| Title | Fuzzy explicit simplified MPC with adjustment parameter |
|---|---|
| Authors | ESCAÑO GONZÁLEZ, JUAN MANUEL, Witheephanich, K. , Roshany-Yamchi, S. , Bordons, C. , Liu, J , Lu, J , Xu, Y , Martinez, L , Kerre, EE |
| External publication | No |
| Means | Data Science and Knowledge Engineering for Sensing Decision Support |
| Scope | Conference Paper |
| Nature | Científica |
| Publication date | 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. |
| Keywords | Piece wise affine; functional principal component analysis; model predictive control; fuzzy control |
| Universidad Loyola members |
|
Manage cookies