Keyword search (4,163 papers available)

"uncertainty" Keyword-tagged Publications:

Title Authors PubMed ID
1 Adaptive sliding mode fault-tolerant control of an over-actuated hybrid VTOL fixed-wing UAV under transition flight Wang B; Zhao H; Hu X; Shen Y; Li N; 41475926
ENCS
2 Intolerance of uncertainty, psychological symptoms, and pain in long-term childhood cancer survivors: a report from the Childhood Cancer Survivor Study Alberts NM; Stratton KL; Leisenring WM; Pizzo A; Lamoureux É; Alschuler K; Flynn J; Krull KR; Jibb LA; Nathan PC; Olgin JE; Stinson JN; Armstrong GT; 40699439
PSYCHOLOGY
3 Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks Adcock B; Brugiapaglia S; Dexter N; Moraga S; 39454372
MATHSTATS
4 Exploring the effects of anthropogenic disturbance on predator inspection activity in Trinidadian guppies Brusseau AJP; Feyten LEA; Crane AL; Brown GE; 38476138
BIOLOGY
5 Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration Hou D; Zhan D; Wang L; Hassan IG; Sezer N; 37936825
ENCS
6 How uncertainty affects information search among consumers: a curvilinear perspective He S; Rucker DD; 36471868
JMSB
7 UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection Abdar M; Salari S; Qahremani S; Lam HK; Karray F; Hussain S; Khosravi A; Acharya UR; Makarenkov V; Nahavandi S; 36217534
ENCS
8 Development of a DREAM-based inverse model for multi-point source identification in river pollution incidents: Model testing and uncertainty analysis Zhu Y; Chen Z; 36191500
ENCS
9 Viral Anxiety Mediates the Influence of Intolerance of Uncertainty on Adherence to Physical Distancing Among Healthcare Workers in COVID-19 Pandemic Chung S; Lee T; Hong Y; Ahmed O; Silva WAD; Gouin JP; 35733798
PSYCHOLOGY
10 Decision-first modeling should guide decision making for emerging risks Morgan K; Collier ZA; Gilmore E; Schmitt K; 35104915
ENCS
11 Towards a better understanding of deep convolutional neural network processes for recognizing organic chemicals of environmental concern Sun X; Zhang X; Wang L; Li Y; Muir DCG; Zeng EY; 34388923
CHEMBIOCHEM
12 Assessing the regional biogenic methanol emission from spring wheat during the growing season: A Canadian case study Cai M; An C; Guy C; Lu C; Mafakheri F; 34182392
ENCS
13 A robust optimization model for tactical capacity planning in an outpatient setting Aslani N; Kuzgunkaya O; Vidyarthi N; Terekhov D; 33215335
ENCS
14 Qualitative threshold method validation and uncertainty evaluation: A theoretical framework and application to a 40 analytes liquid chromatography-tandem mass spectrometry method Camirand Lemyre F; Desharnais B; Laquerre J; Morel MA; Côté C; Mireault P; Skinner CD; 32476284
CHEMBIOCHEM
15 Quantifying construction waste reduction through the application of prefabrication: a case study in Anhui, China. Hao J, Chen Z, Zhang Z, Loehlein G 32358748
ENCS
16 An ecological framework of neophobia: from cells to organisms to populations. Crane AL, Brown GE, Chivers DP, Ferrari MCO 31599483
BIOLOGY
17 Worldwide contamination of food-crops with mycotoxins: Validity of the widely cited 'FAO estimate' of 25. Eskola M, Kos G, Elliott CT, Hajšlová J, Mayar S, Krska R 31478403
CHEMBIOCHEM
18 Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction. Vorwerk J, Aydin Ü, Wolters CH, Butson CR 31231178
PERFORM

 

Title:Adaptive sliding mode fault-tolerant control of an over-actuated hybrid VTOL fixed-wing UAV under transition flight
Authors:Wang BZhao HHu XShen YLi N
Link:https://pubmed.ncbi.nlm.nih.gov/41475926/
DOI:10.1016/j.isatra.2025.12.046
Publication:ISA transactions
Keywords:Actuator faultAdaptive sliding mode controlFault-tolerant controlModel uncertaintyOver-actuated VTOL UAV
PMID:41475926 Category: Date Added:2026-01-01
Dept Affiliation: ENCS
1 School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China; National Key Laboratory of Aircraft Configuration Design, Xi'an 710072, China. Electronic address: wangban@nwpu.edu.cn.
2 School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China; National Key Laboratory of Aircraft Configuration Design, Xi'an 710072, China. Electronic address: huiminzhao@mail.nwpu.edu.cn.
3 School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China; National Key Laboratory of Aircraft Configuration Design, Xi'an 710072, China. Electronic address: xinyuehu@mail.nwpu.edu.cn.
4 Department of Electrical and Computer Engineering, Concordia University, Montreal H3G 1M8, Canada. Electronic address: y_shen@encs.concordia.ca.
5 School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China; National Key Laboratory of Aircraft Configuration Design, Xi'an 710072, China. Electronic address: lini@nwpu.edu.cn.

Description:

In this study, an innovative adaptive sliding mode fault-tolerant control approach is developed for an over-actuated vertical takeoff and landing (VTOL) fixed-wing unmanned aerial vehicle (UAV) with the capability to suppress overestimation of adaptive parameters. This method is designed to effectively address model uncertainties and actuator faults without relying on any previous information regarding the specifics of faults or the boundaries of uncertainties. An innovative adaptive sliding mode control (SMC) mechanism is designed which can autonomously adjust to compensate for the unpredictable nature of these challenges, ensuring the stability and reliability of the UAV system under various operational conditions. Taking into account the over-actuated characteristics of the studied VTOL UAV, a control allocation module is further designed to efficiently distribute the control signals produced by the adaptive SMC scheme. It is noteworthy that the designed adaptive control approach can effectively prevent the overestimation of adaptive parameters, thereby reducing the occurrence of undesired control chattering. Finally, the superiority and efficacy of the designed control technique are convincingly illustrated through an extensive range of comparative hardware-in-the-loop simulation tests.





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