Parameter identification technique for multivariate stochastic systems
โ Scribed by Hajime Akashi; Hiroyuki Imai; Kamal A.F. Moustafa
- Publisher
- Elsevier Science
- Year
- 1979
- Tongue
- English
- Weight
- 388 KB
- Volume
- 15
- Category
- Article
- ISSN
- 0005-1098
No coin nor oath required. For personal study only.
โฆ Synopsis
This paper considers the problem of obtaining accurate estimates of multivariate systems with reasonable computations. To avoid the structural identification problem which is associated with multivariate systems, we observe the system by a linear combination of the outputs. The two stage least square method is employed to estimate the model parameters. An optimum combination of the outputs is obtained such that the parameter estimates have the least asymptotic generalized variance. Computer simulations are provided to illustrate the usefulness of the proposed method.
๐ SIMILAR VOLUMES
An identification technique is devised for SDOF dynamical mechanical systems under random excitations. The system is assumed to be governed by a non-linear equation of motion in general form, in which the restoring force and the dissipative terms are given by arbitrary power functions. Algebraic equ
An algorithm is proposed for suboptimal control of linear multivariable systems with unknown parameters and output noise covariances. This algorithm is based on the idea of explicitly separating the functions of identification, estimation and control. The parameters and states of the system are esti
This paper describes an algorithm for the structure determination and parameter identification of linear discretetime multivariable systems from input-output measurements. The algorithm starts by determining the structure parameters of a certain canonical state space representation from an estimate