Illumination-Resilient Lane Detection by Threshold Self-Adjustment Using Newton-Based Extremum Seeking

Zhou, Yujing; Wang, Zejiang; Wang, Junmin

doi:10.1109/tits.2022.3161902

Cited by 4 publications

(1 citation statement)

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“…As will be proved later, the stability and convergence rate of the FHGO depend on the careful tuning of two parameters. To ensure good performance of the proposed observer, rather than manually choosing the tuning parameters of the FHGO, a real-time optimization of the two parameters was performed using the extremum seeking (ES) algorithm [14][15][16][17] . To address these issues, the following contributions were made.…”

Section: Introduction1mentioning

confidence: 99%

Filtered High Gain Observer for an Electric Vehicle's Electro-hydraulic Brake: Design and Optimization Using Multivariable Newton-Based Extremum Seeking

El-Bakkouri,

Ouadi,

Giri

et al. 2023

Chin. J. Electr. Eng.

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Designing high-gain observers (HGOs) for the state estimation of an electric vehicle's electrohydraulic brake (EHB) system is challenging. This type of observer is applicable to model nonlinearities and constant feature gains. However, they are very sensitive to measurement noise, which is unavoidable in EHB. The first novelty of this study is that it compensates for the measurement noise using a filtered high-gain observer (FHGO) to ensure EHB state estimation. The proposed FHGO provides an estimate of the master cylinder pressure, motor current, and rotor speed from measurements of the rotor position. The second novelty is the design of an extremum-seeking (ES) optimization loop to adjust the FHGO gains online. The performance of the developed FHGO with ES-based online gain optimization was highlighted in the presence of model uncertainties and output measurement noise using a Matlab/Simulink simulation. The superiority of the FHGO (even with a fixed gain) over a standard high gain observer (SHGO) was also demonstrated.

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Section: Introduction1mentioning

confidence: 99%