Novel interaction prediction approach to hierarchical control of large-scale systems

In this paper, a new interaction prediction approach for hierarchical control of non-linear large-scale systems is presented. The proposed approach uses a new gradient-type coordination scheme which is robust with respect to the parameters' variation, and also has a good convergence rate. In classical coordination strategies, which can be divided into the gradient-type and substitution-type approaches, it is not possible to improve the robustness and the convergence rate at the same time, since by increasing one the other decreases. The proposed approach has the main advantages of the gradient-type algorithms in being independent of the parameter's variation and also the initial guess of the coordination vector. In addition, because of the proposed coordination strategy, in which the update of the coordination vector directly causes the reduction of the coordination error, the number of iterations is considerably reduced. The robustness and convergence rate of the proposed approach against the other interaction prediction approaches are shown through simulations of a benchmark problem. The simulation results also show the effectiveness of the proposed approach in solving constrained optimisation problems having non-quadratic cost functions. Comparisons are also made with the solutions obtained using centralised approach.