Structural and Parametric Synthesis of a Hybrid Repetitive Control System for Uncertain Multi-Mode Plant

Article deals with the problem of constructing a hybrid adaptive-robust repetitive control system for one class of a MIMO plants which operating with structural and parametric uncertainty and constant action of an external disturbances. A procedure for structural and parametric synthesis of a control system is proposed. At the structural synthesis stage with the help of hyperstability criterion the authors are developing a decentralized combined controller. After that using the method of continuous models the authors are built a continuous-discrete control system. The main feature of a control loop structure synthesis stage is to ensure the validity of V. M. Popov’s integral inequality. For this purpose, the authors determining the special estimates that guarantee positivity for nonlinear non-stationary part of the system under consideration. At the system’s parametric synthesis stage the authors are use the environment of engineering and technical calculations "Matlab — Simulink" to perform optimization modeling of the continuous and hybrid repetitive control systems. This action is carried out using one of the functional optimization methods — a genetic algorithm. Authors use the criterion of generalized operation for automatic control systems to form the functionality for assessing the quality of the proposed system. At the simulation stage initially for continuous repetitive system it was searched its controller parameters which ensure the minimum value of the specified functional. Then, with a given discretization step of the control loop elements, the hybrid periodic system was optimized in order to improve the quality of its operation.

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Publication Details

Journal
Mekhatronika Avtomatizatsiya Upravlenie
Published
2024-09-05
DOI
https://doi.org/10.17587/mau.25.447-457
Citations
1
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
0.33
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article

Structural and Parametric Synthesis of a Hybrid Repetitive Control System for Uncertain Multi-Mode Plant

S. A. Smirnova, E. A. Shelenok, Е. Л. Еремин
1 citations
Mekhatronika Avtomatizatsiya Upravlenie
Iterative Learning Control Systems
0.33
article

Structural and Parametric Synthesis of a Hybrid Repetitive Control System for Uncertain Multi-Mode Plant

S. A. Smirnova, E. A. Shelenok, Е. Л. Еремин
article en
1 citations

Abstract

Article deals with the problem of constructing a hybrid adaptive-robust repetitive control system for one class of a MIMO plants which operating with structural and parametric uncertainty and constant action of an external disturbances. A procedure for structural and parametric synthesis of a control system is proposed. At the structural synthesis stage with the help of hyperstability criterion the authors are developing a decentralized combined controller. After that using the method of continuous models the authors are built a continuous-discrete control system. The main feature of a control loop structure synthesis stage is to ensure the validity of V. M. Popov’s integral inequality. For this purpose, the authors determining the special estimates that guarantee positivity for nonlinear non-stationary part of the system under consideration. At the system’s parametric synthesis stage the authors are use the environment of engineering and technical calculations "Matlab — Simulink" to perform optimization modeling of the continuous and hybrid repetitive control systems. This action is carried out using one of the functional optimization methods — a genetic algorithm. Authors use the criterion of generalized operation for automatic control systems to form the functionality for assessing the quality of the proposed system. At the simulation stage initially for continuous repetitive system it was searched its controller parameters which ensure the minimum value of the specified functional. Then, with a given discretization step of the control loop elements, the hybrid periodic system was optimized in order to improve the quality of its operation.

Mekhatronika Avtomatizatsiya UpravlenieVol. 25(9)
Amur State University (RU)
Openalex Percentile: Top 42%
Iterative Learning Control Systems
0.33
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