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A Control-Performance-Based Partitioning Operating Space Approach in a Heterogeneous Multiple Model

Wu, Liu, Yue
2020 Processes  
Finally, a multiple model predictive controller is designed, and the computational implementation of the multiple model predictive controller is addressed with the auxiliary vectors.  ...  An operating space partition method with control performance is proposed, where the heterogeneous multiple model is applied to a nonlinear system.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/pr8020215 fatcat:x5q4yxecvjbkdgbalrlx6t4d7u

Cerebro-cerebellar networks facilitate learning through feedback decoupling [article]

Ellen Boven, Joseph Pemberton, Paul Chadderton, Richard Apps, Rui Ponte Costa
2022 bioRxiv   pre-print
In this model a cerebral recurrent network receives feedback predictions from a cerebellar network, thereby decoupling learning in cerebral networks from future feedback.  ...  When trained in a simple sensorimotor task the model shows faster learning and reduced dysmetria-like behaviours, in line with the widely observed functional impact of the cerebellum.  ...  We study the behaviour of our model in a range of tasks. To train the model we use a prediction error function E task which compares the model output with task-specific external feedback.  ... 
doi:10.1101/2022.01.28.477827 fatcat:d6sw7m5igzd2plf4htnefp74qi

The Next Generation NATO Reference mobility model development

Michael McCullough, Paramsothy Jayakumar, Jean Dasch, David Gorsich
2017 Journal of terramechanics  
The NATO Reference Mobility Model (NRMM) is a simulation tool aimed at predicting the capability of a vehicle to move over specified terrain conditions. NRMM was developed and validated by the U.S.  ...  Developing the Next Generation NATO Reference Mobility Model, McCullough, et al. UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited.(#27849)  ...  Approved for public release; distribution is unlimited.(#27849) Page 16 of 20 the current NRMM Operational modules algorithms and models as a starting point toward a draft input/output component of the  ... 
doi:10.1016/j.jterra.2017.06.002 fatcat:yyfbyhusbvee5ddeyt32xvrpgm

A Learning-Based Tune-Free Control Framework for Large Scale Autonomous Driving System Deployment [article]

Yu Wang, Shu Jiang, Weiman Lin, Yu Cao, Longtao Lin, Jiangtao Hu, Jinghao Miao, Qi Luo
2020 arXiv   pre-print
enable the control-in-the-loop simulation with highly accurate vehicle dynamics for parameter tuning; a learning-based open-loop mapping procedure, to solve the feedforward control parameters tuning;  ...  The framework consists of three machine-learning-based procedures, which jointly automate the control parameter tuning for autonomous driving, including: a learning-based dynamic modeling procedure, to  ...  [20] presented a Bayesian-based calibration strategy to tune the Model Predictive Control (MPC) cost with little additional experimental effort.  ... 
arXiv:2011.04250v1 fatcat:krt4d7vfpzffrkryhqpvo5f35m

A neural network model for timing control with reinforcement [article]

Jing Wang, Yousuf El-Jayyousi, Ilker Ozden
2022 arXiv   pre-print
Unlike other neural network models that search for unique network connectivity for the best match between the model prediction and observation, this model can estimate the uncertainty associated with each  ...  In the experiment, human subjects proactively generated a series of timed motor outputs.  ...  Model evaluation metrics We tested whether vAR was a better model for predicting the sequential structure by comparing the residuals of AR, vAR, and GRU.  ... 
arXiv:2205.04347v1 fatcat:uo6r7ghg7jen3jqvrht4tb7efe

2008 Index IEEE Transactions on Automatic Control Vol. 53

2008 IEEE Transactions on Automatic Control  
Note that the item title is found only under the primary entry in the Author Index.  ...  The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TAC March 2008 625-631 A Parametric Lyapunov Equation Approach to the Design of Low Gain Feedback. Zhou, B., +, TAC July 2008 1548-1554 Adaptive Control and Robustness in the Gap Metric.  ... 
doi:10.1109/tac.2008.2010902 fatcat:5d76tgkjnvhohntuilcvl3jb3i

Automatic tuning of paper machines cross-direction controllers via linear matrix inequalities

Mohammed E. Ammar, Guy A. Dumont
2015 Journal of Electrical Systems and Information Technology  
Robust stability and performance of the controller in the presence of parametric uncertainties are investigated through the ν-gap metric.  ...  The paper machine cross-direction (CD) process is a large-scale spatially distributed system.  ...  The ν-gap metric The ν-gap metric between two plants G 0 and G 1 (δ ν (G 0 , G 1 )) is the gap between their L 2 graph spaces when a winding condition (wno) is satisfied.  ... 
doi:10.1016/j.jesit.2015.11.006 fatcat:5h2sffoa7zenfaiyoux2ngurni

Modulation, coding and signal processing for wireless communications - Single-antenna co-channel interference cancellation for TDMA cellular radio systems

P.A. Hoeher, S. Badri-Hoeher, Wen Xu, C. Krakowski
2005 IEEE wireless communications  
In SAIC, decoupled linear CCI cancellation/nonlinear equalization outperforms predictive CCI cancellation in conjunction with auto-regressive interference modeling, due to the inherent model mismatch in  ...  In predictive CCI cancellation in conjunction with auto-regressive interference modeling, the interference plus noise process is modeled by an auto-regressive model.  ... 
doi:10.1109/mwc.2005.1421926 fatcat:eq2wp4w77rhnbji2rd6s3e7fsi

