Improved robust adaptive cascade control of buck converters using complex-order PSO algorithm: theory and experiments
This article attempts to design an improved robust controller for the DC-DC buck converters subject to the load variations. The design mechanism is given by adopting the radial basis function neural networks for identifying unknown terms in which the neural weights are updated adaptively. To improve...
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| Vydané v: | International journal of dynamics and control Ročník 13; číslo 10; s. 357 |
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| Hlavní autori: | , , , , |
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| Jazyk: | English |
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Heidelberg
Springer Nature B.V
01.10.2025
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| Abstract | This article attempts to design an improved robust controller for the DC-DC buck converters subject to the load variations. The design mechanism is given by adopting the radial basis function neural networks for identifying unknown terms in which the neural weights are updated adaptively. To improve the robust behavior of the overall system, two disturbance observers are designed on the basis of cascade control. Furthermore, the control parameters are selected optimally using the complex-order particle swarm optimization algorithm. The stability of the overall system is proven by the Lyapunov theorem. The results of the proposed idea are presented and compared with a fuzzy backstepping control approach and a PID controller in the presence of supplied voltage fluctuations as well as the load variations. In addition, the experimental study is also conducted to assess the practicality of the proposed control framework. |
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| AbstractList | This article attempts to design an improved robust controller for the DC-DC buck converters subject to the load variations. The design mechanism is given by adopting the radial basis function neural networks for identifying unknown terms in which the neural weights are updated adaptively. To improve the robust behavior of the overall system, two disturbance observers are designed on the basis of cascade control. Furthermore, the control parameters are selected optimally using the complex-order particle swarm optimization algorithm. The stability of the overall system is proven by the Lyapunov theorem. The results of the proposed idea are presented and compared with a fuzzy backstepping control approach and a PID controller in the presence of supplied voltage fluctuations as well as the load variations. In addition, the experimental study is also conducted to assess the practicality of the proposed control framework. |
| ArticleNumber | 357 |
| Author | Keighobadi, Javad Vahedi, Hani Alfi, Alireza Saadat, Seyyed Amirhossein Abedi Pahnehkolaei, Seyyed Mehdi |
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| SubjectTerms | Algorithms Buck converters Cascade control Control systems design Controllers Disturbance observers Load fluctuation Neural networks Optimization Parameter identification Particle swarm optimization Proportional integral derivative Radial basis function Robust control Systems stability |
| Title | Improved robust adaptive cascade control of buck converters using complex-order PSO algorithm: theory and experiments |
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