| Título | Fuzzy explicit simplified MPC with adjustment parameter |
|---|---|
| Autores | ESCAÑO GONZÁLEZ, JUAN MANUEL, Witheephanich, K. , Roshany-Yamchi, S. , Bordons, C. , Liu, J , Lu, J , Xu, Y , Martinez, L , Kerre, EE |
| Publicación externa | No |
| Medio | Data Science and Knowledge Engineering for Sensing Decision Support |
| Alcance | Conference Paper |
| Naturaleza | Científica |
| Fecha de publicacion | 01/01/2018 |
| ISI | 000468160600118 |
| Abstract | In this work, a novel methodology is presented to reduce the computational complexity of applying explicit solution of model based predictive control. The methodology is based on applying the functional principal component analysis, providing a mathematically elegant approach to reduce the complexity of rule-based systems, like piecewise affine systems, allowing the reduction of the number of consequents and combining and merging the antecedents. The proposed design has been validated using an industrial system model. |
| Palabras clave | Piece wise affine; functional principal component analysis; model predictive control; fuzzy control |
| Miembros de la Universidad Loyola |
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