Synthesis methods for controlling multiscale processes with predictive models with incomplete information
( Pp. 52-56)
More about authors
Nguyen Khac Tung
aspirant
ITMO University Zhilenkov Anton A. kandidat tehnicheskih nauk, docent; zaveduyuschiy kafedroy morskoy elektroniki
St. Petersburg State Marine Technical University Dang Binh Khac aspirant
ITMO University
ITMO University Zhilenkov Anton A. kandidat tehnicheskih nauk, docent; zaveduyuschiy kafedroy morskoy elektroniki
St. Petersburg State Marine Technical University Dang Binh Khac aspirant
ITMO University
Abstract:
Methods for the synthesis of control of multi-scale processes with predictive models for linear and non-linear systems, as well as with various restrictions on the target functional of the system, including the case with terminal restrictions, are considered. This problem is relevant in the modeling and control of technological processes for growing nanoscale structures. A description is given of a control scheme in which the current control action is obtained by solving at each instant of the sample the optimal control problem with a finite horizon without feedback and using the current state of the object as the initial state. An optimization problem is described that gives an optimal control sequence when the control obtained for the first step of the subsequent sequence is applied to the object. The main differences from traditional control schemes that use a pre-computed control law are described.
How to Cite:
Nguyen K.T., Zhilenkov A.A., Dang B.K., (2020), SYNTHESIS METHODS FOR CONTROLLING MULTISCALE PROCESSES WITH PREDICTIVE MODELS WITH INCOMPLETE INFORMATION. Computational Nanotechnology, 1 => 52-56.
Reference list:
Mayne D.Q., Rawlings J.B., Rao C.V., Scokaert P.O.M. Constrained model predictive control: stability and optimality. Automatica. 2000. No. 26 (6). Pp. 789-814.
Pham H.D.D. Model predictive control and apply to adaptive control ship heading. 2008. Pp. 101-106.
Zhilenkov A., Chernyi S. Models and algorithms of the positioning and trajectory stabilisation system with elements of structural analysis for robotic applications. International Journal of Embedded Systems. 2019. No. 11 (6). P. 806. DOI: 10.1504/ijes.2019.104005 (Zhilenkov Chernyi, 2019).
Sokolov S., Zhilenkov A., Chernyi S. et al. Dynamics models of synchronized piecewise linear discrete chaotic systems of high order. Symmetry. 2019. No. 11 (2). P. 236. DOI: 10.3390/sym11020236 (Sokolov, Zhilenkov, Chernyi, Nyrkov Mamunts, 2019).
Pham H.D.D. Model predictive control and apply to adaptive control ship heading. 2008. Pp. 101-106.
Zhilenkov A., Chernyi S. Models and algorithms of the positioning and trajectory stabilisation system with elements of structural analysis for robotic applications. International Journal of Embedded Systems. 2019. No. 11 (6). P. 806. DOI: 10.1504/ijes.2019.104005 (Zhilenkov Chernyi, 2019).
Sokolov S., Zhilenkov A., Chernyi S. et al. Dynamics models of synchronized piecewise linear discrete chaotic systems of high order. Symmetry. 2019. No. 11 (2). P. 236. DOI: 10.3390/sym11020236 (Sokolov, Zhilenkov, Chernyi, Nyrkov Mamunts, 2019).
Keywords:
control system, predictive model, multi-scale processes, incompleteness of information.
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