Distributed Model Predictive Control for Tracking: A Coalitional Clustering Approach

In this article, a coalitional robust model predictive controller for tracking target sets is presented. The overall system controlled by set of local control agents that dynamically merge into cooperative coalitions or clusters so as to attain an efficient tradeoff between cooperation burden and global performance optimality. Within each cluster, the coordinate their inputs maximize collective performance, while considering coupling effect with external subsystems uncertainty. By using tube-based approach, state driven satisfying input constraints despite changes in controllers’ clustering. Likewise, feasibility stability closed-loop are guaranteed techniques. applicability proposed approach illustrated academic example.