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November  2021, 17(6): 3297-3307. doi: 10.3934/jimo.2020119

Fuzzy event-triggered disturbance rejection control of nonlinear systems

1. 

Key laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi, 214122, China

2. 

School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Perth, Western Australia, 6102, Australia

3. 

School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, GPO Box U1987, Perth, WA6845, Australia

* Corresponding author: Feng Pan

Received  October 2019 Revised  March 2020 Published  November 2021 Early access  June 2020

The problem of fuzzy based event-triggered disturbance rejection control for nonlinear systems is addressed in this paper. A new fuzzy event based anti rejection controller is designed and a fuzzy reduced disturbance observer is constructed. Sufficient conditions for the closed loop system to be asymptotically stable under an $ H_\infty $ performance index are derived. Based on these conditions, the design of a fuzzy event-triggered state feedback controller is formulated and solved. Numerical results are presented to demonstrate the correctness and effectiveness of our theoretical findings.

Citation: Peng Cheng, Yanqing Liu, Yanyan Yin, Song Wang, Feng Pan. Fuzzy event-triggered disturbance rejection control of nonlinear systems. Journal of Industrial and Management Optimization, 2021, 17 (6) : 3297-3307. doi: 10.3934/jimo.2020119
References:
[1]

A. Benzaouia and A. E. Hajjaji, Delay-dependent stabilization conditions of controlled positive T-S fuzzy systems with time varying delay, International Journal of Innovative Computing, Information and Control, 7 (2011), 1533-1548. 

[2]

Y.-Y. CaoZ. L. Lin and Y. Shamash, Set invariance analysis and gain-scheduling control for LPV systems subject to actuator saturation, Systems and Control Letters, 46 (2002), 137-151.  doi: 10.1016/S0167-6911(02)00128-7.

[3]

X. Chang and G. Yang, Relaxed results on stabilization and state feedback $H_\infty$ control conditions for T-S fuzzy systems, International Journal of Innovative Computing, Information and Control, 7 (2011), 1753-1764. 

[4]

M. Chen and W. Chen, Disturbance observer based robust control for time delay uncertain systems, International Journal of Control, Automation and Systems, 8 (2010), 445-453. 

[5]

T. M. Guerra and L. Vermeiren, LMI-based relaxed nonquadratic stabilization conditions for nonlinear systems in the Takagi-Sugeno's form, Automatica J. IFAC, 40 (2004), 823-829.  doi: 10.1016/j.automatica.2003.12.014.

[6]

L. Guo and W.-H. Chen, Disturbance attenuation and rejection for systems with nonlinearity via DOBC approach, International Journal of Robust and Nonlinear Control, 15 (2005), 109-125.  doi: 10.1002/rnc.978.

[7] L. Guo and S. Y. Cao, Anti-Disturbance Control for Systems with Multiple Disturbances, USA: CRC Press, Boca Raton, FL, 2014.  doi: 10.1201/b15528.
[8]

L. Guo and S. Y. Cao, Anti-disturbance control theory for systems with multiple disturbances: A survey, ISA Transactions, 53 (2014), 846-849.  doi: 10.1016/j.isatra.2013.10.005.

[9]

T. IwasakiG. Meinsma and M. Y. Fu, Generalized S-procedure and finite frequency KYP lemma, Mathematical Problems in Engineering, 6 (2000), 305-320.  doi: 10.1155/S1024123X00001368.

[10]

L. L. LvS. Y. Tang and L. Zhang, Parametric solutions to generalized periodic Sylvester bimatrix equations, Journal of the Franklin Institute, 357 (2020), 3601-3621.  doi: 10.1016/j.jfranklin.2019.12.031.

[11]

L. L. Lv and Z. Zhang, Finite iterative solutions to periodic Sylvester matrix equations, Journal of the Franklin Institute, 354 (2017), 2358-2370.  doi: 10.1016/j.jfranklin.2017.01.004.

[12]

L. L. LvZ. ZhangL. Zhang and X. X. Liu, Gradient based approach for generalized discrete-time periodic coupled Sylvester matrix equations, Journal of the Franklin Institute, 355 (2018), 7691-7705.  doi: 10.1016/j.jfranklin.2018.07.045.

[13]

X. J. SuP. ShiL. Q. Wu and Y.-D. Song, A novel control design on discrete-time Takagi-Sugeno fuzzy systems with time-varying delays, IEEE Trans on Fuzzy Systems, 21 (2013), 655-671.  doi: 10.1109/TFUZZ.2012.2226941.

