Entry Trajectory Optimization for Mars Science Laboratory Class Missions Using Indirect Unified Trigonometrization Method Article Swipe
Kshitij Mall
,
Ehsan Taheri
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1910.09438
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1910.09438
Application of traditional indirect optimization methods to optimal control problems (OCPs) with control and state path constraints is not a straightforward task. However, recent advances in regularization techniques and numerical continuation methods have enabled application of indirect methods to very complex OCPs. This study demonstrates the utility and application of an advanced indirect method, the Unified Trigonometrization Method (UTM), to a Mars Science Laboratory type entry problem. The objective is to maximize the parachute deployment altitude for a free-time, fixed-final-velocity entry trajectory. For entry vehicles, in addition to the bank angle that is characterized by bang-bang control profiles, there are typically three state path constraints that have to be considered, namely, the dynamic pressure, heat rate and g-load. This study shows that the UTM enables simultaneous regularization of the bang-bang control and satisfaction of the state path constraints. Two scenarios with and without state path constraints are considered. The results obtained using the UTM for both of these cases are found to be in excellent agreement with a direct optimization method. Furthermore, an interesting feature emerges in the optimal control profile of the UTM during the initial high-altitude part of the resulting optimal trajectory for the scenario with state path constraints, which has an appealing practical implication.
Related Topics
Concepts
Tikhonov regularization
Trajectory
Computer science
Trajectory optimization
Regularization (linguistics)
Control theory (sociology)
Mars Exploration Program
Optimal control
Path (computing)
Mathematical optimization
Control (management)
Mathematics
Artificial intelligence
Physics
Inverse problem
Astronomy
Mathematical analysis
Programming language
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1910.09438
- https://arxiv.org/pdf/1910.09438
- OA Status
- green
- References
- 25
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2981149667
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W2981149667Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1910.09438Digital Object Identifier
- Title
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Entry Trajectory Optimization for Mars Science Laboratory Class Missions Using Indirect Unified Trigonometrization MethodWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-10-21Full publication date if available
- Authors
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Kshitij Mall, Ehsan TaheriList of authors in order
- Landing page
-
https://arxiv.org/abs/1910.09438Publisher landing page
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https://arxiv.org/pdf/1910.09438Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/1910.09438Direct OA link when available
- Concepts
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Tikhonov regularization, Trajectory, Computer science, Trajectory optimization, Regularization (linguistics), Control theory (sociology), Mars Exploration Program, Optimal control, Path (computing), Mathematical optimization, Control (management), Mathematics, Artificial intelligence, Physics, Inverse problem, Astronomy, Mathematical analysis, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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| abstract_inverted_index.in | 25, 85, 163, 176 |
| abstract_inverted_index.is | 17, 69, 92 |
| abstract_inverted_index.of | 1, 35, 49, 127, 133, 156, 181, 189 |
| abstract_inverted_index.to | 6, 38, 59, 70, 87, 107, 161 |
| abstract_inverted_index.For | 82 |
| abstract_inverted_index.The | 67, 148 |
| abstract_inverted_index.Two | 138 |
| abstract_inverted_index.UTM | 123, 153, 183 |
| abstract_inverted_index.and | 13, 28, 47, 116, 131, 141 |
| abstract_inverted_index.are | 99, 146, 159 |
| abstract_inverted_index.for | 76, 154, 194 |
| abstract_inverted_index.has | 202 |
| abstract_inverted_index.not | 18 |
| abstract_inverted_index.the | 45, 54, 72, 88, 111, 122, 128, 134, 152, 177, 182, 185, 190, 195 |
| abstract_inverted_index.Mars | 61 |
| abstract_inverted_index.This | 42, 118 |
| abstract_inverted_index.bank | 89 |
| abstract_inverted_index.both | 155 |
| abstract_inverted_index.have | 32, 106 |
