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Supervised Model Predictive Control for Discrete-time Nonlinear Systems with Time-varying Delay
2015
International Journal of Computer Applications
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The present paper deals with a decoupled multimodel predictive control based on multi-observer for the control of discrete-time nonlinear systems with time-varying delay. ...
For each local model, a controller based on partial predictor/observer is synthesized. ...
Supervised decoupled multimodel predictive control based on multi-observer. ( ) d y k ( ) c y k ( ) m y k ˆ( ) i x k ˆ( ) i x k ( ) y k ( ) u k ( ) i u k Decoupled Supervisor 1 ( 1) ( ) ( ) ( ) ( ( ( ) ...
doi:10.5120/20027-1547
fatcat:6uk6wjpulnajbozfwvhxcvmtpq
Systematic uncertainty reduction strategies for developing streamflow forecasts utilizing multiple climate models and hydrologic models
2014
Water Resources Research
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The findings are also consistent on application to a real watershed, Tar River at Tarboro, for which the ability to predict the observed streamflow is evaluated by developing multimodel streamflow forecasts ...
based on both strategies based on five climate models, two stochastic streamflow models and one water balance model. ...
Thus, the noise term, ε m , controls the correlation between the observed precipitation (P) and the issued forecast over the period . ...
doi:10.1002/2013wr013855
fatcat:46ppyvhinvfihjcbbajwm7a74q
A Sliding Mode-Multimodel Control with Sliding Mode Observer for a Sensorless Pumping System
[article]
2013
arXiv
pre-print
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2013 pre-print arXiv:1301.2714v3 fatcat:dcaxop6i2nfk3obfedesu4wlfiOther Versions
This work deals with the design of a sliding mode observer with a multi-surfaces sliding mode multimodel control (SM-MMC) for a mechanical sensorless pumping system. ...
Robustness tests validated by simulation show the effectiveness of the sliding mode observer associated with this control approach (SM-MMC). ...
Figure 1 1 The
Figure 2 2 Sliding mode multimodel control structureSliding Mode-Multimodel Approach page 7
Figure. 3 3 simulation result of the sliding mode observer
table 1 . 1 Tab 1 Experimental ...
arXiv:1301.2714v4
fatcat:5cqyaryuvvbmnfm3qrhoc2jhzi
Improved Medium- and Long-Term Runoff Forecasting Using a Multimodel Approach in the Yellow River Headwaters Region Based on Large-Scale and Local-Scale Climate Information
2017
Water
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Next, a Bayesian model averaging (BMA)-based multimodel was developed using weighted MLR, RBFNN, and SVR models, and the performance of the BMA-based multimodel was compared to those of the MLR, RBFNN, ...
The BMA-based multimodel performed better than those of the other models, as well as high-runoff forecasting. ...
Figure 5 . 5 BMA-based multimodel runoff forecasting and 90% confidence interval compared to observations. ...
doi:10.3390/w9080608
fatcat:pzgktaim25e6rc6cwi4c2kbw6u
Multimodel Control Design Using Unsupervised Classifiers
2012
Studies in Informatics and Control
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Multimodel approaches derive a smooth control law from the blending of local controllers using the concept of validities and domain overlapping. ...
The case of a second order nonlinear system is studied to illustrate the efficiency of the proposed approach, and it is shown that this approach is much simpler that other multimodel control design methods ...
Multimodel control Once the multimodel structure is elaborated, a polynomial controller can be designed for each linear model of the base. 1 1 1 1 ( ) ( ) ( ) ( ) ( ) 1, , ( ) i i c i i i u k T q y k R ...
doi:10.24846/v21i1y201212
fatcat:ue2dmvdhb5fshgs2fhzimd7w4e
Regional climate models downscaling in the Alpine area with Multimodel SuperEnsemble
2012
Hydrology and Earth System Sciences Discussions
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Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. ...
This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control ...
An evaluation of the models in the control period is available in Sect. 3. ...
doi:10.5194/hessd-9-9425-2012
fatcat:cipcn3blgfcrtdgnjgz2rvfiaa
Regional climate models downscaling in the Alpine area with multimodel superensemble
2013
Hydrology and Earth System Sciences
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<br><br> Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. ...
This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control ...
An evaluation of the models in the control period is available in Sect. 3. ...
doi:10.5194/hess-17-2017-2013
fatcat:ccctwny7yjco5ackxu3bv54vyi
A Multimodel Approach for Complex Systems Modeling based on Classification Algorithms
2014
International Journal of Computers Communications & Control
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In this paper, a new multimodel approach for complex systems modeling based on classification algorithms is presented. It requires firstly the determination of the model-base. ...
