Fault estimation and optimization for uncertain disturbed singularly perturbed systems with time-delay

Lei Liu; Shaoying Lu; Cunwu Han; Chao Li; Zejin Feng

doi:10.3934/naco.2020008

Article Contents

2020, Volume 10, Issue 3: 367-379. Doi: 10.3934/naco.2020008

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Fault estimation and optimization for uncertain disturbed singularly perturbed systems with time-delay

Beijing Key Laboratory of Fieldbus Technology and Automation, North China University of Technology, Beijing 100144, China

^* Corresponding author: Lei Liu, liulei_sophia@163.com
^* Corresponding author: Lei Liu, liulei_sophia@163.com

Received: May 2019

Revised: September 2019

Published: June 2020

The first author is supported by Youth Foundation of Beijing Nature Science Grant (No.4154068), the Youth Talent Cultivation Program of Beijing, the National Natural Science Foundation of China (No.61473002, No.61573024), North China University of Technology Yuyou Talent Support Program and the Fundamental Research Funds for Beijing Universities (No.110052971921/030)

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Abstract

This paper presents a observer-based fault estimation method for a class of singularly perturbed systems subjected to parameter uncertainties and time-delay in state and disturbance signal with finite energy. To solve the estimation problem involving actuator fault and sensor fault for the uncertain disturbed singularly perturbed systems with time-delay, the problem we studied is firstly transformed into a standard $ H_\infty $ control problem, in which the performance index $ \gamma $ represents the attenuation of finite energy disturbance. By adopting Lyapunov function with the $ \varepsilon $-dependence, a sufficient condition can be derived which enables the designed observer to estimate different kinds of fault signals stably and accurately, and the result obtained by dealing with small perturbation parameter in this way is less conservative. A novel multi-objective optimization scheme is then proposed to optimal disturbance attenuation index $ \gamma $ and system stable upper bound $ \varepsilon^* $, in this case, the designed observer can estimate the fault signals better in the presence of interference when the systems guarantee maximum stability bound. In the end, the validity and correctness of proposed scheme is verified by comparing the error between the estimated faults and the actual faults.

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Figure 1. Curves of estimated actuator fault

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Figure 2. Curves of estimated actuator fault

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Figure 3. Curves of the actuator fault estimation error

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Figure 4. Curves of the actuator fault estimation error

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Figure 5. Curves of estimated sensor fault

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Figure 6. Curves of estimated sensor fault

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Figure 7. Curves of the sensor fault estimation error

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Figure 8. Curves of the sensor fault estimation error

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Figure 9. Estimation error curves of fault state vector

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Figure 10. Estimation error curves of original system state vector

