Analytical parameter tuning for a class of extended disturbance observers and sliding mode control

Yinlong Hu, Xuhao Cai, Jin Xu, Shang Shi, Yonghui Sun and Haiping Du

Applied Mathematics and Computation, 2024, vol. 469, issue C

Abstract: This paper studies the parameter tuning problem for a class of extended disturbance observers (EDO) and the EDO-based sliding mode control (SMC). Based on a H2 optimization technique, analytical solutions for the parameter tuning of the EDO and the EDO-based SMC are obtained. The conditions under which higher-order EDOs are strictly better than lower-order EDOs are derived analytically. Furthermore, the steady-state performance of the EDO-based SMC is analyzed, where it is shown that the improvement of the tracking accuracy of the EDO can reduce the sensitivity of the state variables and the control input with respect to the controller parameters. This implies that the SMC parameter tuning requirement can be reduced if a high tracking accuracy of the EDO is guaranteed. Finally, the application to the active structural control problem of an offshore wind turbine is studied and the effectiveness of the obtained results is demonstrated based on a National Renewable Energy Laboratory (NREL) 5MW baseline offshore wind turbine.

Keywords: Extended disturbance observer; Sliding mode control; Parameter tuning; Performance analysis; Offshore wind turbine (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:469:y:2024:i:c:s0096300323006963

DOI: 10.1016/j.amc.2023.128527

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