The second step consists in validating the proposed model-base by using the adequate method of validity computation. ...
to modelling, control and/or fault detection e.g ...
doi:10.15837/ijccc.2012.4.1364
fatcat:yrocbeomtff6xnh3es2nlob2we
The Role of Multimodel Climate Forecasts in Improving Water and Energy Management over the Tana River Basin, Kenya
2013
Journal of Applied Meteorology and Climatology
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The Dam 39 serves as the primary storage reservoir, controlling streamflow through a series of downstream 40 hydro-electric reservoirs. ...
The multimodel forecasts preserves 56 the end of the season target storage better than the single model inflow forecasts by reducing 57 uncertainty and the overconfidence of individual model forecasts. ...
The Dam serves as the 567 primary storage reservoir, controlling streamflow through a series of downstream hydro-electric 568 reservoirs. ...
doi:10.1175/jamc-d-12-0300.1
fatcat:almq5r2cancfjku4oeud46hsvm
Seasonal skill and predictability of ECMWF PROVOST ensembles
2010
Quarterly Journal of the Royal Meteorological Society
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A total of six multimodel schemes are considered that includes combinations based on pooling of ensembles as well as based on the long-term skill of the models. ...
The study suggests that, by constraining the end of the season target storage conditions being met with high probability, the climate information based streamflow forecasts could be utilized for invoking ...
flood control pool (controlled storage, 251.5-264.8 ft and uncontrolled storage, 264.8-289.2 ft); (2) Conservation pool (251.5-236.5 ft) with two separate storage accounts for water quality and water supply ...
doi:10.1002/qj.49712656704
fatcat:zqpfys6cmrdrpkfqszyoyocgkm
Hammerstein–Wiener Multimodel Approach for Fast and Efficient Muscle Force Estimation from EMG Signals
2022
Biosensors
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Results imply that the use of multimodel approach can improve the accuracy in proportional control of prostheses. ...
The second part fixes the appropriate sub-models of a multimodel library and computes the contribution of sub-models to estimate the desired force. ...
Within our scope for controlling upper limb myoelectric prostheses, accurate estimation of the overall force from the EMG drive proportional control-based schemes. ...
doi:10.3390/bios12020117
pmid:35200377
pmcid:PMC8870134
fatcat:i35aekwvwrfnlfxcqgrtyndmei
Incorporating model quality information in climate change detection and attribution studies
2009
Proceedings of the National Academy of Sciences of the United States of America
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The processes affecting the gradual response of the climate system to long-term anthropogenic forcing need not be the same as those controlling shorter-timescale phenomena. ...
The CMIP-3 multimodel dataset was supported by the Office of Science, U.S. Department of Energy. ...
The final step was to repeat the multimodel D&A analysis of Santer et al. (10) with updated SSM/I observations, 12 different fingerprints (Fig. 5 ), and 12 model-based noise estimates (Fig. ...
doi:10.1073/pnas.0901736106
pmid:19706477
pmcid:PMC2727480
fatcat:m6cgjpvbvzdkzmzyuucuv45c44
Biases in CMIP5 Sea Surface Temperature and the Annual Cycle of East African Rainfall
2020
Journal of Climate
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An atmospheric general circulation model (AGCM) is then forced with observed SSTs (1979-2005) generating a set of control runs and observed SSTs plus the monthly, multi-model mean SST biases generating ...
The control runs generally capture the observed annual cycle of East African rainfall while the bias runs capture prominent CMIP5 annual cycle biases, including too little (much) precipitation during the ...
Observational and model data longer base period when generating the atmospheric model runs needed for the study. ...
doi:10.1175/jcli-d-20-0092.1
fatcat:vdk2w2yutvfwxcjwkml4brf24q
Long Time-Scale Teleconnection Patterns in the Northern Atlantic and Pacific
2012
Journal of Climate
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The teleconnection patterns arise in an investigation of the internally generated variability in a multimodel ensemble of coupled climate model control simulations. ...
Although lacking statistical robustness, some aspects of the temperature teleconnection patterns are obtained based on the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) dataset. ...
A multimodel estimate of the potential predictability of decadal means of temperature and precipitation, based on over 8000 yr of data in total from the control simulations of 21 coupled climate models ...
doi:10.1175/2011jcli4107.1
fatcat:cir7jr4ssncfbmfyvxea4q7siy
Towards Active Diagnosis of Hybrid Systems leveraging Multimodel Identification and a Markov Decision Process
2015
IFAC-PapersOnLine
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It proposes to associate a diagnosis method based on multimodel identification and a framework for optimal conditional planning relying on a Markov decision process (MDP). ...
It proposes to associate a diagnosis method based on multimodel identification and a framework for optimal conditional planning relying on a Markov decision process (MDP). ...
The first part of the method presents a diagnosis process based on multimodel identification, also called here multimodel diagnosis. ...
doi:10.1016/j.ifacol.2015.09.522
fatcat:t3rszn3ts5fk5m5tp6v7b363ye
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