Abstract: This paper presents a new adaptive DMC controller
that improves the controller performance in case of plant-model
mismatch. The new controller monitors the plant measured output,
compares it with the model output and calculates weights applied to
the controller move. Simulations show that the new controller can
help improve control performance and avoid instability in case of
severe model mismatches.
Abstract: A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.