Cortico-cerebellar networks as decoupling neural interfaces [article]

Joseph Pemberton and Ellen Boven and Richard Apps and Rui Ponte Costa
2021 arXiv   pre-print
To demonstrate the potential of this framework we introduce a systems-level model in which a recurrent cortical network receives online temporal feedback predictions from a cerebellar module.  ...  Recently, decoupled neural interfaces (DNIs) were introduced as a solution to the forward and feedback locking problems in deep networks.  ...  Moreover, ccRNN also outputs a better model of language as assessed by language metrics (Table S2 ).  ... 
arXiv:2110.11501v2 fatcat:wja2pqn275gnzdhxbeez2tgv4q

Cooperative Control for Ocean Sampling: The Glider Coordinated Control System

D.A. Paley, F. Zhang, N.E. Leonard
2008 IEEE Transactions on Control Systems Technology  
The Glider Coordinated Control System (GCCS) uses a detailed glider model for prediction and a simple particle model for planning to steer a fleet of underwater gliders to a set of coordinated trajectories  ...  The GCCS also serves as a simulation testbed for the design and evaluation of multivehicle control laws.  ...  Haley of Harvard University, Harvard, Cambridge, MA; and the rest of the ASAP team.  ... 
doi:10.1109/tcst.2007.912238 fatcat:ruhhyfgvyzgqhbmsgxvhcqsq4i

2007 Index IEEE Transactions on Automatic Control Vol. 52

2007 IEEE Transactions on Automatic Control  
-1779 Ghafoor, A., and Sreeram, V., Partial-Fraction Expansion Based Frequency Weighted Model Reduction Technique With Error Bounds; TAC Oct. 2007 Oct. 1942Oct. -1948 Ghosh, B.  ...  ., Approximation Metrics for Discrete and Continuous Systems; TAC May 2007 782-798 Giua, A., see Basile, F., TAC Feb. 2007 306-311 Giua, A., Seatzu, C., and Corona, C., Oct. 2007 Oct.  ...  ., +, TAC Feb. 2007 328-334 Nominally Robust Model Predictive Control With State Constraints.  ... 
doi:10.1109/tac.2007.913948 fatcat:vpztpth7jnhk7b5o5bt2nyrrdm

2013 Index IEEE Transactions on Automatic Control Vol. 58

2013 IEEE Transactions on Automatic Control  
., see Dominguez- Garcia, A. D., TAC March 2013 1696-1706 Hammouri, H., see Nadri, M., TAC March 2013 757-762 Hammouri, H., see Benachour, M. S., TAC Dec. 2013 3011-3023 Han, Q.  ...  Gruszka, A., +, TAC Jan. 2013 180-187 Distributed Output-Feedback Control of Nonlinear Multi-Agent Systems.  ...  ., +, TAC March 2013 725-730 Reconciling /spl nu/-Gap Metric and IQC Based Robust Stability Analysis. Khong, S.  ... 
doi:10.1109/tac.2013.2295962 fatcat:3zpqog4r4nhoxgo4vodx4sj3l4

The Impact of Data on the Stability of Learning-Based Control- Extended Version [article]

Armin Lederer, Alexandre Capone, Thomas Beckers, Jonas Umlauft, Sandra Hirche
2021 arXiv   pre-print
Our approach is applicable to a wide variety of unknown nonlinear systems that are to be controlled by a generic learning-based control law, and the results obtained in numerical simulations indicate the  ...  In this paper, we propose a Lyapunov-based measure for quantifying the impact of data on the certifiable control performance.  ...  Acknowledgments This work was supported by the European Research Council Consolidator Grant "Safe data-driven control for human-centric systems (CO-MAN)" under grant agreement number 864686.  ... 
arXiv:2011.10596v2 fatcat:3t6o2lir2jgbbai6ydy46wk7cq

ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia [article]

Aaron Halfaker, R. Stuart Geiger
2020 arXiv   pre-print
ORES decouples several activities that have typically all been performed by engineers: choosing or curating training data, building models to serve predictions, auditing predictions, and developing interfaces  ...  However, conversations about how quality control should work and what role algorithms should play have generally been led by the expert engineers who have the skills and resources to develop and modify  ...  Sloan Foundation (Grant 2013-10-27), as part of the Moore-Sloan Data Science Environments grant to UC-Berkeley, and directly by the Wikimedia Foundation.  ... 
arXiv:1909.05189v3 fatcat:jgttjclmdbgyvoybhzndywuodq

Offset-free fuzzy model predictive control of a boiler–turbine system based on genetic algorithm

Yiguo Li, Jiong Shen, Kwang Y. Lee, Xichui Liu
2012 Simulation modelling practice and theory  
This paper presents a model predictive control (MPC) strategy based on genetic algorithm to solve the boiler-turbine control problem.  ...  First, a Takagi-Sugeno (TS) fuzzy model based on gap values is established to approximate the behavior of the boiler-turbine system, then a specially designed genetic algorithm (GA) is employed to solve  ...  Acknowledgments The authors would like to thank anonymous reviewers and the editor for their valuable comments and suggestions.  ... 
doi:10.1016/j.simpat.2012.04.002 fatcat:qfkvlkykwnfy3fxvx65sof7xdi
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