Tracking Control of Pneumatic Muscle Using Adaptive Passivity Based Control

Elobaid, Youssif Mohamed Toum; Hassan, Ahmed Hassan M.

doi:10.1109/iccceee46830.2019.9071057

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The implementation of the passivity-based control method is relatively straightforward and does not require complex controller architectures and algorithms. Furthermore, this method can be applied to a range of dynamic systems, including mechanical [11], electrical [12], and chemical systems. There are currently multiple nonlinear control methods applied to LLC resonant converters.…”

Section: Introductionmentioning

confidence: 99%

Passivity-based control strategy for resonant converter based on Euler–Lagrange model

Zhang,

Liang,

Wang

et al. 2023

Archives of Electrical Engineering

View full text Add to dashboard Cite

The LLC resonant converter is a widely used DC/DC converter that offers the benefit of enabling soft switching compared to classical DC/DC converters. However, traditional PI control strategy based on a linear model has drawbacks such as slow dynamic response and poor anti-interference performance. To overcome the shortage, a passivitybased control strategy based on the Euler–Lagrange (EL) model is proposed in this paper to improve the dynamic performance of the half-bridge LLC resonant converter. In addition, the stability of the system based on the proposed strategy is analyzed and verified. Further, the effectiveness and performance of the proposed strategy is verified in the simulation by comparing with the traditional PI controller. Finally, a prototype was built to verify the dynamic performance of the LLC resonant converter based on the proposed control strategy.

show abstract

Section: Introductionmentioning

confidence: 99%