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Data-driven Switched Affine Modeling for Model Predictive Control

Francesco Smarra, Achin Jain, Rahul Mangharam, Alessandro D'Innocenzo
2018 IFAC-PapersOnLine  
Finite Receding Horizon Control (RHC) setup using control-oriented data-driven models based on regression trees and random forests is presented as well.  ...  Finite Receding Horizon Control (RHC) setup using control-oriented data-driven models based on regression trees and random forests is presented as well.  ...  Control problem that uses such data-driven model.  ... 
doi:10.1016/j.ifacol.2018.08.034 fatcat:3rxhdmm7b5e2fekrwfjwpoj7hi

2021 Index IEEE Open Journal of the Industrial Electronics Society Vol. 2

2021 IEEE Open Journal of the Industrial Electronics Society  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., OJIES 2021 469-478 Physics Enhanced Data-Driven Models With Variational Gaussian Pro-cesses.  ...  ., +, OJIES 2021 153-168 Physics Enhanced Data-Driven Models With Variational Gaussian Pro-cesses.  ... 
doi:10.1109/ojies.2022.3150712 fatcat:ntirukbx4vb3zm4qjfdm2edtcq

Data-driven Model Predictive and Reinforcement Learning Based Control for Building Energy Management: a Survey [article]

Huiliang Zhang, Sayani Seal, Di Wu, Benoit Boulet, Francois Bouffard, Geza Joos
2021 arXiv   pre-print
This paper presents a compact review of the recent advances in data-driven MPC and reinforcement learning based control methods for BEMS.  ...  Classical model predictive control (MPC) has shown its capacity to reduce building energy consumption, but it suffers from labor-intensive modelling and complex on-line control optimization.  ...  A variation of the similar approach is presented in [24] , where state-space switched affine dynamical linear timeinvariant (LTI) models are identified instead of the affine static prediction The switched  ... 
arXiv:2106.14450v1 fatcat:bmgvjtqig5c4vhntu5eqroarn4

Data-driven Model Predictive and Reinforcement Learning-Based Control for Building Energy Management: a Survey

Huiliang Zhang, Sayani Seal, Di Wu, Francois Bouffard, Benoit Boulet
2022 IEEE Access  
In this work, we first present a compact review of the recent advances in data-driven MPC and RL-based control methods for building energy management.  ...  INDEX TERMS Building energy management, model predictive control, reinforcement learning, datadriven control.  ...  A variation of the similar approach is presented in [37] , where state-space switched affine dynamical linear time-invariant models are identified instead of the affine static prediction The switched  ... 
doi:10.1109/access.2022.3156581 fatcat:ql34l2572fagbdq7vxrai7aclu

Data-driven model predictive control using random forests for building energy optimization and climate control

Francesco Smarra, Achin Jain, Tullio de Rubeis, Dario Ambrosini, Alessandro D'Innocenzo, Rahul Mangharam
2018 Applied Energy  
Data-driven model predictive control using random forests for building energy optimization and climate control. Applied Energy, 2018.  ...  Data-driven model predictive control using random forests for building energy optimization and climate control Abstract Model Predictive Control (MPC) is a model-based technique widely and successfully  ...  the University of L'Aquila, for the help in obtaining the real data from the house, and Manfred Morari, for his feedback on DPC.  ... 
doi:10.1016/j.apenergy.2018.02.126 fatcat:bicc4l6iwfe55jpsjrkah7kh2u

Transcription Factor STAT3 Serves as a Negative Regulator Controlling IgE Class Switching in Mice

Paul Dascani, Chuanlin Ding, Xiangyu Kong, David Tieri, Xiaoling Hu, Huang-ge Zhang, Daisuke Kitamura, Roberto Bolli, Eric C. Rouchka, Jun Yan
2018 ImmunoHorizons  
This model suggests a negative role for STAT3 in regulating class switching of the GC B cells from the IgG1 to the IgE producing state, which may serve as a therapeutic target for treatment of autosomal  ...  We investigated the specific role of STAT3 in the germinal center (GC) B cells and plasma cells for IgE class switching.  ...  However, we have found reduced IgE affinity in our knockout models, indicating a more complex role for STAT3 in IgE production.  ... 
doi:10.4049/immunohorizons.1800069 pmid:31026806 fatcat:hku5l57r25dfzbympgpnb5xyae

Data-Driven Model Predictive Control using Interpolated Koopman Generators [article]

Sebastian Peitz and Samuel E. Otto and Clarence W. Rowley
2020 arXiv   pre-print
The main idea is to transform a control system into a set of autonomous systems for which the optimal switching sequence has to be computed.  ...  We show that when using the Koopman generator, this relaxation --- realized by linear interpolation between two operators --- does not introduce any error for control affine systems.  ...  In this article, we begin to examine how the Koopman operators and generators can be properly interpolated in the sense of [27] to yield efficient data-driven reduced-order models for model predictive  ... 
arXiv:2003.07094v1 fatcat:xporncvksbf47gaui25zu3hbli

Adaptive Cruise Control for a SMART Car: A Comparison Benchmark for MPC-PWA Control Methods

