Long-horizon finite-control-set model predictive control with non-recursive sphere decoding on an FPGA
Research output: Contribution to journal › Article › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Power Electronics |
| DOIs | |
| Publication status | E-pub ahead of print - 28 Nov 2019 |
| Publication type | A1 Journal article-refereed |
Abstract
Long-horizon finite-control-set model predictive control is implemented on a field-programmable gate array (FPGA). To solve the underlying least-squares integer program, a non-recursive sphere decoding algorithm is developed. By exploiting the problem structure, few multipliers are required, and the algorithm computes the optimal solution in a few clock cycles, thus achieving a resource-efficient implementation on the FPGA. For a prediction horizon of five steps and a three-level converter, 87 digital signal processor (DSP) blocks and an execution time of at most 13.4's was required to solve the optimization problem during steady-state operation. Experimental results verify the effectiveness of the long-horizon controller.