Artículo
Computationally Efficient Sphere Decoding Algorithm Based on Artificial Neural Networks for Long-Horizon FCS-MPC
Autor/es | Zafra Ratia, Eduardo
Granado Romero, Joaquín ![]() ![]() ![]() ![]() ![]() ![]() ![]() Baena Lecuyer, Vicente ![]() ![]() ![]() ![]() ![]() ![]() ![]() Vázquez Pérez, Sergio ![]() ![]() ![]() ![]() ![]() ![]() ![]() Márquez Alcaide, Abraham ![]() ![]() ![]() ![]() ![]() ![]() León Galván, José Ignacio ![]() ![]() ![]() ![]() ![]() ![]() ![]() García Franquelo, Leopoldo ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Departamento | Universidad de Sevilla. Departamento de Ingeniería Electrónica |
Fecha de publicación | 2024-01 |
Fecha de depósito | 2024-08-14 |
Publicado en |
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Resumen | Successful application of finite control set model predictive control (FCS-MPC) strategies with long prediction horizon depends on the careful design of the optimization algorithm. The conventional method involves transforming ... Successful application of finite control set model predictive control (FCS-MPC) strategies with long prediction horizon depends on the careful design of the optimization algorithm. The conventional method involves transforming the problem to an equivalent box-constrained integer least-squares (BILS) formulation that can be solved with branch-and-bound techniques such as the sphere decoding algorithm (SDA). In this work, it is proposed to define an artificial neural network (ANN) to replace the SDA, avoiding its inherent computational variability. Similarly to practical applications of the SDA, the ANN finds an approximate solution of the underlying optimization problem. In contrast, the main benefit of the proposed approach is that it can be implemented in a low-cost microprocessing platform, greatly improving the performance in terms of resources in comparison with other advanced techniques roposed in the literature. |
Agencias financiadoras | Ministerio de Ciencia, Innovación y Universidades (MICINN). España European Union NextGenerationEU |
Identificador del proyecto | PID2020-115561RB-C31
![]() TED2021-130613B-I00 ![]() |
Cita | Zafra, E., Granado, J., Baena Lecuyer, V., Vázquez, S., Alcaide, A.M., León, J.I. y Franquelo, L.G. (2024). Computationally Efficient Sphere Decoding Algorithm Based on Artificial Neural Networks for Long-Horizon FCS-MPC. IEEE Transactions on Industrial Electronics, 71 (1), 39-48. https://doi.org/10.1109/TIE.2023.3243301. |
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