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This paper presents a new formulation and synthesis approach for stabilizing cooperative distributed model predictive control (MPC) for networks of linear systems, which are coupled in their dynamics. The controller is defined by a network-wide constrained optimal control problem, which is solved online by distributed optimization. The main challenge is the definition of a global MPC problem, which...
Some aerial tasks are achieved more efficiently and at a lower cost by a group of independently controlled micro aerial vehicles (MAVs) when compared to a single, more sophisticated robot. Controlling formation flight can be cast as a two-level problem: stabilization of relative distances of agents (formation shape control) and control of the center of gravity of the formation. To date, accurate shape...
This paper provides a framework for distributed tracking of piecewise constant references for a network of constrained linear systems which act cooperatively. It is shown how the tracking problem can be posed as a distributed optimization problem and a method for distributed synthesis of the control law is presented. In particular, the notion of a distributed invariant set for tracking is introduced,...
In this work, synthesis and closed-loop operation of robust distributed model predictive control (MPC) for linear systems using distributed optimization is discussed. Previous work has shown that a nominal MPC controller for this setup can be synthesized and operated in a purely distributed manner. This paper extends this concept to linear systems subject to additive bounded disturbance. It is shown...
This paper presents a systematic computational study on the performance of distributed optimization in model predictive control (MPC). We consider networks of dynamically coupled systems, which are subject to input and state constraints. The resulting MPC problem is structured according to the system's dynamics, which makes the problem suitable for distributed optimization. The influence of fundamental...
This work presents an approach for both distributed synthesis and control for a network of discrete-time constrained linear systems without central coordinator. Every system in the network is dynamically coupled to a number of neighboring systems and it is assumed that communication among neighbors is possible. A model predictive controller based on distributed optimization is introduced, by which...
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