SINGULAR-VALUE-DECOMPOSITION APPROACH TO MULTIVARIABLE GENERALIZED PREDICTIVE CONTROL
A change of basis, from the standard set to the set of eigenvectors, provides the means for the decomposition of a multivariable problem into a set of scalar problems. This idea was deployed in an earlier paper to embed scalar generalized predictive control into the multivariable framework. Eigen-de...
| Những tác giả chính: | , , |
|---|---|
| Định dạng: | Journal article |
| Ngôn ngữ: | English |
| Được phát hành: |
1993
|
| Tóm tắt: | A change of basis, from the standard set to the set of eigenvectors, provides the means for the decomposition of a multivariable problem into a set of scalar problems. This idea was deployed in an earlier paper to embed scalar generalized predictive control into the multivariable framework. Eigen-decompositions, however, can be sensitive to perturbations and cannot be applied to non-square matrices. The paper shows how an analogous approach to multivariable predictive control can be based on a singular-value decomposition, and illustrates its applicability to non-square systems as well as demonstrates its superior sensitivity properties by means of two numerical examples. |
|---|