Approximation of stable systems by laguerre filters
Automatica (Journal of IFAC)
Discrete-time LQG dynamic controller design using plant Markov parameters
Automatica (Journal of IFAC)
System identification with generalized orthonormal basis functions
Automatica (Journal of IFAC) - Special issue on trends in system identification
On approximation of stable linear dynamical systems using Laguerre and Kautz functions
Automatica (Journal of IFAC)
L∞ system approximation algorithms generated by 4 summations
Automatica (Journal of IFAC)
Paper: Model predictive heuristic control
Automatica (Journal of IFAC)
Extended Ho-Kalman algorithm for systems represented in generalized orthonormal bases
Automatica (Journal of IFAC)
A new modeling approach of MIMO linear systems using the generalized orthonormal basis functions
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
A new estimation method of the poles for the generalized orthonormal bases filters
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
A new modeling approach of MIMO linear systems using the generalized orthonormal basis functions
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
A new estimation method of the poles for the generalized orthonormal bases filters
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
Hi-index | 22.15 |
A solution is presented for the problem of realizing a discrete-time LTI state-space model of minimal McMillan degree such that its first N expansion coefficients in terms of generalized orthonormal basis match a given sequence. The basis considered, also known as the Hambo basis, can be viewed as a generalization of the more familiar Laguerre and two-parameter Kautz constructions, allowing general dynamic information to be incorporated in the basis. For the solution of the problem use is made of the properties of the Hambo operator transform theory that underlies the basis function expansion. As corollary results compact expressions are found by which the Hambo transform and its inverse can be computed efficiently. The resulting realization algorithms can be applied in an approximative sense, for instance, for computing a low-order model from a large basis function expansion that is obtained in an identification experiment.