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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bender, D.J. Laub, A.J. |
| Copyright Year | 1985 |
| Description | Author affiliation: University of California, Santa Barbara, CA (Bender, D.J.; Laub, A.J.) |
| Abstract | In this paper we investigate the linear-quadratic optimal regulator problem for the continuous-time descriptor system Ex = Ax + Bu where E is, in general, a singular matrix. The infinite-horizon version of this problem was previously solved by Cobb [5] by a quite different approach. We solve a somewhat more general finite-horizon problem by applying Hamiltonian minimization to derive the optimal trajectory of the vector consisting of the concatenated descriptor, codescriptor, and control vectors. From this trajectory the optimal feedback gain relating the control and descriptor variable can be computed. By transforming to a coordinate system which can be computed by performing a singular value decomposition of E, we derive a Riccati differential equation whose solution gives the optimal cost. The steady-state optimal feedback gain can be computed by solving an eigenvalue eigenvector problem formulated from the untransformed system parameters. In general there does not exist a unique optimal feedback gain but a linear variety whose dimension is equal to the number of inputs times the rank deficiency of E. A more complete version of this paper has been submitted for publication [3]. |
| Starting Page | 957 |
| Ending Page | 962 |
| File Size | 588656 |
| Page Count | 6 |
| File Format | |
| DOI | 10.1109/CDC.1985.268642 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1985-12-11 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Regulators Feedback Optimal control Concatenated codes Singular value decomposition Riccati equations Differential equations Cost function Steady-state Eigenvalues and eigenfunctions |
| Content Type | Text |
| Resource Type | Article |
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