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Disturbance rejection in nonlinear systems based on equivalent-input-disturbance approach

Author

Listed:
  • Gao, Fang
  • Wu, Min
  • She, Jinhua
  • Cao, Weihua

Abstract

This paper presents a new system configuration and a design method that improves disturbance rejection performance for a nonlinear system. The equivalent-input-disturbance (EID) approach is used to construct an EID estimator that estimates the influence of exogenous disturbances and nonlinearities on the output of the system. Sufficient stability conditions for state- and output-feedback control are derived in terms of linear matrix inequalities. New EID-based control laws that combines an EID estimate with a state- or an output-feedback control laws ensure good control performance. A numerical example illustrates the design method. A comparison between the EID-based control, the conventional disturbance observer, the disturbance-observer-based-control, and the sliding mode control methods demonstrates the validity and superiority of the EID-based control method.

Suggested Citation

  • Gao, Fang & Wu, Min & She, Jinhua & Cao, Weihua, 2016. "Disturbance rejection in nonlinear systems based on equivalent-input-disturbance approach," Applied Mathematics and Computation, Elsevier, vol. 282(C), pages 244-253.
    • Handle: RePEc:eee:apmaco:v:282:y:2016:i:c:p:244-253
    DOI: 10.1016/j.amc.2016.02.014
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    References listed on IDEAS

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    1. Zhang, Ancai & Lai, Xuzhi & Wu, Min & She, Jinhua, 2015. "Stabilization of underactuated two-link gymnast robot by using trajectory tracking strategy," Applied Mathematics and Computation, Elsevier, vol. 253(C), pages 193-204.
    2. G. Y. Tang & Y. D. Zhao, 2007. "Optimal Control of Nonlinear Time-Delay Systems with Persistent Disturbances," Journal of Optimization Theory and Applications, Springer, vol. 132(2), pages 307-320, February.
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    Cited by:

    1. Yin, Xiang & She, Jinhua & Wu, Min & Sato, Daiki & Ohnishi, Kouhei, 2022. "Disturbance rejection using SMC-based-equivalent-input-disturbance approach," Applied Mathematics and Computation, Elsevier, vol. 418(C).
    2. Subramanian Manickavalli & Arumugam Parivallal & Ramasamy Kavikumar & Boomipalagan Kaviarasan, 2024. "Distributed Bipartite Consensus of Multi-Agent Systems via Disturbance Rejection Control Strategy," Mathematics, MDPI, vol. 12(20), pages 1-13, October.
    3. Karthick, S.A. & Sakthivel, R. & Ma, Y.K. & Mohanapriya, S. & Leelamani, A., 2019. "Disturbance rejection of fractional-order T-S fuzzy neural networks based on quantized dynamic output feedback controller," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 846-857.
    4. Sakthivel, R. & Joby, Maya & Wang, Chao & Kaviarasan, B., 2018. "Finite-time fault-tolerant control of neutral systems against actuator saturation and nonlinear actuator faults," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 425-436.
    5. Mohanapriya, S. & Sweety, C. Antony Crispin & Sakthivel, R. & Parthasarathy, V., 2023. "Disturbance attenuation for neutral Markovian jump systems with multiple delays," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    6. Mathiyalagan, Kalidass & Sangeetha, G., 2020. "Second-order sliding mode control for nonlinear fractional-order systems," Applied Mathematics and Computation, Elsevier, vol. 383(C).
    7. Yao, Xueqi & Zhong, Shouming, 2021. "EID-based robust stabilization for delayed fractional-order nonlinear uncertain system with application in memristive neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).

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