ESCAÑO GONZÁLEZ, JUAN MANUEL, Witheephanich, K. , Roshany-Yamchi, S. , Bordons, C. , Liu, J , Lu, J , Xu, Y , Martinez, L , Kerre, EE

No

Data Science and Knowledge Engineering for Sensing Decision Support

Conference Paper

Científica

✗

✗

01/01/2018

000468160600118

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.

Piece wise affine; functional principal component analysis; model predictive control; fuzzy control