Model Reduction and Chattering Mitigation in Multi-Model Predictive Control for Quadrotor UAVs Article Swipe
Ghulam E Mustafa Abro
,
Sufyan Ali Memon
,
Saddaf Rubab
,
Kaznah Alshammari
,
Faheem Khan
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/access.2025.3576178
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1109/access.2025.3576178
This study introduces a multi-model predictive control (MMPC) framework for quadrotor attitude regulation, combining the high-precision capabilities of nonlinear model predictive control (NMPC) with the computing efficiency of linear model predictive control (LMPC). Although NMPC provides excellent regulation, its substantial computational expense restricts its real-time use in high-refresh-rate applications like attitude control. In contrast, LMPC exhibits computational efficiency but encounters challenges with stability and precision in nonlinear dynamics. In order to resolve this discrepancy, we propose a Multi-Model Predictive Control (MMPC) approach that integrates Principal Component Analysis (PCA) for model reduction and employs linear quadrotor attitude models. This approach reduces the computational complexity and the number of necessary Linear Model Predictive Controllers (LMPCs). To improve performance, we implement an adaptive gain scheduling algorithm to mitigate the chattering effect frequently seen in multi-model approaches. This seamless switching technique diminishes high-frequency noise in brushless DC motor operation, minimises peak overshoot, and mitigates actuator wear, thereby enhancing system stability and durability. Comparative assessments indicate that the suggested MMPC framework attains NMPC-equivalent performance while incurring LMPC-level computational expenses, exceeding the efficacy of conventional incremental nonlinear dynamic inversion, sliding mode control, and traditional NMPC and LMPC methodologies. This study offers a computationally efficient and stable control solution for real-time UAV applications, including model reduction, chattering mitigation, and predictive control optimisation for autonomous aerial systems.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2025.3576178
- OA Status
- gold
- References
- 27
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4410985752Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2025.3576178Digital Object Identifier
- Title
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Model Reduction and Chattering Mitigation in Multi-Model Predictive Control for Quadrotor UAVsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-01Full publication date if available
- Authors
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Ghulam E Mustafa Abro, Sufyan Ali Memon, Saddaf Rubab, Kaznah Alshammari, Faheem KhanList of authors in order
- Landing page
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https://doi.org/10.1109/access.2025.3576178Publisher landing page
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1109/access.2025.3576178Direct OA link when available
- Concepts
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Reduction (mathematics), Model predictive control, Computer science, Control (management), Control theory (sociology), Remotely operated underwater vehicle, Control engineering, Engineering, Artificial intelligence, Mobile robot, Robot, Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W1973734421, https://openalex.org/W4405786388, https://openalex.org/W2059493488, https://openalex.org/W2035734362, https://openalex.org/W4409830312, https://openalex.org/W3197225143, https://openalex.org/W4213414279, https://openalex.org/W1919002818, https://openalex.org/W3123524846, https://openalex.org/W4236381219, https://openalex.org/W3114622139, https://openalex.org/W3110904289, https://openalex.org/W4317376674, https://openalex.org/W4391507006, https://openalex.org/W4392221607, https://openalex.org/W2152982646, https://openalex.org/W4210283550, https://openalex.org/W2898391506, https://openalex.org/W4366779169, https://openalex.org/W2022312987, https://openalex.org/W2410081681, https://openalex.org/W2793261119, https://openalex.org/W2001208849, https://openalex.org/W4408861872, https://openalex.org/W4384828729, https://openalex.org/W1986814071, https://openalex.org/W4405166114 |
