F. A high order method for orbital conjunctions analysis: Monte Carlo collision probability computation. Advances in Space Research. 2015;55(1):311-333. [Link] [DOI:10.1016/j.asr.2014.09.003]
11. Witting A, Colombo C, Armellin R. Long-term density evolution through semi-analytical and differential algebra techniques. Celestial Mechanics and Dynamical Astronomy. 2017;128(4):435-452. [Link] [DOI:10.1007/s10569-017-9756-x]
12. Moghadasian M, Roshanian J. Continuous maneuver of unmanned aerial vehicle using high order expansions method for optimal control problem. Modares Mechanical Engineering. 2018;17(12):382-390. [Persian] [Link]
13. Moghadasian M, Roshanian J. Semi-feedback optimal control design for nonlinear problems. Optimal Control Applications and Methods. 2018;39(2):549-562. [Link] [DOI:10.1002/oca.2358]
14. Pierson BL, Chen I. Minimum landing-approach distance for a sailplane. Journal of Aircraft. 1979;16(4):287-288. [Link] [DOI:10.2514/3.58520]
15. Moghadasian M, Roshanian J. Approximately optimal manoeuvre strategy for aero-assisted space mission. Advances in Space Research. 2019;64(2):436-450. [Link] [DOI:10.1016/j.asr.2019.04.003]
16. Mason JC, Handscomb DC. Chebyshev Polynomials. 1st Edition. New York: CRC Press; 2002. pp. 237-267. [Link] [DOI:10.1201/9781420036114]

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