Title :
Distributed model predictive control with actuator saturation for Markovian jump linear system
Author :
Yan Song ; Haifeng Lou ; Shuai Liu
Author_Institution :
Dept. of Control Sci. & Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
Abstract :
This paper is concerned with the distributed model predictive control (MPC) problem for a class of discrete-time Markovian jump linear systems (MJLSs) subject to actuator saturation and polytopic uncertainty in system matrices. The global system is decomposed into several subsystems which coordinate with each other. A set of distributed controllers is designed by solving a min-max optimization problem in terms of the solutions of linear matrix inequalities (LMIs). An iterative algorithm is developed to achieve the online computation. Finally, a simulation example is employed to show the effectiveness of the proposed algorithm.
Keywords :
Markov processes; actuators; control system synthesis; discrete time systems; iterative methods; linear matrix inequalities; linear systems; minimax techniques; predictive control; uncertain systems; LMI; MJLS; MPC; actuator saturation; discrete-time Markovian jump linear systems; distributed controller design; iterative algorithm; linear matrix inequalities; min-max optimization problem; model predictive control; polytopic uncertainty; system matrix; Actuators; Cost function; Linear systems; Predictive control; State feedback; Symmetric matrices; Upper bound; Distributed model predictive control (MPC); Markovian jump linear system (MJLS); actuator saturation; linear matrix inequality (LMI);
Journal_Title :
Automatica Sinica, IEEE/CAA Journal of
