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Gradient-Based Model Predictive Control in a Pendulum System

Giselsson, Pontus LU (2012) In Report TFRT 7624.
Abstract
Model predictive control (MPC) is applied to a physical pendulum system consisting of a pendulum and a cart. The objective of the MPC controller is to steer the system towards precomputed, time-optimal feedforward trajectories that move the system from one stationary point to another. The sample time of the controller sets hard limitations on the execution time of the optimization algorithm in the MPC controller. The MPC optimization problem is stated as a quadratic program, which is solved using the algorithm presented in [10]. The algorithm in [10] is an accelerated gradient method that is applied to solve a dual formulation of the MPC optimization problem. Experiments show that the optimization algorithm is efficient enough to be... (More)
Model predictive control (MPC) is applied to a physical pendulum system consisting of a pendulum and a cart. The objective of the MPC controller is to steer the system towards precomputed, time-optimal feedforward trajectories that move the system from one stationary point to another. The sample time of the controller sets hard limitations on the execution time of the optimization algorithm in the MPC controller. The MPC optimization problem is stated as a quadratic program, which is solved using the algorithm presented in [10]. The algorithm in [10] is an accelerated gradient method that is applied to solve a dual formulation of the MPC optimization problem. Experiments show that the optimization algorithm is efficient enough to be implemented in a real-time pendulum application. (Less)
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author
organization
publishing date
type
Book/Report
publication status
published
subject
keywords
Model Predictive Control, Pendulum system, Gradient-Based Optimization
in
Report TFRT
volume
7624
publisher
Department of Automatic Control, Lund Institute of Technology, Lund University
ISSN
0280-5316
language
English
LU publication?
yes
id
76aa52af-757d-4ef5-8243-e98c3031c6ae (old id 3128472)
date added to LUP
2012-10-12 13:18:22
date last changed
2016-04-15 23:46:09
@techreport{76aa52af-757d-4ef5-8243-e98c3031c6ae,
  abstract     = {Model predictive control (MPC) is applied to a physical pendulum system consisting of a pendulum and a cart. The objective of the MPC controller is to steer the system towards precomputed, time-optimal feedforward trajectories that move the system from one stationary point to another. The sample time of the controller sets hard limitations on the execution time of the optimization algorithm in the MPC controller. The MPC optimization problem is stated as a quadratic program, which is solved using the algorithm presented in [10]. The algorithm in [10] is an accelerated gradient method that is applied to solve a dual formulation of the MPC optimization problem. Experiments show that the optimization algorithm is efficient enough to be implemented in a real-time pendulum application.},
  author       = {Giselsson, Pontus},
  institution  = {Department of Automatic Control, Lund Institute of Technology, Lund University},
  issn         = {0280-5316},
  keyword      = {Model Predictive Control,Pendulum system,Gradient-Based Optimization},
  language     = {eng},
  series       = {Report TFRT},
  title        = {Gradient-Based Model Predictive Control in a Pendulum System},
  volume       = {7624},
  year         = {2012},
}