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Fuel Optimum Lunar Soft Landing Trajectory Design Using Different Solution Schemes


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DOI: https://doi.org/10.15866/irease.v9i5.10119

Abstract


The problem of soft landing on Moon is formulated and solved using different solution schemes. The solution scheme consists of one of the two approaches i) direct ii) indirect and one of different optimization techniques (viz. gradient based and gradient free techniques). Gradient free (Particle Swarm optimization and Differential Evolution) and gradient based optimization techniques are explored to solve the problem for direct and indirect approaches. In indirect approach, the optimal control problem is transformed into a two point boundary value problem (TPBVP) using Pontryagin’s minimum principle and the appropriate initial costates are selected using different optimization techniques. The performances of these optimization techniques are evaluated for the indirect approach for soft landing trajectory design problem. In direct approach, it is transformed into a non linear programming (NLP) problem and is solved by using an optimizer. The performance of the direct schemes is compared with indirect schemes. A scheme based on the indirect approach and differential evolution technique is evaluated superior to other options for the soft landing trajectory problem. Also the trajectory design is carried out with different constant thrust levels and their sensitivities are analyzed.
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Keywords


Lunar Soft Landing; Particle Swarm Optimization (PSO); Differential Evolution (DE); Non-Linear Programming (NLP); Two Point Boundary Value Problem (TPBVP); Optimal Control; Pontryagin’s Minimum Principle Etc.

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References


Klumpp, Allan R., Apollo Lunar-Descent Guidance. Charles Stark Draper Laboratory, R-695, June 1971.
http://dx.doi.org/10.1016/0005-1098(74)90019-3

R.V Ramanan and Madanlal, Analysis of optimal strategies for Soft landing on the Moon from Lunar Parking orbits,” Journal of Earth System Sciences, Vol. 114, No.6, p807-813.
http://dx.doi.org/10.1007/bf02715967

Anil V. Rao, A survey of numerical methods for optimal control, AAS 09-334, Astrodynamics 2009, Advances in the Astronautical Science, Vol 135 Part 1
http://dx.doi.org/10.2514/6.2016-5575

S Subchan, R Zikowski, Computational Optimal control, Tools and practice, John Wiley & Sons Ltd. 2009
http://dx.doi.org/10.1002/9780470747674

Joseph Z. Ben Asher, Optimal control theory with aerospace Applications, AIAA education series-2010
http://dx.doi.org/10.2514/4.867347

Kirk D E 1970, Optimal Control Theory: An Introduction. Prentice Hall
http://dx.doi.org/10.1002/aic.690170452

Oskar von Stryk. Numerical Solution of Optimal Control problem by Direct Collocation, Optimal Control theory and numerical methods, International series of Numerical Mathematics 111, 1993, 129-143
http://dx.doi.org/10.1007/978-3-0348-7539-4_10

Gerhard Venter, Particle Swarm optimization, AIAA JOURNAL Vol. 41, No. 8, August 2003
http://dx.doi.org/10.2514/2.2111

M. Pontani, B.A. Conway, Particle Swarm Optimization Applied to Space Trajectories, Journal of Guidance, Control & Dynamics, Vol.33, No.5, Sep-Oct 2010.
http://dx.doi.org/10.2514/1.48475

M. Pontani, P. Ghosh, B.A. Conway, Particle Swarm Optimization of Multiple-Burn Rendezvous Trajectories, Journal of Guidance, Control & Dynamics, Vol.35, No.4, July-Aug 2012.
http://dx.doi.org/10.2514/1.55592

Rhonald M. Jenkins & Roy J. Hartfield Jr. Hybrid Particle Swarm: Pattern Search Optimizer for Rocket Propulsion Applications, Journal of Space Crafts & Rockets, Vol. 49, No. 3, May–June 2012.
http://dx.doi.org/10.2514/1.58810

Rania Hassan, Babak Cohanim, Olivier de Weck, A comparison of Particle Swarm Optimization and Genetic algorithm, 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference Austin, Texas, AIAA 2005-1897.
http://dx.doi.org/10.2514/6.2005-1897

R. Storn, "On the usage of differential evolution for function optimization," Proceedings of North American Fuzzy Information Processing, Berkeley, CA, 1996, pp. 519-523.
http://dx.doi.org/10.1109/nafips.1996.534789

Aaron D Olds and Craig A Kluever & Michael Cupples, Interplanetary mission Design using Differential Evolution. Journal of Spacecraft & Rockets, Vol.44, No.5, Sept-Oct 2007.
http://dx.doi.org/10.2514/1.27242

M. Vasile and E. Minisci, Analysis of Some Global Optimization Algorithms for Space Trajectory Design. Journal of Space Crafts & Rockets, Vol. 47, No. 2, March–April 2010
http://dx.doi.org/10.2514/1.45742

M. Vasile and E. Minisci, M. Locatelliz, On Testing Global Optimization Algorithms for Space Trajectory Design, AIAA/AAS Astrodynamics Specialist Conference and Exhibit, Guidance, Navigation, and Control and Co-located Conferences , AIAA 2008-6277
http://dx.doi.org/10.2514/6.2008-6277

Qi Gong, F. Fahroo & I Michael Ross, Spectral Algorithm for Pseudospectral Methods in optimal Control, Journal of Guidance, Control and Dynamics, Vol.31, No 3, May-June 2008.
http://dx.doi.org/10.2514/1.32908