| abstract_inverted_index.heat | 114 |
| abstract_inverted_index.part | 188 |
| abstract_inverted_index.path | 15, 103, 136, 144, 199 |
| abstract_inverted_index.rate | 115 |
| abstract_inverted_index.that | 91, 105, 121 |
| abstract_inverted_index.type | 64 |
| abstract_inverted_index.very | 39 |
| abstract_inverted_index.with | 11, 140, 166, 197 |
| abstract_inverted_index.OCPs. | 41 |
| abstract_inverted_index.angle | 90 |
| abstract_inverted_index.cases | 158 |
| abstract_inverted_index.entry | 65, 80, 83 |
| abstract_inverted_index.found | 160 |
| abstract_inverted_index.shows | 120 |
| abstract_inverted_index.state | 14, 102, 135, 143, 198 |
| abstract_inverted_index.study | 43, 119 |
| abstract_inverted_index.task. | 21 |
| abstract_inverted_index.there | 98 |
| abstract_inverted_index.these | 157 |
| abstract_inverted_index.three | 101 |
| abstract_inverted_index.using | 151 |
| abstract_inverted_index.which | 201 |
| abstract_inverted_index.(OCPs) | 10 |
| abstract_inverted_index.(UTM), | 58 |
| abstract_inverted_index.Method | 57 |
| abstract_inverted_index.direct | 168 |
| abstract_inverted_index.during | 184 |
| abstract_inverted_index.recent | 23 |
| abstract_inverted_index.Science | 62 |
| abstract_inverted_index.Unified | 55 |
| abstract_inverted_index.complex | 40 |
| abstract_inverted_index.control | 8, 12, 96, 130, 179 |
| abstract_inverted_index.dynamic | 112 |
| abstract_inverted_index.emerges | 175 |
| abstract_inverted_index.enabled | 33 |
| abstract_inverted_index.enables | 124 |
| abstract_inverted_index.feature | 174 |
| abstract_inverted_index.g-load. | 117 |
| abstract_inverted_index.initial | 186 |
| abstract_inverted_index.method, | 53 |
| abstract_inverted_index.method. | 170 |
| abstract_inverted_index.methods | 5, 31, 37 |
| abstract_inverted_index.namely, | 110 |
| abstract_inverted_index.optimal | 7, 178, 192 |
| abstract_inverted_index.profile | 180 |
| abstract_inverted_index.results | 149 |
| abstract_inverted_index.utility | 46 |
| abstract_inverted_index.without | 142 |
| abstract_inverted_index.However, | 22 |
| abstract_inverted_index.addition | 86 |
| abstract_inverted_index.advanced | 51 |
| abstract_inverted_index.advances | 24 |
| abstract_inverted_index.altitude | 75 |
| abstract_inverted_index.indirect | 3, 36, 52 |
| abstract_inverted_index.maximize | 71 |
| abstract_inverted_index.obtained | 150 |
| abstract_inverted_index.problem. | 66 |
| abstract_inverted_index.problems | 9 |
| abstract_inverted_index.scenario | 196 |
| abstract_inverted_index.agreement | 165 |
| abstract_inverted_index.appealing | 204 |
| abstract_inverted_index.bang-bang | 95, 129 |
| abstract_inverted_index.excellent | 164 |
| abstract_inverted_index.numerical | 29 |
| abstract_inverted_index.objective | 68 |
| abstract_inverted_index.parachute | 73 |
| abstract_inverted_index.practical | 205 |
| abstract_inverted_index.pressure, | 113 |
| abstract_inverted_index.profiles, | 97 |
| abstract_inverted_index.resulting | 191 |
| abstract_inverted_index.scenarios | 139 |
| abstract_inverted_index.typically | 100 |
| abstract_inverted_index.vehicles, | 84 |
| abstract_inverted_index.Laboratory | 63 |
| abstract_inverted_index.deployment | 74 |
| abstract_inverted_index.free-time, | 78 |
| abstract_inverted_index.techniques | 27 |
| abstract_inverted_index.trajectory | 193 |
| abstract_inverted_index.Application | 0 |
| abstract_inverted_index.application | 34, 48 |
| abstract_inverted_index.considered, | 109 |
| abstract_inverted_index.considered. | 147 |
| abstract_inverted_index.constraints | 16, 104, 145 |
| abstract_inverted_index.interesting | 173 |
| abstract_inverted_index.traditional | 2 |
| abstract_inverted_index.trajectory. | 81 |
| abstract_inverted_index.Furthermore, | 171 |
| abstract_inverted_index.constraints, | 200 |
| abstract_inverted_index.constraints. | 137 |
| abstract_inverted_index.continuation | 30 |
| abstract_inverted_index.demonstrates | 44 |
| abstract_inverted_index.implication. | 206 |
| abstract_inverted_index.optimization | 4, 169 |
| abstract_inverted_index.satisfaction | 132 |
| abstract_inverted_index.simultaneous | 125 |
| abstract_inverted_index.characterized | 93 |
| abstract_inverted_index.high-altitude | 187 |
| abstract_inverted_index.regularization | 26, 126 |
| abstract_inverted_index.straightforward | 20 |
| abstract_inverted_index.Trigonometrization | 56 |
| abstract_inverted_index.fixed-final-velocity | 79 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile |