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In this paper we investigate lagrangian duality for a class of mixed integer programs which is of wide practical interest as it appears in many application domains, such as power systems or logistics. For this problem structure, we provide a new solution method that is simple to implement, is distributable and has convergence and performance guarantees. To obtain it, we borrow ideas and results from...
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...
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