Open AccessSampled‐data MPC for LPV systems with input saturation
Author(s) -
Shi Ting,
Su Hongye
Publication year - 2014
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0205
Subject(s) - control theory (sociology) , sampled data systems , saturation (graph theory) , computer science , mathematics , control system , engineering , control (management) , artificial intelligence , combinatorics , electrical engineering
In this work, a sampled‐data model predictive control (MPC) design method is proposed for continuous‐time linear parameter varying (LPV) systems. The input saturation and parameter uncertainties are both considered. Using a method to deal with actuator saturation, the MPC controller is permitted to saturate. Using the measurable parameter vector, a scheduled state‐feedback MPC controller is computed at each time instant which fully exploits the real‐time information on the variations of the plant characteristics. By modelling the closed‐loop systems of the continuous‐time LPV systems with a piecewise constant sampled‐data control input as linear impulsive systems, the stability properties of the proposed MPC are studied. The sampling interval in this work is not required to be periodic. The proposed MPC design method is expected to further reduce the conservativeness. The improvements of the proposed sampled‐data MPC method w.r.t. other existing MPC techniques are demonstrated by an example.