Nonlinear model predictive control with input-output linearization

Constituting reliable optimal solution is a key issue for the constrained non-linear predictive control. Input/output feedback linearization is a popular method in nonlinear control. By using a non-linear feedback linearizing controller, the original linear input constraints will change to non-linear and state dependent constraints. Considering the state-space continuous-time system, this paper presents an NMPC algorithm to calculate exactly the first control move, which is actually implemented, and to approximate the rest of the control moves, which are not implemented. Simulation results the CSTR demonstrate the effectiveness of the proposed method.