Robust regret optimal control Article Swipe
Summary This paper presents a synthesis method for robust, regret optimal control. The plant is modeled in discrete‐time by an uncertain linear time‐invariant (LTI) system. An optimal non‐causal controller is constructed using the nominal plant model and given full knowledge of the disturbance. Robust regret is defined relative to the performance of this optimal non‐causal control. It is shown that a controller achieves robust regret if and only if it satisfies a robust performance condition. DK‐iteration can be used to synthesize a controller that satisfies this condition and hence achieve a given level of robust regret. The approach is demonstrated two examples: (i) a single‐input, single‐output (SISO) classical design, and (ii) an active suspension for a quarter car model. The SISO example is simple but is intended to provide insight about the robust regret control design. The quarter car example compares the robust regret controllers against regret controllers designed without plant uncertainty.
Related Topics
Concepts
Regret
Control theory (sociology)
Robust control
Controller (irrigation)
Computer science
Optimal control
Mathematical optimization
Robustness (evolution)
Control (management)
Mathematics
Engineering
Control system
Artificial intelligence
Gene
Electrical engineering
Chemistry
Machine learning
Biochemistry
Agronomy
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/rnc.7209
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/rnc.7209
- OA Status
- hybrid
- Cited By
- 4
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390765621
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4390765621Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/rnc.7209Digital Object Identifier
- Title
-
Robust regret optimal controlWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-11Full publication date if available
- Authors
-
Jingping Liu, Peter SeilerList of authors in order
- Landing page
-
https://doi.org/10.1002/rnc.7209Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/rnc.7209Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/rnc.7209Direct OA link when available
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Regret, Control theory (sociology), Robust control, Controller (irrigation), Computer science, Optimal control, Mathematical optimization, Robustness (evolution), Control (management), Mathematics, Engineering, Control system, Artificial intelligence, Gene, Electrical engineering, Chemistry, Machine learning, Biochemistry, Agronomy, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 3Per-year citation counts (last 5 years)
- References (count)
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28Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.can | 76 |
| abstract_inverted_index.car | 117, 138 |
| abstract_inverted_index.for | 7, 114 |
| abstract_inverted_index.the | 32, 41, 49, 131, 141 |
| abstract_inverted_index.two | 100 |
| abstract_inverted_index.(ii) | 110 |
| abstract_inverted_index.SISO | 120 |
| abstract_inverted_index.This | 1 |
| abstract_inverted_index.full | 38 |
| abstract_inverted_index.only | 67 |
| abstract_inverted_index.that | 59, 83 |
| abstract_inverted_index.this | 52, 85 |
| abstract_inverted_index.used | 78 |
| abstract_inverted_index.(LTI) | 23 |
| abstract_inverted_index.about | 130 |
| abstract_inverted_index.given | 37, 91 |
| abstract_inverted_index.hence | 88 |
| abstract_inverted_index.level | 92 |
| abstract_inverted_index.model | 35 |
| abstract_inverted_index.paper | 2 |
| abstract_inverted_index.plant | 13, 34, 150 |
| abstract_inverted_index.shown | 58 |
| abstract_inverted_index.using | 31 |
| abstract_inverted_index.(SISO) | 106 |
| abstract_inverted_index.Robust | 43 |
| abstract_inverted_index.active | 112 |
| abstract_inverted_index.linear | 21 |
| abstract_inverted_index.method | 6 |
| abstract_inverted_index.model. | 118 |
| abstract_inverted_index.regret | 9, 44, 64, 133, 143, 146 |
| abstract_inverted_index.robust | 63, 72, 94, 132, 142 |
| abstract_inverted_index.simple | 123 |
| abstract_inverted_index.Summary | 0 |
| abstract_inverted_index.achieve | 89 |
| abstract_inverted_index.against | 145 |
| abstract_inverted_index.control | 134 |
| abstract_inverted_index.defined | 46 |
| abstract_inverted_index.design, | 108 |
| abstract_inverted_index.design. | 135 |
| abstract_inverted_index.example | 121, 139 |
| abstract_inverted_index.insight | 129 |
| abstract_inverted_index.modeled | 15 |
| abstract_inverted_index.nominal | 33 |
| abstract_inverted_index.optimal | 10, 26, 53 |
| abstract_inverted_index.provide | 128 |
| abstract_inverted_index.quarter | 116, 137 |
| abstract_inverted_index.regret. | 95 |
| abstract_inverted_index.robust, | 8 |
| abstract_inverted_index.system. | 24 |
| abstract_inverted_index.without | 149 |
| abstract_inverted_index.achieves | 62 |
| abstract_inverted_index.approach | 97 |
| abstract_inverted_index.compares | 140 |
| abstract_inverted_index.control. | 11, 55 |
| abstract_inverted_index.designed | 148 |
| abstract_inverted_index.intended | 126 |
| abstract_inverted_index.presents | 3 |
| abstract_inverted_index.relative | 47 |
| abstract_inverted_index.classical | 107 |
| abstract_inverted_index.condition | 86 |
| abstract_inverted_index.examples: | 101 |
| abstract_inverted_index.knowledge | 39 |
| abstract_inverted_index.satisfies | 70, 84 |
| abstract_inverted_index.synthesis | 5 |
| abstract_inverted_index.uncertain | 20 |
| abstract_inverted_index.condition. | 74 |
| abstract_inverted_index.controller | 28, 61, 82 |
| abstract_inverted_index.suspension | 113 |
| abstract_inverted_index.synthesize | 80 |
| abstract_inverted_index.constructed | 30 |
| abstract_inverted_index.controllers | 144, 147 |
| abstract_inverted_index.performance | 50, 73 |
| abstract_inverted_index.demonstrated | 99 |
| abstract_inverted_index.disturbance. | 42 |
| abstract_inverted_index.non‐causal | 27, 54 |
| abstract_inverted_index.uncertainty. | 151 |
| abstract_inverted_index.DK‐iteration | 75 |
| abstract_inverted_index.discrete‐time | 17 |
| abstract_inverted_index.single‐input, | 104 |
| abstract_inverted_index.single‐output | 105 |
| abstract_inverted_index.time‐invariant | 22 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5009028512 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I27837315 |
| citation_normalized_percentile.value | 0.83559892 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |