Robust extrapolation in discrete systems with interval parameters using algorithms for estimating unknown input | Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitelnaja tehnika i informatika – Tomsk State University Journal of Control and Computer Science. 2022. № 59. DOI: 10.17223/19988605/59/5

Robust extrapolation in discrete systems with interval parameters using algorithms for estimating unknown input

The problem of synthesizing an extrapolator for a discrete object with interval parameters is considered. The problem is solved on the basis of a probabilistic approach, which is based on the replacement of uncertain parameters of an interval type with independent random variables with a uniform distribution law. The problem is solved using the separation principle, recurrent algorithms, the least squares method and smoothing procedures. Contribution of the authors: the authors contributed equally to this article. The authors declare no conflicts of interests.

Download file

Counter downloads: 29

Keywords

Robust extrapolation estimates, discrete system, unknown input, interval parameters, least-squares

Authors

Name	Organization	E-mail
Kim Konstantin S.	Tomsk State University	kks93@rambler.ru
Smagin Valery I.	Tomsk State University	vsm@mail.tsu.ru

Всего: 2

References

Wang Y., Bevly D., Rajamani R.Interval observer design for LPV systems with parametric uncertainty // Automatica. 2015. V. 60. P. 79-85.

Abolhasani M., Rahmani M. Robust Kalman filtering for discrete-time systems with stochastic uncertain time-varying parameters // Electronics Letters. 2017. V. 53. No. 3. P. 146-148.

Ichalal D., Marx B., Maquin D., Ragot J. State estimation of system with bounded uncertain parameters: interval multi-model approach // International Journal of Adaptive Control and Signal Processing. 2018. V. 32 (3). P. 480-493.

Hattab O., Franchek M.A., Grigoriadis K. Observer based parameter estimation for linear uncertain discrete-time systems //j. of Engineering Research and Application. 2018. V. 8, is. 10 (part II). P. 51-60. doi: 10.9790/9622-0810025160

Wang Z., Lim C., Shen Y.Interval observer design for uncertain discrete time linear systems // Systems & Control Letters. 2018. V. 116. P. 41-46.

Rocha K.D.T., Terra M.H. Robust Kalman filter for systems subject to parametric uncertainties // Systems & Control Letters. 2021. V. 157. Art. 105034.

Ким К.С., Смагин В.И. Экстраполяция в дискретных системах с мультипликативными возмущениями при неполной ин формации // Вестник Томского государственного университета. Управление, вычислительная техника и информатика. 2019. № 47. С. 49-56.

Janczak D., Grishin Yu. State estimation of linear dynamic system with unknown input and uncertain observation using dynamic programming // Control and Cybernetics. 2006. № 4. P. 851-862.

Gillijns S., Moor B. Unbiased minimum-variance input and state estimation for linear discrete-time systems // Automatica. 2007. V. 43. P. 111-116.

Hsien C.-S. On the optimality of two-stage Kalman filter for systems with unknown input // Asian J. of Control. 2010. V. 12, № 4. P. 510-523.

Witczak M. Fault diagnosis and fault-tolerant control strategies for non-linear systems : Analytical and Soft Computing Approaches. Springer International Publishing, 2014. 239 p. (Lecture Notes in Electrical Engineering; v. 266).

Smagin V.I. State estimation for nonstationary discrete systems with unknown input using compensations // Russian Physics Journal. 2015. V. 58, is. 7. P. 1010-1017.

Smagin V.I. Prediction of states of discrete systems with unknown input of the model using compensation // Russian Physics Journal. 2017. V. 59, is. 9, P. 1507-1514.

Smagin V.I., Koshkin G.M. Kalman filtering and control algorithms for systems with unknown disturbances and parameters using nonparametric technique // Proceedings 20th International Conference on Methods and Models in Automation and Robotics (MMAR 2015), 24-27 August, Miedzyzdroje, Poland. 2015. P. 247-251.

Barmish B.R., Polyak B.T. A new approach to open robustness problems based on probabilistic predication formulae // Proc. 13th World IFAC Congr., 30 June - 5 July, San Francisco, USA. 1996. V. H. P. 1-6.

Mukhina O.O., Smagin V.I. Locally Optimal Control for Discrete Time Delay Systems with Interval Parameters // Communications in Computer and Information Science. 2014. V. CCIS 487. P. 301-311.

Athans M. The matrix minimum principle // Informat. and Contr. 1968. V. 11. P. 592-606.