Abstract
AbstractWe apply a recent result from Lazar and Heemels. [2009] that analytically relates a model predictive control suboptimal solution to performance loss in order to quantify the number of iterations necessary for the incremental primal decomposition algorithm to achieve a solution that guarantees stability. We use this result to explore the idea of “incremental robustness”, meaning that the overall system is robustly stable and its performance varies gracefully with the inclusion of sub-systems and sub-controllers. We demonstrate these ideas in a consensus seeking problem and provide simulation results. To our best knowledge, this is the first time the result in Lazar and Heemels. [2009] is applied to a distributed model predictive control framework based on primal decomposition.
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