Hierarchical routing control in discrete manufacturing plants via model predictive path allocation and greedy path following

The problem of real-time control and optimization of components' routing in discrete manufacturing plants is considered. This problem features a large number of discrete control inputs and the presence of temporal-logic constraints. A new approach is proposed, with a shift of perspective with respect to previous contributions, from a Eulerian system model that tracks the state of plant nodes, to a Lagrangian model that tracks the state of each part being processed. The approach features a hierarchical structure. At a higher level, a predictive receding horizon strategy allocates a path across the plant to each part in order to minimize a chosen cost criterion. At a lower level, a path following logic computes the control inputs in order to follow the assigned path, while satisfying all constraints. The approach is tested here in simulations, reporting extremely good performance as measured by closed-loop cost function values and computational efficiency.