Many-core acceleration for model predictive control systems

Kawakami, Satoshi; Iwanaga, Akihito; Inoue, Koji

doi:10.1145/2489068.2489071

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Mpc Parallelization1

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Cited by 3 publications

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“…Although the key concept of parallel precomputation method for MPC has considered in [12], it mainly lacks four critical points. First, the related paper does not discuss the impact of real implementation.…”

Section: Mpc Parallelizationmentioning

confidence: 99%

Parallel Precomputation with Input Value Prediction for Model Predictive Control Systems

Kawakami

Ono

Ohtsuka

et al. 2018

IEICE Trans. Inf. & Syst.

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We propose a parallel precomputation method for realtime 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.

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Section: Mpc Parallelizationmentioning

confidence: 99%