Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Brief paper: The minimal disturbance invariant set: Outer approximations via its partial sums
Automatica (Journal of IFAC)
Decentralized receding horizon control for large scale dynamically decoupled systems
Automatica (Journal of IFAC)
Hybrid decentralized control of large scale systems
HSCC'05 Proceedings of the 8th international conference on Hybrid Systems: computation and control
A Quasi-Infinite Horizon Nonlinear Model Predictive Control Scheme with Guaranteed Stability
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Input-to-state stability for discrete-time nonlinear systems
Automatica (Journal of IFAC)
Optimization over state feedback policies for robust control with constraints
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)
| Hi-index | 22.14 |
This paper considers the distributed model predictive control (DMPC) of systems with interacting subsystems having decoupled dynamics and constraints but coupled costs. An easily-verifiable constraint is introduced to ensure asymptotic stability of the overall system in the absence of disturbance. The constraint introduced has a parameter which allows for the performance of the DMPC system to approach that controlled by a centralized model predictive controller. When the subsystems are linear and additive disturbance is present, the added constraint ensures the state of each subsystem converges to its respective minimal disturbance invariant set. The approach is demonstrated via several numerical examples.