Adaptive optimal $\ell_\infty$-induced robust stabilization of minimum phase SISO plant under bounded disturbance and coprime factor perturbations

Fuente: arXiv
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Main Author: Sokolov, Victor F.
Format: Preprint
Published: 2022
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author Sokolov, Victor F.
author_facet Sokolov, Victor F.
contents This paper addresses the problem of optimal robust stabilization of a discrete-time minimum-phase plant in the framework of robust control theory in the $\ell_1$ setup and under poor a priori information. Coefficients of the transfer function of the plant nominal model with stable zeros are unknown and belong to a known bounded polyhedron in the space of coefficients. The gains of coprime factor perturbations of the plant and the upper bound of external disturbance are also unknown. The problem under consideration is to design adaptive controller that minimizes, with the prescribed accuracy, the worst-case asymptotic upper bound of the output. Solution of the problem is based on set-membership estimation of unknown parameters and treating the control criterion as the identification criterion. A hard nonconvex problem of on-line computation of optimal estimates is reduced, under additional nonrestrictive assumption, to a linear-fractional programming via a nonlinear transformation of estimated parameters. Despite the non-identifiability of the unknown parameters, the proposed adaptive controller guarantees, with the prescribed accuracy, the same optimal asymptotic upper bound of the output of adaptive system as the optimal controller for the plant with known parameters. In addition to the optimality of adaptive control, the proposed solution provides on-line verification/validation of current estimates and a priori assumptions.
format Preprint
id arxiv_https___arxiv_org_abs_2207_14028
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Adaptive optimal $\ell_\infty$-induced robust stabilization of minimum phase SISO plant under bounded disturbance and coprime factor perturbations
Sokolov, Victor F.
Optimization and Control
Systems and Control
93Cxx, 49Nxx
This paper addresses the problem of optimal robust stabilization of a discrete-time minimum-phase plant in the framework of robust control theory in the $\ell_1$ setup and under poor a priori information. Coefficients of the transfer function of the plant nominal model with stable zeros are unknown and belong to a known bounded polyhedron in the space of coefficients. The gains of coprime factor perturbations of the plant and the upper bound of external disturbance are also unknown. The problem under consideration is to design adaptive controller that minimizes, with the prescribed accuracy, the worst-case asymptotic upper bound of the output. Solution of the problem is based on set-membership estimation of unknown parameters and treating the control criterion as the identification criterion. A hard nonconvex problem of on-line computation of optimal estimates is reduced, under additional nonrestrictive assumption, to a linear-fractional programming via a nonlinear transformation of estimated parameters. Despite the non-identifiability of the unknown parameters, the proposed adaptive controller guarantees, with the prescribed accuracy, the same optimal asymptotic upper bound of the output of adaptive system as the optimal controller for the plant with known parameters. In addition to the optimality of adaptive control, the proposed solution provides on-line verification/validation of current estimates and a priori assumptions.
title Adaptive optimal $\ell_\infty$-induced robust stabilization of minimum phase SISO plant under bounded disturbance and coprime factor perturbations
topic Optimization and Control
Systems and Control
93Cxx, 49Nxx
url https://arxiv.org/abs/2207.14028