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References

[1]	Z. Bougatef, N. Abdelkrim, A. Tellili, et al., Fault diagnosis and accommodation for singularly perturbed time-delayed systems: descriptor approach, in 18th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering, (2017), 86–92.
[2]	G. R. Duan, H. H. Yu, A. G. Wu, et al., Analysis and Design of Descriptor Linear Systems, 1^st edition, Beijing: Science Press, 2012. doi: 10.1007/978-1-4419-6397-0.
[3]	S. H. Jiang, Stability analysis of time-varying time-delay uncertain singular systems, Journal of Tonghua Normal University, 38 (2017), 30-32.
[4]	H. Y. Li, Y. Y. Wang, D. Y. Yao, et al., A sliding mode approach to stabilization of nonlinear Markovian jump singularly perturbed systems, Automatica, 97 (2018), 404-413. doi: 10.1016/j.automatica.2018.03.066.
[5]	D. Liu, Y. Yang and Y. Zhang, Robust fault estimation for singularly perturbed systems with Lipschitz nonlinearity, Journal of The Franklin Institute, 353 (2016), 876-890. doi: 10.1016/j.jfranklin.2016.01.009.
[6]	H. S. Liu and Y. Huang, Robust adaptive output feedback tracking control for flexible-joint robot manipulators based on singularly perturbed decoupling, Robotica, 36 (2018), 822-838.
[7]	L. Liu, Y. Yang and W. Liu, Unified optimization of $H_\infty$ index and upper stability bound for singularly perturbed systems, Optimization Letters, 8 (2014), 1889-1904. doi: 10.1007/s11590-013-0686-6.
[8]	L. Liu, S. Y. Lu, C. W. Han, et al., Robust $H_\infty$ control for uncertain singularly perturbed systems with time-delay, in China Control Conference, (2017), 3147–3152.
[9]	L. Liu , X. F. Yan, C. W. Han, et al., Fault diagnosis and optimal fault-tolerant control of singularly perturbed systems based on PI observer, Control and Decision, 31 (2016), 1867-1872.
[10]	W. Q. Liu, M. Paskota, V. Sreeram, et al., Improvement on stability bounds for singularly perturbed systems via state feedback, International Journal of Systems Science, 28 (1997), 571-578.
[11]	P. Mei and Y. Zou, Study on robust stability of uncertain singular perturbation systems with time delay, Control and Decision, 23 (2008), 392-396.
[12]	M. Ndiaye, W. Liu and Z. M. Wang, Robust ISS stabilization on disturbance for uncertain singularly perturbed systems, IMA Journal of Mathematical Control and Information, 35 (2018), 1115-1127. doi: 10.1093/imamci/dnx017.
[13]	H. Shen, F. Li, Z. Wu, J. H. Park, et al., Fuzzy-model-based nonfragile control for nonlinear singularly perturbed systems with semi-Markov jump parameters, IEEE Transactions on Fuzzy Systems, 26 (2018), 3428-3439.
[14]	H. Shen, Y. Men, Z. G. Wu, et al., Nonfragile $H_\infty$ control for fuzzy markovian jump systems under fast sampling singular perturbation, IEEE Transactions on Systems, Man and Cybernetics: Systems, (2017), 1–12.
[15]	H. Shen, Y. Men, Z. Wu, J. Cao, et al., Network-based quantized control for fuzzy singularly perturbed semi-Markov jump systems and its application, IEEE Transactions on Circuits and Systems I: Regular Papers, 66 (2019), 1130-1140.
[16]	F. Q. Sun, Guaranteed performance control of a time-varying time-delay uncertain singular perturbation system, Journal of Jilin University, 6 (2015), 637-643.
[17]	A. Tellili, M. N. Abdelkrim and M. Benrejeb, Model-based fault diagnosis of two-time scales singularly perturbed systems, in International Symposium on Control, (2004), 819–822.
[18]	A. Tellili and M. N. Abdelkrim, Fault diagnosis and reconfigurable control of singularly perturbed systems using GIMC structure, International Journal of Computer Applications, 44 (2012), 31-35.
[19]	A. Tellili and M. N. Abdelkrim, Realiable $H_\infty$ controller design for singularly perturbed systems with sensor failure, in IEEE International Conference on Industrial Technology, (2004), 1636–1641.
[20]	A. Tellili, M. N. Abdelkrim and M. Benrejeb, Reliable $H_\infty$ control of multiple time scales singularly perturbed systems with sensor failure, International Journal of Control, 80 (2007), 659-665. doi: 10.1080/00207170601009634.
[21]	G. X. Wang, J. Wu, B. F. Zeng, et. al., A nonlinear adaptive sliding mode control strategy for modular high-temperature gas-cooled reactors, Progress in Nuclear Energy, 113 (2019), 53-61.
[22]	Y. Y. Wang, W. Liu and Z. M. Wang, Robust $H_\infty$ control of uncertain singular perturbation system with time delay, Journal of Beijing University of Technology, 42 (2016), 217-222.
[23]	J. Xu, C. Cai and Y. Zou, A novel method for fault detection in singularly perturbed systems via the finite frequency strategy, Journal of The Franklin Institute, 352 (2015), 5061-5084. doi: 10.1016/j.jfranklin.2015.08.001.
[24]	J. Xu and Y. G. Niu, A finite frequency approach for fault detection of fuzzy singularly perturbed systems with regional pole assignment, Neurocomputing, 325 (2019), 200-201.
[25]	J. Xu, Y. G. Niu, E. Fridman and et. al, Finite frequency $H_\infty$ control of singularly perturbed Euler-Lagrange systems: An artificial delay approach, Inernational Journal of Robust and Nonlinear Control, 29 (2019), 353-374. doi: 10.1002/rnc.4383.
[26]	K. K. Xu, Singular Perturbation in the Control Systems, Beijing: Science Press, 1986.
[27]	C. Yang, L. Ma, X. Ma, et al., Stability analysis of singularly perturbed control systems with actuator saturation, Journal of The Franklin Institute, 353 (2016), 1284-1296. doi: 10.1016/j.jfranklin.2015.12.013.
[28]	C. Yang, Z. Che, J. Fu, et al., Passivity-based integral sliding mode control and " - bound estimation for uncertain singularly perturbed systems with disturbances, IEEE Transactions on Circuits and Systems II: Express Briefs, 66 (2019), 452-456. doi: 10.1155/2015/926762.
[29]	C. Yang, Z. Che and L. Zhou, Integral sliding mode control for singularly perturbed systems with mismatched disturbances, Circuits, Systems, and Signal Processing, 38 (2019), 1561-1582. doi: 10.1007/s00034-018-0925-2.
[30]	C. Yang and Q. Zhang, Multiobjective control for T-S fuzzy singularly perturbed systems, IEEE Transactions Fuzzy Systems, 17 (2009), 104-115.
[31]	D. M. Yang, Q. L. Zhang, B. Yao, et al., Singular Systems, 1^st edition, Beijing: Science Press, 2004.
[32]	M. R. Zhou, W. Z. Lin, M. K. Ni, et al., Introduction to Singular Perturbation, Beijing: Science Press, 2014.