MPC implementation in a PLC based on Nesterov's fast gradient method

2015 23rd Mediterranean Conference on Control and Automation (MED) ◽

10.1109/med.2015.7158777 ◽

2015 ◽

Author(s):

M. Pereira ◽

D. Limon ◽

D. Munoz de la Pena ◽

T. Alamo

Keyword(s):

Gradient Method ◽

Fast Gradient Method ◽

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Three-Dimensional Gravity-Magnetic Cross-Gradient Joint Inversion Based on Structural Coupling and a Fast Gradient Method

Journal of Computational Mathematics ◽

10.4208/jcm.1905-m2018-0240 ◽

2019 ◽

Vol 37 (6) ◽

pp. 758-777 ◽

Author(s):

Yuanping Zhang and Yanfei Wang sci

Keyword(s):

Gradient Method ◽

Joint Inversion ◽

Three Dimensional ◽

Structural Coupling ◽

Fast Gradient Method ◽

Dimensional Gravity ◽

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An FPGA implementation of the fast gradient method for solving the Model Predictive Pulse Pattern Control problem

2013 IEEE International Symposium on Sensorless Control for Electrical Drives and Predictive Control of Electrical Drives and Power Electronics (SLED/PRECEDE) ◽

10.1109/sled-precede.2013.6684480 ◽

2013 ◽

Author(s):

Helfried Peyrl ◽

Junyi Liu ◽

Tobias Geyer

Keyword(s):

Control Problem ◽

Gradient Method ◽

Fpga Implementation ◽

Fast Gradient Method ◽

Pattern Control ◽

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An application of the fast gradient method to model predictive control of an atomic force microscope X-Y stage

2017 IEEE Conference on Control Technology and Applications (CCTA) ◽

10.1109/ccta.2017.8062449 ◽

2017 ◽

Author(s):

Roger A. Braker ◽

Lucy Y. Pao

Keyword(s):

Model Predictive Control ◽

Atomic Force Microscope ◽

Predictive Control ◽

Gradient Method ◽

Fast Gradient Method ◽

Atomic Force ◽

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Model Predictive Torque Control with PWM using fast gradient method

2013 Twenty-Eighth Annual IEEE Applied Power Electronics Conference and Exposition (APEC) ◽

10.1109/apec.2013.6520661 ◽

2013 ◽

Author(s):

Matthias Preindl ◽

Silverio Bolognani ◽

Claus Danielson

Keyword(s):

Gradient Method ◽

Torque Control ◽

Fast Gradient Method ◽

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A parallel dual fast gradient method for MPC applications

2015 54th IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc.2015.7402568 ◽

2015 ◽

Author(s):

Laura Ferranti ◽

Tamas Keviczky

Keyword(s):

Gradient Method ◽

Fast Gradient Method ◽

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Primal-dual fast gradient method with a model

Computer Research and Modeling ◽

10.20537/2076-7633-2020-12-2-263-274 ◽

2020 ◽

Vol 12 (2) ◽

pp. 263-274

Author(s):

Alexander Igorevich Tyurin

Keyword(s):

Gradient Method ◽

Fast Gradient Method ◽

Primal Dual ◽

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Computational Complexity Certification for Real-Time MPC With Input Constraints Based on the Fast Gradient Method

IEEE Transactions on Automatic Control ◽

10.1109/tac.2011.2176389 ◽

2012 ◽

Vol 57 (6) ◽

pp. 1391-1403 ◽

Author(s):

Stefan Richter ◽

Colin Neil Jones ◽

Manfred Morari

Keyword(s):

Computational Complexity ◽

Real Time ◽

Gradient Method ◽

Input Constraints ◽

Fast Gradient Method ◽

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NESVM: A Fast Gradient Method for Support Vector Machines

2010 IEEE International Conference on Data Mining ◽

10.1109/icdm.2010.135 ◽

2010 ◽

Author(s):

Tianyi Zhou ◽

Dacheng Tao ◽

Xindong Wu

Keyword(s):

Support Vector Machines ◽

Gradient Method ◽

Support Vector ◽

Fast Gradient Method ◽

Vector Machines ◽

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Fast predictive control of linear, time-invariant systems using an algorithm based on the fast gradient method and augmented Lagrange multipliers

2011 IEEE International Conference on Control Applications (CCA) ◽

10.1109/cca.2011.6044410 ◽

2011 ◽

Author(s):

Markus Kogel ◽

Rolf Findeisen

Keyword(s):

Predictive Control ◽

Gradient Method ◽

Lagrange Multipliers ◽

Linear Time ◽

Fast Gradient Method ◽

Linear Time Invariant ◽

Fast Gradient ◽

Linear Time Invariant Systems ◽

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Rate of convergence analysis of a dual fast gradient method for general convex optimization

2015 54th IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc.2015.7402717 ◽

2015 ◽

Author(s):

Andrei Patrascu ◽

Ion Necoara ◽

Rolf Findeisen

Keyword(s):

Convex Optimization ◽

Rate Of Convergence ◽

Convergence Analysis ◽

Gradient Method ◽

Fast Gradient Method ◽

General Convex ◽

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