Multi-agent model predictive control for transportation networks: Serial versus parallel schemes
Engineering Applications of Artificial Intelligence
Brief paper: MPC for tracking piecewise constant references for constrained linear systems
Automatica (Journal of IFAC)
Dynamic dual decomposition for distributed control
ACC'09 Proceedings of the 2009 conference on American Control Conference
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Technical communique: Stabilizing decentralized model predictive control of nonlinear systems
Automatica (Journal of IFAC)
Hi-index | 22.14 |
This paper proposes a cooperative distributed linear model predictive control (MPC) strategy for tracking changing setpoints, applicable to any finite number of subsystems. The proposed controller is able to drive the whole system to any admissible setpoint in an admissible way, ensuring feasibility under any change of setpoint. It also provides a larger domain of attraction than standard distributed MPC for regulation, due to the particular terminal constraint. Moreover, the controller ensures convergence to the centralized optimum, even in the case of coupled constraints. This is possible thanks to the warm start used to initialize the optimization Algorithm, and to the design of the cost function, which integrates a Steady-State Target Optimizer (SSTO). The controller is applied to a real four-tank plant.