Parallelized Model Predictive Control
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 res...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2014
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| Online Access: | http://hdl.handle.net/1721.1/86999 https://orcid.org/0000-0002-4354-0459 |
| Summary: | 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. |
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