Comparing and analyzing min-time and min-effort criteria for free true anomaly of low-thrust orbital maneuvers with new optimal control algorithm
This research presents a new algorithm for solving optimal control problems with regard to path planning with a free initial condition. To conduct research in this subject, issues such as optimal control theory, orthogonal functions in the Hilbert space, and the evolutionary optimizations such as Ge...
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| Published in | Aerospace science and technology Vol. 35; pp. 116 - 134 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Issy-les-Moulineaux
Elsevier Masson SAS
01.05.2014
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1270-9638 1626-3219 |
| DOI | 10.1016/j.ast.2014.03.009 |
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| Abstract | This research presents a new algorithm for solving optimal control problems with regard to path planning with a free initial condition. To conduct research in this subject, issues such as optimal control theory, orthogonal functions in the Hilbert space, and the evolutionary optimizations such as Genetic algorithm (GA), Particle swarm optimization (PSO), Genetic algorithm-Particle swarm optimization (GA-PSO) and Imperial competition algorithm (ICA) are utilized. The algorithm is proposed for low-thrust orbital transfer problems, which include nonlinear dynamic equations. To validate the algorithm, Edelbaum low-thrust equations are compared with proposed analytical solutions. Afterwards, the algorithm is investigated for low-thrust orbital transfers concerning equinoctial equations of the min-time and min-effort problems and compared with pseudo-spectral method. Also two performance indices are compared from the viewpoint of space mission analysis and design. In addition, to obtain the best point for starting maneuvers, initial condition of true anomaly is considered to be free. Once the orbital transfer problem is solved, the fuzzy decision maker has to choose the best configuration among the free true anomaly solutions and performance indices to upgrade the proposed algorithm. This configuration balanced two performance indices by considering free true anomaly. As a result, this novel algorithm is able to overcome difficulties of optimal control problems using the global optimization and multi combination performance indices. Another innovation of this new method in the field of optimal control theory is to set initial conditions with more than one performance criterion free. |
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| AbstractList | This research presents a new algorithm for solving optimal control problems with regard to path planning with a free initial condition. To conduct research in this subject, issues such as optimal control theory, orthogonal functions in the Hilbert space, and the evolutionary optimizations such as Genetic algorithm (GA), Particle swarm optimization (PSO), Genetic algorithm-Particle swarm optimization (GA-PSO) and Imperial competition algorithm (ICA) are utilized. The algorithm is proposed for low-thrust orbital transfer problems, which include nonlinear dynamic equations. To validate the algorithm, Edelbaum low-thrust equations are compared with proposed analytical solutions. Afterwards, the algorithm is investigated for low-thrust orbital transfers concerning equinoctial equations of the min-time and min-effort problems and compared with pseudo-spectral method. Also two performance indices are compared from the viewpoint of space mission analysis and design. In addition, to obtain the best point for starting maneuvers, initial condition of true anomaly is considered to be free. Once the orbital transfer problem is solved, the fuzzy decision maker has to choose the best configuration among the free true anomaly solutions and performance indices to upgrade the proposed algorithm. This configuration balanced two performance indices by considering free true anomaly. As a result, this novel algorithm is able to overcome difficulties of optimal control problems using the global optimization and multi combination performance indices. Another innovation of this new method in the field of optimal control theory is to set initial conditions with more than one performance criterion free. |
| Author | Novinzadeh, A.B. Shafieenejad, I. Molazadeh, V.R. |
| Author_xml | – sequence: 1 givenname: I. surname: Shafieenejad fullname: Shafieenejad, I. email: shafiee_iman@yahoo.com – sequence: 2 givenname: A.B. surname: Novinzadeh fullname: Novinzadeh, A.B. – sequence: 3 givenname: V.R. surname: Molazadeh fullname: Molazadeh, V.R. |
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| CitedBy_id | crossref_primary_10_1590_jatm_v15_1307 crossref_primary_10_1007_s42405_024_00740_6 crossref_primary_10_1177_0954410015579473 crossref_primary_10_1007_s40435_022_01033_0 crossref_primary_10_1016_j_isatra_2016_01_012 crossref_primary_10_1016_j_actaastro_2021_06_046 crossref_primary_10_1017_aer_2022_102 crossref_primary_10_1080_0305215X_2015_1115026 crossref_primary_10_1016_j_paerosci_2018_07_007 |
| Cites_doi | 10.1016/j.actaastro.2009.05.013 10.1016/j.eswa.2010.04.081 10.2514/1.37675 10.2514/1.48475 10.2514/1.4022 10.2514/1.55795 10.2514/2.4145 10.1016/j.patrec.2009.12.005 10.1016/j.actaastro.2011.08.008 10.1016/j.enconman.2010.01.014 10.1016/j.ast.2012.02.016 10.2514/1.28694 10.1016/j.actaastro.2004.05.035 10.1016/j.ast.2010.07.006 10.1002/oca.957 10.2514/1.30833 10.1016/j.ast.2010.10.004 10.2514/1.3409 10.1016/j.ast.2012.02.021 10.2514/1.54101 10.2514/1.3042 10.1016/j.actaastro.2009.08.020 10.1007/s10569-011-9360-4 10.2514/1.22984 10.2514/1.40619 10.1016/j.compstruc.2010.06.011 10.1016/j.actaastro.2011.09.007 10.1016/j.mcm.2013.06.014 10.2514/1.51024 10.2514/1.44885 10.2514/1.52136 10.1016/j.ast.2012.02.017 10.2514/1.32220 |
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| Keywords | Orbital transfer Fuzzy logic Optimal control theory Evolutionary optimizations Orthogonal functions Low-thruster Space application Competition Evolutionary algorithm Control program Control synthesis Transfer orbit Modeling Innovation Anomaly Hilbert space Swarm intelligence Initial condition Optimal algorithm Decision making Independent component analysis Spacecraft Path planning Particle swarm optimization Celestial mechanics Genetic algorithm Orthogonal function Optimal control Optimal trajectory Fuzzy decision Non linear effect Thrust |
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| SubjectTerms | Applied sciences Computer science; control theory; systems Control system synthesis Control theory. Systems Evolutionary optimizations Exact sciences and technology Fundamental areas of phenomenology (including applications) Fuzzy logic Low-thruster Optimal control Optimal control theory Orbital transfer Orthogonal functions Physics Solid dynamics (ballistics, collision, multibody system, stabilization...) Solid mechanics System theory |
| Title | Comparing and analyzing min-time and min-effort criteria for free true anomaly of low-thrust orbital maneuvers with new optimal control algorithm |
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