Constrained neural model predictive control with guaranteed free offset

An extended model-based predictive control scheme is proposed and implemented on a bench three-tanks system. This structure is based on a constrained local instantaneous linear model-based predictive controller complemented with a static offset compensator for guaranteeing that tracking errors converge to zero in a finite time. A nonlinear state-space neural network architecture trained offline is used for modelling purposes and forming a seed from where linear models are extracted at each sampling time. Results from experiments show that this extended model-based predictive control (MPC) scheme ensures a good tracking performance with zero steady-state offsets, in spite of modelling errors.