| referenced_works_count | 27 |
| abstract_inverted_index.a | 3, 76, 195 |
| abstract_inverted_index.DC | 142 |
| abstract_inverted_index.In | 52, 68 |
| abstract_inverted_index.To | 113 |
| abstract_inverted_index.an | 118 |
| abstract_inverted_index.in | 46, 65, 130, 140 |
| abstract_inverted_index.of | 17, 27, 106, 177 |
| abstract_inverted_index.to | 70, 123 |
| abstract_inverted_index.we | 74, 116 |
| abstract_inverted_index.UAV | 204 |
| abstract_inverted_index.and | 63, 91, 103, 148, 156, 186, 189, 198, 211 |
| abstract_inverted_index.but | 58 |
| abstract_inverted_index.for | 9, 88, 202, 215 |
| abstract_inverted_index.its | 38, 43 |
| abstract_inverted_index.the | 14, 24, 100, 104, 125, 162, 175 |
| abstract_inverted_index.use | 45 |
| abstract_inverted_index.LMPC | 54, 190 |
| abstract_inverted_index.MMPC | 164 |
| abstract_inverted_index.NMPC | 34, 188 |
| abstract_inverted_index.This | 0, 97, 133, 192 |
| abstract_inverted_index.gain | 120 |
| abstract_inverted_index.like | 49 |
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| abstract_inverted_index.peak | 146 |
| abstract_inverted_index.seen | 129 |
| abstract_inverted_index.that | 82, 161 |
| abstract_inverted_index.this | 72 |
| abstract_inverted_index.with | 23, 61 |
| abstract_inverted_index.(PCA) | 87 |
| abstract_inverted_index.Model | 109 |
| abstract_inverted_index.model | 19, 29, 89, 207 |
| abstract_inverted_index.motor | 143 |
| abstract_inverted_index.noise | 139 |
| abstract_inverted_index.order | 69 |
| abstract_inverted_index.study | 1, 193 |
| abstract_inverted_index.wear, | 151 |
| abstract_inverted_index.while | 169 |
| abstract_inverted_index.(MMPC) | 7, 80 |
| abstract_inverted_index.(NMPC) | 22 |
| abstract_inverted_index.Linear | 108 |
| abstract_inverted_index.aerial | 217 |
| abstract_inverted_index.effect | 127 |
| abstract_inverted_index.linear | 28, 93 |
| abstract_inverted_index.number | 105 |
| abstract_inverted_index.offers | 194 |
| abstract_inverted_index.stable | 199 |
| abstract_inverted_index.system | 154 |
| abstract_inverted_index.(LMPC). | 32 |
| abstract_inverted_index.Control | 79 |
| abstract_inverted_index.attains | 166 |
| abstract_inverted_index.control | 6, 21, 31, 200, 213 |
| abstract_inverted_index.dynamic | 181 |
| abstract_inverted_index.employs | 92 |
| abstract_inverted_index.expense | 41 |
| abstract_inverted_index.improve | 114 |
| abstract_inverted_index.models. | 96 |
| abstract_inverted_index.propose | 75 |
| abstract_inverted_index.reduces | 99 |
| abstract_inverted_index.resolve | 71 |
| abstract_inverted_index.sliding | 183 |
| abstract_inverted_index.thereby | 152 |
| abstract_inverted_index.(LMPCs). | 112 |
| abstract_inverted_index.Although | 33 |
| abstract_inverted_index.Analysis | 86 |
| abstract_inverted_index.actuator | 150 |
| abstract_inverted_index.adaptive | 119 |
| abstract_inverted_index.approach | 81, 98 |
| abstract_inverted_index.attitude | 11, 50, 95 |
| abstract_inverted_index.control, | 185 |
| abstract_inverted_index.control. | 51 |
| abstract_inverted_index.efficacy | 176 |
| abstract_inverted_index.exhibits | 55 |
| abstract_inverted_index.indicate | 160 |
| abstract_inverted_index.mitigate | 124 |
| abstract_inverted_index.provides | 35 |
| abstract_inverted_index.seamless | 134 |
