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Design & application of adaptive variable structure &H∞ robust optimal schemes in nonlinear control of boiler-turbine unit in the presence of various uncertainties

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  • Ghabraei, Soheil
  • Moradi, Hamed
  • Vossoughi, Gholamreza

Abstract

In this article, to improve the precision, performance and robustness of an industrial boiler-turbine, two robust controllers are designed. First, a robust adaptive variable structure control scheme (RAVSC) is proposed to control a nonlinear multi-inputs multi-outputs (MIMO) model of an industrial boiler-turbine unit, in the presence of significant uncertainties and external disturbances. To guarantee the reliable performance of the RAVSC, appropriate adaption and control laws are introduced to compensate the uncertainties and modeling imprecisions and guarantee the convergence to the sliding surface. Then, the robustness and stability of the proposed RAVSC is proved via Lyapunov stability theory. Moreover, a robust H∞ controller is designed based on μ−DKiteration , with assumption of presence rational deviation in parameters and suitable weights to attenuate the control signals. To investigate the performance of proposed control schemes, simulation studies are carried out on nonlinear dynamic model in the presence of various uncertainties. Then, the performance of designed robust controllers exposed to discussion which reveals the satisfactory performance of the both proposed controllers. However, it is observed that RAVSC has some minor advantages over the robust H∞ controller.

Suggested Citation

  • Ghabraei, Soheil & Moradi, Hamed & Vossoughi, Gholamreza, 2018. "Design & application of adaptive variable structure &H∞ robust optimal schemes in nonlinear control of boiler-turbine unit in the presence of various uncertainties," Energy, Elsevier, vol. 142(C), pages 1040-1056.
    • Handle: RePEc:eee:energy:v:142:y:2018:i:c:p:1040-1056
    DOI: 10.1016/j.energy.2017.10.089
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    References listed on IDEAS

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    1. Benato, Alberto & Stoppato, Anna & Mirandola, Alberto, 2015. "Dynamic behaviour analysis of a three pressure level heat recovery steam generator during transient operation," Energy, Elsevier, vol. 90(P2), pages 1595-1605.
    2. Fang, Fang & Wei, Le, 2011. "Backstepping-based nonlinear adaptive control for coal-fired utility boiler-turbine units," Applied Energy, Elsevier, vol. 88(3), pages 814-824, March.
    3. Benato, A. & Bracco, S. & Stoppato, A. & Mirandola, A., 2016. "LTE: A procedure to predict power plants dynamic behaviour and components lifetime reduction during transient operation," Applied Energy, Elsevier, vol. 162(C), pages 880-891.
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    Cited by:

    1. Hongxia Zhu & Gang Zhao & Li Sun & Kwang Y. Lee, 2019. "Nonlinear Predictive Control for a Boiler–Turbine Unit Based on a Local Model Network and Immune Genetic Algorithm," Sustainability, MDPI, vol. 11(18), pages 1-25, September.
    2. Kong, Xiaobing & Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Lee, Kwang Y., 2023. "Stable feedback linearization-based economic MPC scheme for thermal power plant," Energy, Elsevier, vol. 268(C).
    3. Javed, Syed Bilal & Uppal, Ali Arshad & Samar, Raza & Bhatti, Aamer Iqbal, 2021. "Design and implementation of multi-variable H∞ robust control for the underground coal gasification project Thar," Energy, Elsevier, vol. 216(C).

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