A Tuning Approach for Offset-free MPC with Conditional Reference Adaptation
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
The 19th World Congress of the International Federation of Automatic Control
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Model predictive control has become a widely accepted strategy in industrial
applications in the recent years. Often mentioned reasons for the success are the optimization
based on a system model, consideration of constraints and an intuitive tuning process. However,
as soon as unknown disturbances or model plant mismatch have to be taken into account the
tuning effort to achieve offset-free tracking increases. In this work a novel approach for offset-free
MPC is presented, which divides the tuning in two steps, the setup of a nominal MPC loop and
an external reference adaptation. The inner nominal loop addresses the performance targets in
the nominal case, decouples the system and essentially leads to a first order response. The second
outer loop enables offset-free tracking in case of unknown disturbances and consists of feedback
controllers adapting the reference. Due to the mentioned properties these controllers can be
tuned separate and by known guidelines. To address conditions with active input constraints,
additionally a conditional reference adaptation scheme is introduced. The tuning strategy is
evaluated on a simulated linear Wood-Berry binary distillation column example.