Alan W. Wilhite etal, Lunar Module Descent mission design, AIAA 2008-6939, AIAA/AAS Astrodynamics Specialist Conference and Exhibit 18 - 21 August 2008, Honolulu, Hawaii
http://dx.doi.org/10.2514/6.2008-6939

Bong-Gyun Park etal. Two-Dimensional Trajectory Optimization for Soft Lunar Landing Considering a landing site. Int’l J. of Aeronautical Space Sci. 12(3), 288-295(2011) The Korean Soceity for Aeronautical & Space Sciences.
http://dx.doi.org/10.5139/ijass.2011.12.3.288

Afshari, H., Rostamy, N., Nejad, I., Novinzadeh, A., Nonlinear Optimal Closed-Loop Guidance Law for Lunar Landing Mission Using Perturbation Feedback Control, (2015) International Review of Physics (IREPHY), 9 (1), pp. 22-29.

C. Bei, W. Zhang, A Guidance and Control Solution for Small Lunar Probe Precise Landing Mission, Acta Astronautica, 12, 047,(2006).
http://dx.doi.org/10.1016/j.actaastro.2006.12.047

C. N. Souza, An Optimal Guidance Law for Planetary Landing, The AIAA Guidance, Navigation, and Control Conference, New Orleanse.Proc.LA.(1997).
http://dx.doi.org/10.2514/6.1997-3709

A. B. Novinzadeh, S. H. Pourtakdoust, A Perturbation Approach in Determination of Closed-Loop Optimal-Fuzzy Control Policy for Lunar Landers, Japan Society for Aeronautical and Space Sciences and ISTS, d, 23, (2006).
http://dx.doi.org/10.1243/09544100jaero429

A. Naghash, R. Esmaelzadeh, M. Mortazavi, R. Jamilnia, Near Optimal Guidance Law for Descent to a Point Using Inverse Problem Approach, Aerospace Science and Technology, (2007).
http://dx.doi.org/10.1016/j.ast.2007.06.006

S. Suzuki, T. Yoshizawa, Near-Minimum Fuel Guidance Law of a Lunar Landing Module, IFAC Automatic Control in Aerospace, (1994).
http://dx.doi.org/10.2514/6.1999-3983

Mallikharjuna, K., Anuradha, K., An Efficient Method for Software Reliability Growth Model Selection Using Modified Particle Swarm Optimization Technique, (2015) International Review on Computers and Software (IRECOS), 10 (12), pp. 1169-1178.
http://dx.doi.org/10.15866/irecos.v10i12.8089

Gupta, R., Muttoo, S., Pal, S., Binary Division Fuzzy C-Means Clustering and Particle Swarm Optimization Based Efficient Intrusion Detection for E-Governance Systems, (2016) International Review on Computers and Software (IRECOS), 11 (8), pp. 672-681.
http://dx.doi.org/10.15866/irecos.v11i8.9546

Sundereswaran, K., Srinivasa Rao Nayak, P., Chandra Sekhar, A., Development of an Improved Particle Swarm Optimization (PSO) and its Application to Induction Motor Soft-Starting, (2014) International Review of Automatic Control (IREACO), 7 (2), pp. 156-165.

Ramya, S., Rajesh, N., Viswanathan, B., Vigneswari, B., Particle Swarm Optimization (PSO) based optimum Distributed Generation (DG) location and sizing for Voltage Stability and Loadability Enhancement in Radial Distribution System, (2014) International Review of Automatic Control (IREACO), 7 (3), pp. 288-293.

Syahputra, R., Robandi, I., Ashari, M., Performance Improvement of Radial Distribution Network with Distributed Generation Integration Using Extended Particle Swarm Optimization Algorithm, (2015) International Review of Electrical Engineering (IREE), 10 (2), pp. 293-304.
http://dx.doi.org/10.15866/iree.v10i2.5410

Muthukumar, K., Jayalalitha, S., Ramaswamy, M., PSO Embedded Artificial Bee Colony Algorithm for Optimal Shunt Capacitor Allocation and Sizing in Radial Distribution Networks with Voltage Dependent Load Models, (2015) International Review of Electrical Engineering (IREE), 10 (2), pp. 305-320.
http://dx.doi.org/10.15866/iree.v10i2.5481

El-Arini, M., Othman, A., Othman, A., Said, T., Said, T., Particle Swarm Optimization and Genetic Algorithm for Convex and Non-convex Economic Dispatch, (2014) International Review of Electrical Engineering (IREE), 9 (1), pp. 127-135.

Dharmaraj, K., G., R., Optimal Reactive Power Dispatch of Power System using Improved Harmony Search Algorithm, (2014) International Review of Electrical Engineering (IREE), 9 (3), pp. 620-628.

Thanga Parvathi, B., MercyShalinie, S., Differential Evolution (DE) based Multiple Regression Model for Classification, (2014) International Review on Computers and Software (IRECOS), 9 (6), pp. 1117-1124.

Godwin Raja Ebenezer, N., Saravanan, R., Ramabalan, S., Natarajan, R., Evolutionary Optimum Design for a Task Specified 6-Link Planar Robot, (2014) International Review of Mechanical Engineering (IREME), 8 (1), pp. 36-51.
http://dx.doi.org/10.15866/ireme.v8i1.1179


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