The sliding mode controller for automotive ABS based on the fuzzy neural network

Mao, Yan-e; Zhang, Yifei; Liu, Tao

doi:10.1109/icnc.2010.5582534

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Literature [11] used convolutional neural network to implement the problem of fault detection and classification of gearboxes. Mao et al [12] proposed a fuzzy sliding mode controller based on neural network and applied it to the anti-lock system, which can effectively control wheel slip.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis and identification of rotating machinery based on one-dimensional convolutional neural network

Yu,

Chen,

et al. 2024

J. vibroeng.

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The paper focuses on two kinds of rotating machinery, miniature table drilling machine and automobile engine, as the research object. Traditional machine learning has the need for manual feature extraction, and is very dependent on expert diagnostic experience and expertise, but also has the disadvantages of low accuracy, low timeliness, low efficiency, etc. For the traditional rotating machinery fault diagnosis method is more based on the traditional machine learning model, this paper puts forward a one-dimensional convolutional neural network-based fault identification method. According to the characteristics of the miniature table drilling machine and the automobile engine which are not detachable, the corresponding faults are set up respectively, Vibration signals of the attitude sensor are obtained by using the signal collector, and the collected data are preprocessed, then the CNN model is built for fault identification, and the network structure is constantly optimized to obtain the optimal network model with high accuracy (up to 100 %) and robustness. The results show that the one-dimensional convolutional neural network model improves the fault recognition accuracy and reduces the cost compared with the traditional machine learning SVM model when the original signal is used as the input signal.

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Section: Introductionmentioning

confidence: 99%

Fault diagnosis and identification of rotating machinery based on one-dimensional convolutional neural network

Yu,

Chen,

et al. 2024

J. vibroeng.

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“…For examples, anti-lock braking system (ABS) is used to allow the vehicle to follow the desired steering angle while the intense braking is applied [1]. In addition, the ABS helps reducing the stopping distance of a vehicle compared with the conventional braking system.…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis of vehicle-to-vehicle impact using vehicle dynamics control systems for collision mitigation

Elmarakbi

Elkady

MacIntyre

2013

Int. J. Dynam. Control

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This paper focuses on the use of vehicle dynamics control systems (VDCS) to mitigate vehicle collisions in case of offset frontal vehicle-to-vehicle crash scenario. A unique 6-degree-of-freedom vehicle dynamics/crash mathematical model is developed and analyzed in this research. The model is used to define the vehicle body crash parameters by integrating a vehicle dynamics model with a vehicle front-end structure model. In this model, the anti-lock braking system and the active suspension control system are co-simulated with the full car vehicle dynamics model and integrated with the front-end structure. The associated equations of motion of the model are developed and solved numerically. Four different cases of VDCS are investigated in this paper and their associated results are compared with the free rolling case scenario. It is shown from the numerical simulations that the vehicle dynamics/crash response can be captured and analyzed quickly and accurately. Furthermore, it is shown that the VDCS affect the crash characteristics positively.

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The sliding mode controller for automotive ABS based on the fuzzy neural network

Cited by 2 publications

References 9 publications

Fault diagnosis and identification of rotating machinery based on one-dimensional convolutional neural network

Fault diagnosis and identification of rotating machinery based on one-dimensional convolutional neural network

Numerical analysis of vehicle-to-vehicle impact using vehicle dynamics control systems for collision mitigation

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