Multi-objective optimization configuration of redundant electromagnetic actuators in fault-tolerant control of active magnetic bearing system
Fault-tolerant control of active magnetic bearing (AMB) systems with redundant electromagnetic actuators (EMAs) based on generalized bias current linearization has become a practical technique to address EMA/amplifier faults. In this method, the configuration of multi-channel EMAs involves solving a...
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| Vydáno v: | ISA transactions Ročník 140; s. 293 - 308 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
Elsevier Ltd
01.09.2023
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| Témata: | |
| ISSN: | 0019-0578, 1879-2022, 1879-2022 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Fault-tolerant control of active magnetic bearing (AMB) systems with redundant electromagnetic actuators (EMAs) based on generalized bias current linearization has become a practical technique to address EMA/amplifier faults. In this method, the configuration of multi-channel EMAs involves solving a high-dimensional and nonlinear problem containing complex constraints offline. This article develops a general framework for the EMAs multi-objective optimization configuration (MOOC) by combining the non-dominated sorting genetic algorithm III (NSGA-III) and the sequential quadratic programming (SQP) with the designing of objectives, handling of constraints, consideration of the iterative efficiency and the diversity of solutions. The numerical simulation results confirm the feasibility of the framework for searching the non-inferior configurations and reveal the function mechanism that intermediate variables of the nonlinear optimization model on AMB performance. Finally, the best configurations identified using the technique for order preference by similarity to an ideal solution (TOPSIS) are applied to the 4-DOF AMB experimental platform. Experiments further indicate that the work in this paper provides a novel way with good performance and high reliability for solving the EMAs MOOC problem in fault-tolerant control of AMB systems.
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•The nonlinear optimization model determining the relationship between EMAs configuration and optimization objectives is obtained.•The constraint handling operator enables the decision-maker to make a trade-off between the diversity of desired configurations and the performance of the current distribution controller.•This paper correlates the initial population generation for NSGA-III with the physical characteristics of AMB to enlighten the evolutionary direction and improve the iteration efficiency.•Simulation and experiments reveal that the work in this paper provides a novel way with good performance and high reliability for solving the EMAs MOOC problem in fault-tolerant control of AMB systems. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0019-0578 1879-2022 1879-2022 |
| DOI: | 10.1016/j.isatra.2023.06.015 |