Title :
State-feedback MPC with piecewise constant control for continuous-time nonlinear systems
Author :
Magni, L. ; Scattolini, R.
Author_Institution :
Dipt. di Inf. e Sistemistica, Pavia Univ., Italy
Abstract :
A new model predictive control (MPC) algorithm for nonlinear systems is presented. The plant under control, the state and control constraints and the performance index to be minimized are described in continuous time, while the manipulated Variables are allowed to change at fixed and uniformly distributed sampling times. In so doing, the optimization is performed with respect to sequences, as in discrete time nonlinear MPC, but the continuous time evolution of the system is considered and the approximate plant discretization is avoided, as in continuous time nonlinear MPC.
Keywords :
continuous time systems; discrete time systems; nonlinear control systems; optimisation; performance index; piecewise constant techniques; predictive control; state feedback; approximate plant; continuous time; continuous time nonlinear systems; control constraints; discrete time nonlinear control; distributed sampling times; manipulated variables; model predictive control algorithm; nonlinear systems; optimization; performance index; piecewise constant control; state constraints; state feedback; Control systems; Nonlinear control systems; Nonlinear systems; Optimization methods; Performance analysis; Prediction algorithms; Predictive control; Predictive models; Sampling methods; Stability;
Conference_Titel :
Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
Print_ISBN :
0-7803-7516-5
DOI :
10.1109/CDC.2002.1185107
