Grid interconnection of distributed generation units at distribution level using feedback linearization technique

Seyedalipour, S. Sajjad; Hosseini, Monir Sadat; Gharehpetian, Gevork B.

doi:10.1109/epdc.2016.7514813

Cited by 6 publications

(2 citation statements)

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“…Various researchers have used observational techniques, based on different algorithms. Examples include the proportional-integral (PI) technique [31,32], proportional multiple-integral (PMI) method [33,34,35], descriptor technique [36,37], adaptive methods [38,39,40], sliding mode techniques [41,42,43,44], and feedback linearization techniques [45,46]. Linear observer methods (e.g., PI and PMI) have been used in various applications for FDD, but these techniques have challenges in the presence of uncertainties [47,48].…”

Section: Introductionmentioning

confidence: 99%

“…Linear observer methods (e.g., PI and PMI) have been used in various applications for FDD, but these techniques have challenges in the presence of uncertainties [47,48]. To solve the challenge of linear observers, nonlinear observer techniques have been recommended [44,45,46]. One of the well-known nonlinear observation techniques for FDD is the sliding mode observer [41,42,43,44].…”

Section: Introductionmentioning

confidence: 99%

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Bearing Fault Diagnosis Using an Extended Variable Structure Feedback Linearization Observer

Piltan

Kim

2018

Sensors

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The rolling element bearing is a significant component in rotating machinery. Suitable bearing fault detection and diagnosis (FDD) is vital to maintaining machine operations in a safe and healthy state. To address this issue, an extended observer-based FDD method is proposed, which uses a variable structure feedback linearization observer (FLO). The traditional feedback linearization observer is stable; however, this technique suffers from a lack of robustness. The proposed variable structure technique was used to improve the robustness of the fault estimation while reducing the uncertainties in the feedback linearization observer. The effectiveness of the proposed FLO procedure for the identification of outer, inner, and ball faults was tested using the Case Western University vibration dataset. The proposed model outperformed the variable structure observer (VSO), traditional feedback linearization observer (TFLO), and proportional-integral observer (PIO) by achieving average performance improvements of 5.5%, 8.5%, and 18.5%, respectively.

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