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JOURNALS // Vestnik Sankt-Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika. Informatika. Protsessy Upravleniya // Archive

Vestnik S.-Petersburg Univ. Ser. 10. Prikl. Mat. Inform. Prots. Upr., 2023 Volume 19, Issue 1, Pages 109–119 (Mi vspui570)

This article is cited in 1 paper

Control processes

Optimization approach to the design of nonlinear control system controllers

S. V. Zavadskiy, D. A. Ovsyannikov, D. D. Melnikov

St. Petersburg State University, 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation

Abstract: The optimization approach is applied to the synthesis and optimization of nonlinear real-time feedback optimal control system of a certain Maglev platform. To optimize the nonlinear control law, the integral functional criteria is minimized, which evaluates the quality of the dynamics of not one trajectory, but an ensemble of nonlinear trajectories of the system. The considered ensemble of trajectories covers the entire area of the engineering gap between the platform and the guide rails. In this area the magnetic forces provide highly nonlinear effects due to the considered design features of the object. At the same time, it is required to provide the stabilization within the entire engineering gap. It makes this statement to be a multi-input nonlinear control problem. The components of the feedback control law vector have a polynomial form of the state-space variables. As a result of computational optimization of trajectories ensemble, a class of Pareto-optimal polynomial regulators is constructed for considered control object. In the presented set, each Pareto-optimal point corresponds to a specific designed controller and investigated functional criteria which evaluates the entire ensemble of perturbed nonlinear trajectories. This allows a research engineer to choose various nonlinear regulators and achieve a compromise between stabilization accuracy and energy costs.

Keywords: nonlinear system, stabilization, nonlinear regulators, Maglev, real-time feedback, ensemble of trajectories, optimization.

UDC: 517.977.58

MSC: 49N35

Received: December 17, 2022
Accepted: January 19, 2023

Language: English

DOI: 10.21638/11701/spbu10.2023.109



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