Distributed partial output consensus optimization for constrained chain interconnected systems

For chain interconnected systems with state and input constraints, a partial output consensus (POC) optimization problem is studied when the set-points are infeasible. In this case, outputs with and without consensus requirements cannot converge to the set-points achieved from real-time optimization. For this case, a novel set-point optimization method is developed, which is called distributed partial output consensus optimization. Based on this method, the set-points for two-part outputs i.e. having a part that must achieve consensus and a part that has a set-point, can be recalculated simultaneously and their feasibility can be ensured by using a distributed projection operator. The convergence of the strategy is then analyzed. From the results of both simulation and experimental testing, the effectiveness of the proposed method is validated.