Parallel precomputation with input value prediction for model predictive control systems

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


We propose a parallel precomputation method for real-time model predictive control. The key idea is to use predicted input values produced by model predictive control to solve an optimal control problem in advance. It is well known that control systems are not suitable for multi- or many-core processors because feedback-loop control systems are inherently based on sequential operations. However, since the proposed method does not rely on conventional thread-/data-level parallelism, it can be easily applied to such control systems without changing the algorithm in applications. A practical evaluation using three real-world model predictive control system simulation programs demonstrates drastic performance improvement without degrading control quality offered by the proposed method.

Original languageEnglish
Pages (from-to)2864-2877
Number of pages14
JournalIEICE Transactions on Information and Systems
Issue number12
Publication statusPublished - Dec 2018

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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