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Abstract

In this work, a novel methodology is presented to reduce the computational complexity of applying explicit solution of Model Predictive Control (MPC). 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. Thus, the application of MPC is allowed in systems with low computational requirements, such as programmable logic controllers, embedded systems, etc. The proposed design has been validated using an industrial distiller model.

Keywords

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

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Explicit simplified MPC with an adjustment parameter adapted by a fuzzy system

Abstract

Keywords

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