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Long-Horizon Finite-Control-Set Model Predictive Control With Non-Recursive Sphere Decoding on an FPGA


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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 μs was required to solve the optimization problem during steady-state operation. Experimental results verify the effectiveness of the long-horizon controller.

KeyWords
Model predictive control, optimal control, fieldprogrammable gate array, integer programming, sphere decoder, three-level neutral-point clamped (NPC) converters, integer leastsquares



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