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Explicit Model Predictive Control of a Hybrid System Using Support Vector Machines

Bernt M. Åkesson, Mats J. Nikus, Hannu T. Toivonen, Explicit Model Predictive Control of a Hybrid System Using Support Vector Machines. In: 1st IFAC Workshop on Applications of Large Scale Industrial Systems (ALSIS'06), 2006.

Abstract:

The objective of this work is to study the capabilities of support vector machines for approximating the complex control law arising from model predictive control of a hybrid MIMO-system. By approximating the control law, an explicit formulation can be obtained, which is computationally less intensive for on-line use. The explicit model predictive control approach is applied to a simulated hybrid system consisting of two tanks in series. The system has real-valued, integer-valued, and binary-valued control inputs. A model predictive controller is first designed to control the entire system. This controller is then approximated using support vector machines, with separate approximators for each control input. Reasonable control results were achieved with the approximators.

BibTeX entry:

@INPROCEEDINGS{inpAkNiTo06a,
  title = {Explicit Model Predictive Control of a Hybrid System Using Support Vector Machines},
  booktitle = {1st IFAC Workshop on Applications of Large Scale Industrial Systems (ALSIS'06)},
  author = {Åkesson, Bernt M. and Nikus, Mats J. and Toivonen, Hannu T.},
  year = {2006},
}

Belongs to TUCS Research Unit(s): Other

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