Method and apparatus for analyzing a neural network within desired operating parameter constraints
US5781432A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Dec 4, 1996 |
| Grant date | Jul 14, 1998 |
| Priority date | — |
| Expiry date | Dec 4, 2016 |
Classification
- Technology area (CPC F)Mechanical Engineering; Lighting; Heating
- CPC primaryF23N2223/44
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A distributed control system (14) receives on the input thereof the control inputs and then outputs control signals to a plant (10) for the operation thereof. The measured variables of the plant and the control inputs are input to a predictive model (34) that operates in conjunction with an inverse model (36) to generate predicted control inputs. The predicted control inputs are processed through a filter (46) to apply hard constraints, the values of which are received from a control parameter block (22). During operation, predetermined criterion stored in the control parameter block (22) are utilized by a cost minimization block (42) to generate an error control signal which is minimized by the inverse model (36) to generate the control signals. The system works in two modes, an analyze mode and a runtime mode. In the analyze mode, the predictive model (34) and the inverse model (36) are connected to either training data or simulated data from the analyzer (30) and the operation of the plant (10) evaluated. The values of the hard constraints in filter (46) and the criterion utilized for the cost minimization (42) can then be varied to change the constraints on the control signals …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.