| abstract_inverted_index.solution | 201 |
| abstract_inverted_index.systems. | 218 |
| abstract_inverted_index.Component | 85 |
| abstract_inverted_index.Principal | 84 |
| abstract_inverted_index.algorithm | 122 |
| abstract_inverted_index.brushless | 141 |
| abstract_inverted_index.combining | 13 |
| abstract_inverted_index.computing | 25 |
| abstract_inverted_index.contrast, | 53 |
| abstract_inverted_index.dynamics. | 67 |
| abstract_inverted_index.efficient | 197 |
| abstract_inverted_index.enhancing | 153 |
| abstract_inverted_index.exceeding | 174 |
| abstract_inverted_index.excellent | 36 |
| abstract_inverted_index.expenses, | 173 |
| abstract_inverted_index.framework | 8, 165 |
| abstract_inverted_index.implement | 117 |
| abstract_inverted_index.including | 206 |
| abstract_inverted_index.incurring | 170 |
| abstract_inverted_index.minimises | 145 |
| abstract_inverted_index.mitigates | 149 |
| abstract_inverted_index.necessary | 107 |
| abstract_inverted_index.nonlinear | 18, 66, 180 |
| abstract_inverted_index.precision | 64 |
| abstract_inverted_index.quadrotor | 10, 94 |
| abstract_inverted_index.real-time | 44, 203 |
| abstract_inverted_index.reduction | 90 |
| abstract_inverted_index.restricts | 42 |
| abstract_inverted_index.stability | 62, 155 |
| abstract_inverted_index.suggested | 163 |
| abstract_inverted_index.switching | 135 |
| abstract_inverted_index.technique | 136 |
| abstract_inverted_index.LMPC-level | 171 |
| abstract_inverted_index.Predictive | 78, 110 |
| abstract_inverted_index.autonomous | 216 |
| abstract_inverted_index.challenges | 60 |
| abstract_inverted_index.chattering | 126, 209 |
| abstract_inverted_index.complexity | 102 |
| abstract_inverted_index.diminishes | 137 |
| abstract_inverted_index.efficiency | 26, 57 |
| abstract_inverted_index.encounters | 59 |
| abstract_inverted_index.frequently | 128 |
| abstract_inverted_index.integrates | 83 |
| abstract_inverted_index.introduces | 2 |
| abstract_inverted_index.inversion, | 182 |
| abstract_inverted_index.operation, | 144 |
| abstract_inverted_index.overshoot, | 147 |
| abstract_inverted_index.predictive | 5, 20, 30, 212 |
| abstract_inverted_index.reduction, | 208 |
| abstract_inverted_index.scheduling | 121 |
| abstract_inverted_index.Comparative | 158 |
| abstract_inverted_index.Controllers | 111 |
| abstract_inverted_index.Multi-Model | 77 |
| abstract_inverted_index.approaches. | 132 |
| abstract_inverted_index.assessments | 159 |
| abstract_inverted_index.durability. | 157 |
| abstract_inverted_index.incremental | 179 |
| abstract_inverted_index.mitigation, | 210 |
| abstract_inverted_index.multi-model | 4, 131 |
| abstract_inverted_index.performance | 168 |
| abstract_inverted_index.regulation, | 12, 37 |
| abstract_inverted_index.substantial | 39 |
| abstract_inverted_index.traditional | 187 |
| abstract_inverted_index.applications | 48 |
| abstract_inverted_index.capabilities | 16 |
| abstract_inverted_index.conventional | 178 |
| abstract_inverted_index.discrepancy, | 73 |
| abstract_inverted_index.optimisation | 214 |
| abstract_inverted_index.performance, | 115 |
| abstract_inverted_index.applications, | 205 |
| abstract_inverted_index.computational | 40, 56, 101, 172 |
| abstract_inverted_index.high-frequency | 138 |
| abstract_inverted_index.high-precision | 15 |
| abstract_inverted_index.methodologies. | 191 |
| abstract_inverted_index.NMPC-equivalent | 167 |
| abstract_inverted_index.computationally | 196 |
| abstract_inverted_index.high-refresh-rate | 47 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/13 |
| sustainable_development_goals[0].score | 0.8100000023841858 |
| sustainable_development_goals[0].display_name | Climate action |
| citation_normalized_percentile.value | 0.24213811 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |