Decentralized receding horizon control for large scale dynamically decoupled systems
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Distributed receding horizon control for multi-vehicle formation stabilization
Automatica (Journal of IFAC)
Technical communique: Stabilizing decentralized model predictive control of nonlinear systems
Automatica (Journal of IFAC)
Robust model predictive control of constrained linear systems with bounded disturbances
Automatica (Journal of IFAC)
Technical communique: Tube-based robust sampled-data MPC for linear continuous-time systems
Automatica (Journal of IFAC)
Block-wise discretization accounting for structural constraints
Automatica (Journal of IFAC)
Hi-index | 22.15 |
This paper presents a novel Distributed Predictive Control (DPC) algorithm for linear discrete-time systems. This method enjoys the following properties: (i) state and input constraints can be considered; (ii) under mild assumptions, convergence of the closed loop control system is proved; (iii) it is not necessary for each subsystem to know the dynamical models of the other subsystems; (iv) the transmission of information is limited, in that each subsystem only needs the reference trajectories of the state variables of its neighbors. A simulation example is reported to illustrate the main characteristics and performance of the algorithm.