Abstract
In this paper, a novel combination of a multi-model predictive controller (MMPC) and an adaptive integral controller is usedto achieve offset-free control of a nonlinear process. The idea is to avoid the more complex tuning that comes with an offset-free control based on an observer. To create an easily tuned controller based on a piecewise linear (PWL) description of an MPC setup, which utilizes a Bayesian weighting approach. The PWL models are also used to design the separate the I-controller that is made adaptive by using the Bayesian weighting again. The MPC and the I-controller are then acting in parallel. The setup is implemented and tested using a simulation of a pH neutralization process.