Name
Abstract | ||
|---|---|---|
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 system production to the required demand and guaranteeing system stability and boundedness of all signals in the closed-loop system. Modeling errors and discretization effects are taken into account thus rendering the controller robust. A case study demonstrates the efficiency of the proposed technique. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1016/S0005-1098(98)00139-3 | Automatica |
Keywords | Field | DocType |
Manufacturing systems,Neural networks,Adaptive control | Discretization,Control theory,Job shop scheduling,Control theory,Real-time Control System,Control engineering,Flexible manufacturing system,Process control,Adaptive control,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
35 | 1 | 0005-1098 |
Citations | PageRank | References |
6 | 0.72 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| George A. Rovithakis | 1 | 749 | 45.73 |
| Vassilis I. Gaganis | 2 | 6 | 0.72 |
| Stelios E. Perrakis | 3 | 6 | 0.72 |
| manolis a christodoulou | 4 | 461 | 59.94 |