Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method
As to solve the problem of multivariable output tracking control of variable cycle engine under system uncertainties and external disturbances, an augmented model reference adaptive sliding mode control method based on LQR method was developed. Firstly, the model is augmented and the reference state...
Format: | Article |
---|---|
Language: | zho |
Published: |
EDP Sciences
2018-10-01
|
Series: | Xibei Gongye Daxue Xuebao |
Subjects: | |
Online Access: | https://www.jnwpu.org/articles/jnwpu/pdf/2018/05/jnwpu2018365p824.pdf |
_version_ | 1797427609559105536 |
---|---|
collection | DOAJ |
description | As to solve the problem of multivariable output tracking control of variable cycle engine under system uncertainties and external disturbances, an augmented model reference adaptive sliding mode control method based on LQR method was developed. Firstly, the model is augmented and the reference state is provided to the controller by designing the reference model using the optimal LQR method. Then, based on the state tracking sliding mode control method, the adaptive law is derived based on the strict stability condition of Lyapunov function to estimate the upper bound of the system perturbation matrix and the upper bound of the external disturbances. Finally, the controller achieves the asymptotic zero tracking error of the system under the conditions of uncertainty and external disturbance. The simulation results showed that the LQR-based augmented model reference adaptive sliding mode control method can solve the problem that the traditional sliding mode control method needs to specify the reference state in advance and improve the control performance of the variable cycle engine control with system uncertainties and external disturbance. The tracking of the control command is effectively achieved and the steady-state and dynamic performance are improved. The steady-state control errors under different conditions are less than 0.1%, the system overshoot is less than 0.5%, and the adjustment time is less than 1s, which conformed to the requirements of the aero engine control system technology. |
first_indexed | 2024-03-09T08:47:02Z |
format | Article |
id | doaj.art-f864d4f9df6a4223a52fdaffa9a6f318 |
institution | Directory Open Access Journal |
issn | 1000-2758 2609-7125 |
language | zho |
last_indexed | 2024-03-09T08:47:02Z |
publishDate | 2018-10-01 |
publisher | EDP Sciences |
record_format | Article |
series | Xibei Gongye Daxue Xuebao |
spelling | doaj.art-f864d4f9df6a4223a52fdaffa9a6f3182023-12-02T15:15:54ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252018-10-0136582483010.1051/jnwpu/20183650824jnwpu2018365p824Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method01234School of Power and Energy, Northwestern Polytechnical UniversitySchool of Power and Energy, Northwestern Polytechnical UniversitySchool of Power and Energy, Northwestern Polytechnical UniversitySchool of Power and Energy, Northwestern Polytechnical UniversitySchool of Power and Energy, Northwestern Polytechnical UniversityAs to solve the problem of multivariable output tracking control of variable cycle engine under system uncertainties and external disturbances, an augmented model reference adaptive sliding mode control method based on LQR method was developed. Firstly, the model is augmented and the reference state is provided to the controller by designing the reference model using the optimal LQR method. Then, based on the state tracking sliding mode control method, the adaptive law is derived based on the strict stability condition of Lyapunov function to estimate the upper bound of the system perturbation matrix and the upper bound of the external disturbances. Finally, the controller achieves the asymptotic zero tracking error of the system under the conditions of uncertainty and external disturbance. The simulation results showed that the LQR-based augmented model reference adaptive sliding mode control method can solve the problem that the traditional sliding mode control method needs to specify the reference state in advance and improve the control performance of the variable cycle engine control with system uncertainties and external disturbance. The tracking of the control command is effectively achieved and the steady-state and dynamic performance are improved. The steady-state control errors under different conditions are less than 0.1%, the system overshoot is less than 0.5%, and the adjustment time is less than 1s, which conformed to the requirements of the aero engine control system technology.https://www.jnwpu.org/articles/jnwpu/pdf/2018/05/jnwpu2018365p824.pdfvariable cycle enginemultivariable controluncertaintymodel referenceadaptive sliding mode controlcontrollerslyapunov functions |
spellingShingle | Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method Xibei Gongye Daxue Xuebao variable cycle engine multivariable control uncertainty model reference adaptive sliding mode control controllers lyapunov functions |
title | Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method |
title_full | Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method |
title_fullStr | Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method |
title_full_unstemmed | Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method |
title_short | Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method |
title_sort | research on variable cycle engine control based on model reference adaptive sliding mode control method |
topic | variable cycle engine multivariable control uncertainty model reference adaptive sliding mode control controllers lyapunov functions |
url | https://www.jnwpu.org/articles/jnwpu/pdf/2018/05/jnwpu2018365p824.pdf |