Method and device for conducting a process in a controlled system with at least one precomputed process parameter determined using a mathematical model having variable model parameters adjusted based on a network response of a neural network

US5673368A · 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: Sep 30, 1997
• Expiry date: Nov 10, 2014

Classification

• Technology area (CPC B): Performing Operations; Transporting
• CPC primary: B21B2261/20
• WIPO field: Materials, metallurgy
• WIPO sector: Chemistry

Abstract

In known processes for conducting a process in an automatically controlled system, the system is preset at the beginning of each process run based on at least one process parameter. The at least one process parameter is precomputed with a model of the process, containing at least one model parameter and input values supplied to the model. During the process, the input values and the process parameter are measured and used to adaptively improve the precomputed process parameter after the process run. A neural network is used to determine the model parameters whose dependence on the input values is unknown or insufficiently known. Network parameters of the neural network are modified after each process run to adapt the model to the actual process events.