Adaptive model predictive process control using neural networks
US5659667A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Jan 17, 1995 |
| Grant date | Aug 19, 1997 |
| Priority date | — |
| Expiry date | Jan 17, 2015 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/063
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.