Large-Inertia Temperature Control Based-On Information Fusion

Abstract

The constant-temperature workshop is important in modernized production. A workshop with the larger space has a larger inertia, the temperature controlled problem is the control system can not be made in a timely control to the temperature, some interferences are difficult to determine and affected heavily by the environmental temperature changes, it is difficult to adopt appropriate measures to control. This paper proposes a model structure fused with the local weather forecast information to accomplish temperature control in the large-inertia constant-temperature workshop. A practical application system is accomplished with DCS (Distributed Control System) structure and general PLC (Programmable Logical Controller). At the same time, The Artificial Neural Network is used to improve the performance of the algorithm. The results show the new system over general systems in large-inertia constant-temperature workshop for more accurate temperature control.