In this paper, an approach to low complexity distributed MPC of linear interconnected systems with coupled dynamics subject to both state and input constraints is proposed. The suggested approach is based on the idea of introducing a contractive set constraint in the centralized MPC problem formulation, which would guarantee the closed-loop system stability when using a small prediction horizon. Then, a dual accelerated gradient method is applied to obtain distributedly a suboptimal solution of the resulting Quadratic Programming problem. The suggested approach would be appropriate for embedded distributed MPC since it will reduce the complexity of the on-line MPC computations, simplify the software implementation, and reduce the requiremen...
In the article, we study the distributed model predictive control (DMPC) problem for a network of li...
Decentralized and distributed model predictive control (DMPC) addresses the problem of controlling a...
In this paper we propose an application of distributed model predictive control techniques to the pr...
In this paper, an approach to low complexity distributed MPC of linear interconnected systems with c...
An approach to low complexity distributed MPC of nonlinear interconnected systems with coupled dynam...
Theory for Distributed Model Predictive Control (DMPC) is developed based on dual decomposition of t...
A suboptimal approach to distributed NMPC for nonlinear interconnected systems subject to constraint...
A novel distributed model predictive control (DMPC) strategy with time-varying terminal set for line...
In this paper, sequential nonlinear Distributed Model Predictive Control (DMPC) algorithms for large...
International audienceA suboptimal approach to distributed robust MPC for uncertain systems consisti...
This paper proposes a decoupling strategy for the Distributed Model Predictive Control (DMPC) for a ...
We present a stopping condition to the duality based distributed optimization algorithm presented in...
We address the problem of efficient implementations of distributed Model Predictive Control (MPC) sy...
A tube-based distributed model predictive control (DMPC) scheme is proposed for dynamically coupled ...
ISBN : 978-94-007-7006-5In this chapter, we propose a distributed model predictive control scheme ba...
In the article, we study the distributed model predictive control (DMPC) problem for a network of li...
Decentralized and distributed model predictive control (DMPC) addresses the problem of controlling a...
In this paper we propose an application of distributed model predictive control techniques to the pr...
In this paper, an approach to low complexity distributed MPC of linear interconnected systems with c...
An approach to low complexity distributed MPC of nonlinear interconnected systems with coupled dynam...
Theory for Distributed Model Predictive Control (DMPC) is developed based on dual decomposition of t...
A suboptimal approach to distributed NMPC for nonlinear interconnected systems subject to constraint...
A novel distributed model predictive control (DMPC) strategy with time-varying terminal set for line...
In this paper, sequential nonlinear Distributed Model Predictive Control (DMPC) algorithms for large...
International audienceA suboptimal approach to distributed robust MPC for uncertain systems consisti...
This paper proposes a decoupling strategy for the Distributed Model Predictive Control (DMPC) for a ...
We present a stopping condition to the duality based distributed optimization algorithm presented in...
We address the problem of efficient implementations of distributed Model Predictive Control (MPC) sy...
A tube-based distributed model predictive control (DMPC) scheme is proposed for dynamically coupled ...
ISBN : 978-94-007-7006-5In this chapter, we propose a distributed model predictive control scheme ba...
In the article, we study the distributed model predictive control (DMPC) problem for a network of li...
Decentralized and distributed model predictive control (DMPC) addresses the problem of controlling a...
In this paper we propose an application of distributed model predictive control techniques to the pr...