Dynamic neural networks for real time adaptive control of FMS

In this paper, a control aspect of the non-acyclic FMS scheduling problem is considered. Based on a dynamic neural network model derived herein, an adaptive, continuous time neural network controller is constructed. The actual dispatching times are determined from the continuous control input discretization. The controller is capable of driving the system production to the required demand and guarantees system stability and boundedness of all signals in the closed loop. Modeling errors and discretization effects are taken into account thus rendering the controller robust. A case study demonstrates the efficiency of the proposed technique.