Neural network including input normalization for use in a closed loop control system
US6078843A · kind A · utility
Assignee
Inventor
Key dates
| Filing date | Jan 24, 1997 |
| Grant date | Jun 20, 2000 |
| Priority date | — |
| Expiry date | Jan 24, 2017 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B13/027
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
An apparatus and method for controlling a process using a neural network which operates as part of a closed loop control system. The state of the control system is defined by one or more process condition signals and monitored for a predetermined set of controller parameters. The output of the control system is one or more device control signals, used by a control device to alter a process being controlled. The neural network uses normalized values of process condition signals in combination with a predetermined set of controller parameters to produce correction control signals. The correction control signals are then used to the create device control signals. Proper normalization of at least one of the process condition signals using the throttling range set by the controller parameters is necessary. The remaining input signals must be normalized as well, but the method of normalization is not as critical, except to create a common range for all process condition signals input to the neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.