A Comparative Study Between Linear and Affine Multi-Model in Predictive Control of a Nonlinear Dynamic System

Model Predictive Control (MPC) is the most successful control strategy that coped in many areas. However, the success of an MPC scheme lies in the accuracy of the adopted prediction model. This paper treats the problem of MPC when there is a need to a larger domain of set-point values and best tracking performances. It presents a novel modeling structure for representing a nonlinear dynamic system based on its static nonlinear characteristic. Then, the Multiple Affine Model (MAM) structure is compared to Multiple Linear Models (MLM) in a Linear MPC (LMPC) scheme. It is noted that the MAM structure offers more precision for modeling and the much smaller number of models. Therefore, it guarantees the best tracking performances in terms of stability, speed and accuracy.

@article{Mezrigui2024,
  title     = {A Comparative Study Between Linear and Affine Multi-Model in Predictive Control of a Nonlinear Dynamic System},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {6},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Houda Mezrigui and Wassila Chagra and Maher Ben Hariz},
  doi       = {10.14569/IJACSA.2024.01506127},
  url       = {https://doi.org/10.14569/IJACSA.2024.01506127}
}