Interval State Feedback Control for Uncertain Systems Through Regional Pole Assignment With Optimization

Aiming at the problems of interval expansion and mismatch of uncertainty description in the design of interval state feedback controller (ISFCr), this paper proposes a new design method of ISFCr using the regional pole assignment (RPA). In this method, the interval system uncertainty is adjusted to a new formation, and the controller parameters are expressed with the interval’s center and half-width. Then, the linear matrix inequality (LMI) of RPA is extended, resulting in a set of variable order LMIs. A feasible controller is obtained using the multi-objective particle swarm optimization (MOPSO) algorithm after defining the interval width and the stability indicators. The proposed interval controller inherits the advantages of the state feedback controller based on pole assignment, and provides state feedback control sets that stabilize any parameter of the interval system. The effectiveness of the ISFCr is verified through numerical simulations.