Abstract
This paper proposes multi-model modelling and predictive control based on Local Model Networks (LMN). An LMN modelling method using Satisfying Fuzzy c-Mean (SFCM) clustering algorithm is introduced. SFCM is designed to determine a satisfactory number of local models, and an identification algorithm based on weighted performance index is used to generate multiple models with good trade-off between global fitting and local interpretation. Considering that each local model is valid only in each local regime, different predictive controllers are designed for different local models with different local constraints, and Multi-model Predictive Control with Local Constraints (MMPCLC) is presented using Parallel Distribution Compensation (PDC) method. The presented modelling and controller design procedures are demonstrated on a Multi-Inputs Multi-Outputs (MIMO) simulated pH neutralization process.
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