[14]

C. SunY. Wang and C. Chang, Switching T-S fuzzy model-based guaranteed cost control for two-wheeled mobile robots, International Journal of Innovative Computing, Information and Control, 8 (2012), 3015-3028. 

[15]

T. Takagi and M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans on Syst. Man Cybern, 15 (1985), 116-132. 

[16]

K. TanakaT. Hori and H. O. Wang, A multiple Lyapunov function approach to stabilization of fuzzy control systems, IEEE Trans on Fuzzy Syst., 11 (2003), 582-589.  doi: 10.1109/TFUZZ.2003.814861.

[17]

L. WuX. SuP. Shi and J. Qiu, Model approximation for discrete-time state-delay systems in the T-S fuzzy framework, IEEE Trans on Fuzzy Systems, 19 (2011), 366-378. 

[18]

X. M. Yao and L. Guo, Composite anti-disturbance control for Markovian jump nonlinear systems via disturbance observer, Automatica J. IFAC, 49 (2013), 2538-2545.  doi: 10.1016/j.automatica.2013.05.002.

[19]

Y. Y. Yin, X. Chen and F. Liu, Disturbance rejection control for Markov jump systems with nonhomogeneous processes, The 27th Chinese Control and Decision Conference (2015 CCDC), Qingdao, China, (2015), 15340479. doi: 10.1109/CCDC.2015.7162007.

[20]

Y. Y. YinZ. L. LinY. Q. Liu and K. L. Teo, Event-triggered constrained control of positive systems with input saturation, International Journal of Robust and Nonlinear Control, 28 (2018), 3532-3542.  doi: 10.1002/rnc.4097.

[21]

Y. Y. YinY. Q. LiuK. L. Teo and S. Wang, Event-triggered probabilistic robust control of linear systems with input constrains: By scenario optimization approach, International Journal of Robust and Nonlinear Control, 28 (2018), 144-153.  doi: 10.1002/rnc.3858.

[22]

Y. Y. Yin, L. J. Zhu, F. Liu, K. L. Teo and S. Wang, Asynchronous $H_\infty$ control for nonhomogeneous higher-level Markov jump systems, Journal of the Franklin Institute, 357 (2020), 4697–4708. doi: 10.1016/j.jfranklin.2020.02.010.

[23]

L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353.  doi: 10.1016/S0019-9958(65)90241-X.

[24]

H. B. ZengK. L. TeoY. He and W. Wang, Sampled-data-based dissipative control of T-S fuzzy systems, Applied Mathematical Modelling, 65 (2019), 415-427.  doi: 10.1016/j.apm.2018.08.012.

[25]

H.-B. ZengK. L. TeoY. He and W. Wang, Sampled-data stabilization of chaotic systems based on a T-S fuzzy model, Information Sciences, 483 (2019), 262-272.  doi: 10.1016/j.ins.2019.01.046.

show all references

References:
[1]

A. Benzaouia and A. E. Hajjaji, Delay-dependent stabilization conditions of controlled positive T-S fuzzy systems with time varying delay, International Journal of Innovative Computing, Information and Control, 7 (2011), 1533-1548. 

[2]

Y.-Y. CaoZ. L. Lin and Y. Shamash, Set invariance analysis and gain-scheduling control for LPV systems subject to actuator saturation, Systems and Control Letters, 46 (2002), 137-151.  doi: 10.1016/S0167-6911(02)00128-7.

[3]

X. Chang and G. Yang, Relaxed results on stabilization and state feedback $H_\infty$ control conditions for T-S fuzzy systems, International Journal of Innovative Computing, Information and Control, 7 (2011), 1753-1764. 

[4]

M. Chen and W. Chen, Disturbance observer based robust control for time delay uncertain systems, International Journal of Control, Automation and Systems, 8 (2010), 445-453. 

[5]

T. M. Guerra and L. Vermeiren, LMI-based relaxed nonquadratic stabilization conditions for nonlinear systems in the Takagi-Sugeno's form, Automatica J. IFAC, 40 (2004), 823-829.  doi: 10.1016/j.automatica.2003.12.014.

[6]

L. Guo and W.-H. Chen, Disturbance attenuation and rejection for systems with nonlinearity via DOBC approach, International Journal of Robust and Nonlinear Control, 15 (2005), 109-125.  doi: 10.1002/rnc.978.

[7] L. Guo and S. Y. Cao, Anti-Disturbance Control for Systems with Multiple Disturbances, USA: CRC Press, Boca Raton, FL, 2014.  doi: 10.1201/b15528.
[8]

L. Guo and S. Y. Cao, Anti-disturbance control theory for systems with multiple disturbances: A survey, ISA Transactions, 53 (2014), 846-849.  doi: 10.1016/j.isatra.2013.10.005.

