Patent · US Expired

Method and apparatus for training a system model with gain constraints

US7058617B1 · kind B1 · utility

58Cited by
4References
18Claims
0Family size

Assignee

Inventors

Key dates

Filing dateSep 14, 2000
Grant dateJun 6, 2006
Priority date
Expiry dateJan 3, 2022

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG05B17/02
  • WIPO fieldControl
  • WIPO sectorInstruments

Abstract

Method and apparatus for training a system model with gain constraints. A method is disclosed for training a steady-state model, the model having an input and an output and a mapping layer for mapping the input to the output through a stored representation of a system. A training data set is provided having a set of input data u(t) and target output data y(t) representative of the operation of a system. The model is trained with a predetermined training algorithm which is constrained to maintain the sensitivity of the output with respect to the input substantially within user defined constraint bounds by iteratively minimizing an objective function as a function of a data objective and a constraint objective. The data objective has a data fitting learning rate and the constraint objective has constraint learning rate that are varied as a function of the values of the data objective and the constraint objective after selective iterative steps.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.