Model Predictive control of multi-input multi-output systems

In this work, a novel method is constructed for model predictive control (MPC) of Multi-Input Multi-Output (MIMO) systems. These latter are represented by a discrete-time MIMO ARX model expansion on Laguerre orthonormal bases. The resulting model entitled MIMO ARX-Laguerre model, provides a recursive representation with parameter number reduction. The recursive formulation of the MIMO ARX-Laguerre model is used to obtain the MPC strategy and to synthesizing an adaptive predictive controller of MIMO systems. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithm of both model parameters and Laguerre poles.

Autorentext

Abdelkader MBAREK received his Ph.D degree from ENIT, Tunisia in 2008, his Habilitation degree from Monastir university in 2020. He is now Assistant professor in Electrical and Computer Engineering at ENIM, Tunisia. His research interests include modeling and identification, predictive control, fault diagnosis, fault tolerant control, etc.