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Parallel Sphere Decoding Algorithm for Long-Prediction-Horizon FCS-MPC
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DOI：10.1109/TPEL.2022.3150433.png)
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Abstract
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Researchinterest in finite-control-set model-predictive control (FCS-MPC) for power conversion devices has grown in recent years. Particularly, long-prediction-horizon FCS-MPC provides promising results in recent research works. However, its practical implementation is not generally straightforward due to its inherently large computational burden. To overcome this obstacle, the problem can be formulated as a least-squares integer program. A sphere decoding algorithm (SDA) is a branch-and-bound algorithm proposed in previous works as an efficient approach to solve this problem. In these works, the SDA is formulated as an iterative process, where simultaneous search is not possible. A parallel and fully scalable SDA design is proposed in this article. The design is implemented in the field-programmable gate array of a modern field-programmable system-on-chip platform. Thanks to the proposed parallelization, the required execution time is greatly reduced. Experimental results prove the feasibility and performance improvements of the proposed implementation.
Keywords:
Cost function
Prediction algorithms
Power harmonic filters
Uninterruptible power systems
Switches
Mathematical models
Predictive models
DC-AC power converter
digital control
predictive control
Journal
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6.5
Papers:
1.7W
Citations:
8.3W
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