Method and device for conducting a process in a controlled system with at least one precomputed parameter based on a plurality of results from partial mathematical models combined by a neural network

US5608842A · kind A · utility

Assignee

• Siemens Aktiengesellschaft · DE

Inventors

• Einar Broese · Erlangen, DE
• Otto Gramckow · Uttenreuth, DE
• Thomas Martinetz · Munich, DE
• Guenter Soergel · Nuremberg, DE

Key dates

• Filing date: Nov 10, 1994
• Grant date: Mar 4, 1997
• Expiry date: Nov 10, 2014

Classification

• Technology area (CPC G): Physics
• CPC primary: G05B17/02
• WIPO field: Control
• WIPO sector: Instruments

Abstract

In known methods for conducting a process in an automatically controlled system, the system is preset at the beginning of each process run according to at least one process parameter. The at least one process parameter is precomputed with a model of the process which is supplied with input values. During the process, the input values and the process parameters are measured and are used after the process run to adaptively improve the precomputed value of the process parameters. To simplify and improve the precomputed value of a model having a plurality of partial models, computed results of the partial models are supplied to a neural network. The neural network produces the process parameters to be precomputed as a network response. The network parameters of the neural network are modified after each process run to adapt the precomputed value to the actual process events.