Parallelized Model Predictive Control
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Model predictive control (MPC) has been used in many industrial applications because of its ability to produce optimal performance while accommodating constraints. However, its application on plants with fast time constants is difficult because of its computationally expensive algorithm. In this research, we propose a parallelized MPC that makes use of the structure of the computations and the matrices in the MPC. We show that the computational time of MPC with prediction horizon N can be reduced to O(log(N)) using parallel computing, which is significantly less than that with other available algorithms.
Date issued
2013-06Department
Massachusetts Institute of Technology. Department of Mechanical EngineeringJournal
Proceedings of the 2013 American Control Conference
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Soudbakhsh, Damoon and Anuradha M. Annaswamy. "Parallelized Model Predictive Control." 2013 American Control Conference. IEEE, 2013.
Version: Author's final manuscript
ISBN
978-1-4799-0178-4