A new bandwidth scheduling method for networked learning control

In this paper, the optimal bandwidth allocation scheduling problem for two-layer networked learning control systems (NLCSs) is studied. In NLCS, multiple networked feedback control loops share a common communication channel and they compete to bid for available bandwidth. A non-cooperative game fairness model is first formulated, which takes into consideration of a number of factors, such as transmission data rate, control sampling strategy and scheduling pattern. Then, a novel two-layer hierarchical market competition algorithm (THMCA) is proposed. Two hierarchical population individuals are defined in the algorithm, namely the holding companies and the subsidiary companies which altogether form conglomerates. Market competitions among these conglomerates lead to the convergence to a monopoly at the end, resulting in an optimal solution of the above problem. The algorithm is shown to have a high convergence rate and the comparison simulation results on a NLCS with up to 100 subsystems have demonstrated the effectiveness of the proposed method.