[9]

T. IwasakiG. Meinsma and M. Y. Fu, Generalized S-procedure and finite frequency KYP lemma, Mathematical Problems in Engineering, 6 (2000), 305-320.  doi: 10.1155/S1024123X00001368.

[10]

L. L. LvS. Y. Tang and L. Zhang, Parametric solutions to generalized periodic Sylvester bimatrix equations, Journal of the Franklin Institute, 357 (2020), 3601-3621.  doi: 10.1016/j.jfranklin.2019.12.031.

[11]

L. L. Lv and Z. Zhang, Finite iterative solutions to periodic Sylvester matrix equations, Journal of the Franklin Institute, 354 (2017), 2358-2370.  doi: 10.1016/j.jfranklin.2017.01.004.

[12]

L. L. LvZ. ZhangL. Zhang and X. X. Liu, Gradient based approach for generalized discrete-time periodic coupled Sylvester matrix equations, Journal of the Franklin Institute, 355 (2018), 7691-7705.  doi: 10.1016/j.jfranklin.2018.07.045.

[13]

X. J. SuP. ShiL. Q. Wu and Y.-D. Song, A novel control design on discrete-time Takagi-Sugeno fuzzy systems with time-varying delays, IEEE Trans on Fuzzy Systems, 21 (2013), 655-671.  doi: 10.1109/TFUZZ.2012.2226941.

[14]

C. SunY. Wang and C. Chang, Switching T-S fuzzy model-based guaranteed cost control for two-wheeled mobile robots, International Journal of Innovative Computing, Information and Control, 8 (2012), 3015-3028. 

[15]

T. Takagi and M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans on Syst. Man Cybern, 15 (1985), 116-132. 

[16]

K. TanakaT. Hori and H. O. Wang, A multiple Lyapunov function approach to stabilization of fuzzy control systems, IEEE Trans on Fuzzy Syst., 11 (2003), 582-589.  doi: 10.1109/TFUZZ.2003.814861.

[17]

L. WuX. SuP. Shi and J. Qiu, Model approximation for discrete-time state-delay systems in the T-S fuzzy framework, IEEE Trans on Fuzzy Systems, 19 (2011), 366-378. 

[18]

X. M. Yao and L. Guo, Composite anti-disturbance control for Markovian jump nonlinear systems via disturbance observer, Automatica J. IFAC, 49 (2013), 2538-2545.  doi: 10.1016/j.automatica.2013.05.002.

[19]

Y. Y. Yin, X. Chen and F. Liu, Disturbance rejection control for Markov jump systems with nonhomogeneous processes, The 27th Chinese Control and Decision Conference (2015 CCDC), Qingdao, China, (2015), 15340479. doi: 10.1109/CCDC.2015.7162007.

[20]

Y. Y. YinZ. L. LinY. Q. Liu and K. L. Teo, Event-triggered constrained control of positive systems with input saturation, International Journal of Robust and Nonlinear Control, 28 (2018), 3532-3542.  doi: 10.1002/rnc.4097.

[21]

Y. Y. YinY. Q. LiuK. L. Teo and S. Wang, Event-triggered probabilistic robust control of linear systems with input constrains: By scenario optimization approach, International Journal of Robust and Nonlinear Control, 28 (2018), 144-153.  doi: 10.1002/rnc.3858.

[22]

Y. Y. Yin, L. J. Zhu, F. Liu, K. L. Teo and S. Wang, Asynchronous $H_\infty$ control for nonhomogeneous higher-level Markov jump systems, Journal of the Franklin Institute, 357 (2020), 4697–4708. doi: 10.1016/j.jfranklin.2020.02.010.

[23]

L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353.  doi: 10.1016/S0019-9958(65)90241-X.

[24]

H. B. ZengK. L. TeoY. He and W. Wang, Sampled-data-based dissipative control of T-S fuzzy systems, Applied Mathematical Modelling, 65 (2019), 415-427.  doi: 10.1016/j.apm.2018.08.012.

[25]

H.-B. ZengK. L. TeoY. He and W. Wang, Sampled-data stabilization of chaotic systems based on a T-S fuzzy model, Information Sciences, 483 (2019), 262-272.  doi: 10.1016/j.ins.2019.01.046.

Figure 1.  System trajectories under disturbance rejection controller
Figure 2.  Estimation of disturbance
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