D. Corona, B. De Schutter
2008 IEEE Transactions on Control Systems Technology  
The design of an adaptive cruise controller for a SMART car, a type of small car, is proposed as a benchmark setup for several model predictive control methods for nonlinear and piecewise affine systems  ...  Index Terms-Adaptive cruise control, mixed integer optimization, model predictive control (MPC), piecewise affine systems, road vehicles.  ...  Second, the problem of designing the control law may be naturally cast into a model predictive control (MPC) framework [1] , which will result in a constrained minimization problem for which several efficient  ... 
doi:10.1109/tcst.2007.908212 fatcat:hjtma4inmfcsfiqjjl55fdnheq

Model of DC/DC Dual-Bridge Series Resonant Converter in Buck and Boost Modes for Output Current and Commutation Timing Control

Alex Borisevich, BrutBio Inc., Filipp Gleyzer, Department of Automotive, Skyline College, 3300 College Drive, San Bruno, CA 94066, USA.
2019 Journal of Engineering Science and Technology Review  
In the paper, a control-affine model for the active dual-bridge series resonant converter is presented.  ...  The maximum prediction error of this model is about 10% in comparison to the measured data.  ...  The general conclusion from the data is: the model fairly well predicts the output current, the switching parameters are predicted with about 100ns tolerance.  ... 
doi:10.25103/jestr.122.21 fatcat:kvsihvphf5hwnclp7vm7mcsjfe

The cis-Regulatory Logic of Hedgehog Gradient Responses: Key Roles for Gli Binding Affinity, Competition, and Cooperativity

D. S. Parker, M. A. White, A. I. Ramos, B. A. Cohen, S. Barolo
2011 Science Signaling  
Counterintuitively and in contrast to previous models of Gli-regulated gene expression, we found that low-affinity binding sites for Ci were required for proper spatial expression of the Hh target gene  ...  Three low-affinity Ci sites enabled expression of dpp in response to low signal; increasing the affinity of these sites restricted dpp expression to regions of maximal signaling. A model  ...  Gumucio, and members of our labs for helpful discussions and comments on the manuscript.  ... 
doi:10.1126/scisignal.2002077 pmid:21653228 pmcid:PMC3152249 fatcat:c3uinvnprvdnxaxod6zudwbzea

Front cover

2021 IEEE/CAA Journal of Automatica Sinica  
So-In (1786) Data-Driven Heuristic Assisted Memetic Algorithm for Efficient Inter-Satellite Link Scheduling in the BeiDou Navigation Satellite System· . . . . . . . . . . .. Y. H. Du, L. Wang, L. N.  ...  Liu (1817) Pseudo-Predictor Feedback Control for Multiagent Systems with Both State and Input Delays· . · Q. S.  ... 
doi:10.1109/jas.2021.1004186 fatcat:gpalqrp4nbfzbnuybxakcfs2by

Special issue on control theory and technologies in honor of the 70th birthday of Professor Frank L. Lewis

Jie Huang, Ben M. Chen
2019 Control Theory and Technology  
his earlier research period, and his recent focus on cooperative multi-agent distributed systems, reinforcement learning in control, wireless sensor networks for area security monitoring and condition-based  ...  maintenance, robotic system control, and manufacturing process control and scheduling to name a few.  ...  discrete-time systems by Bo PANG, Tao BIAN, Zhong-Ping JIANG This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discrete-time systems.  ... 
doi:10.1007/s11768-019-8287-2 fatcat:rx4kdt5d3jacndj3kgy562jpo4

Modularized Bilinear Koopman Operator for Modeling and Predicting Transients of Microgrids [article]

Xinyuan Jiang, Yan Li, Daning Huang
2022 arXiv   pre-print
As a scalable data-driven approach, M-KBF divides the identification and prediction of the high-dimensional nonlinear system into the individual study of subsystems; and thus, alleviating the difficulty  ...  The modularity feature of M-KBF enables the provision of fast and precise prediction for the microgrid operation and control, paving the way towards online applications.  ...  KBF is used to develop a precise data-driven model for each DER, since the typical power-electronics-interfaced DERs have been determined to be control-affine to the input disturbance from the current  ... 
arXiv:2205.03214v2 fatcat:etc24ranenhy7aa5xa6foulszm

Table of Contents

2022 IEEE Transactions on Automatic Control  
Sontag 3305 Data-Driven Control for Linear Discrete-Time Delay Systems . . . . . . .J. G. Rueda-Escobedo, E. Fridman, and J.  ...  Deng 3273 Distributionally Robust Chance Constrained Data-Enabled Predictive Control . . . . J. Coulson, J. Lygeros, and F.  ... 
doi:10.1109/tac.2022.3184886 fatcat:zokii7rbtvanpk7iclo76eanue

Model Predictive Control approach to adaptive messaging intervention for physical activity [article]

Ibrahim E. Bardakci, Sahar Hojjatinia, Sarah Hojjatinia, Constantino M. Lagoa, David E. Conroy
2021 arXiv   pre-print
In this work, we have developed a framework for synthesizing data driven controllers for a class of uncertain switched systems arising in an application to physical activity interventions.  ...  We have tailored the mixed-integer programming-based approach for evaluating the Model Predictive Control decision at each time step.  ...  APPLICATION TO BEHAVIORAL DATA SETS In this section, we provide an implementation of the data driven approach to controller design for developing personalized treatments aimed at improving physical activity  ... 
arXiv:2108.11499v1 fatcat:wfe4erqlarebff7ryvlguc43ry
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