Design and modeling of 1000ppi fingerprint sensor

Huang, Sheng-Miao; Huang, Yu‐Sheng; Yeh, Cheng-Nan; Sugiura, Norío; You, Jhen-Yu; Peng, Chien-Huan

doi:10.1109/icsens.2015.7370566

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…,u u f , then obtain a predicting model considering road curvature: (10) Here A(t), B1(t) and B2(t) satisfy Equation ( 11). (11) Real time is continuous, but the observed time series are discrete. In order to better analyze the model, this paper linearizes and obtains the discrete state equation of the car dynamics model: (12) Set controlling time domain Tm < predicting time domain Tp, and…”

Section: Sideways Dynamic Modelmentioning

confidence: 99%

“…Xiu Caijing et al [10] designed the obstacle avoidance system of self-driving cars based on the artificial potential field method. Sheng Pengcheng et al [11] used the velocity obstacle method to detect the collision threat in real time, and established a mathematical model of the shortest obstacle avoidance time and safety distance to achieve efficient dynamic obstacle avoidance, and finally used Bayes' theorem to calculate the probability of the hazard level of the candidate path. Zhao Haipeng et al [12] introduced obstacle avoidance constraints based on the triangle area method, designed the cost function to meet the most predicted trajectory output, meanwhile introduced the nonlinear model prediction controller with rollover constraints for online optimal path tracking.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Model Based Research on Intelligent Vehicle Steering and Obstacle Avoidance

Huang¹

2023

HSET

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In order to improve road safety, promote the development of autonomous driving, and realize the stability of unmanned vehicles during steering and obstacle avoidance, this paper establishes a lateral dynamic model and a cyclotron curve model based on the 3-degree-freedom vehicle dynamics model. Taking no collision between cars and timely obstacle avoidance as the optimization goal, this paper discretizes the model, a prediction model is established, a soft constraint solver is designed, and a relaxation factor is added to the performance index function. Based on the model prediction and control principle, the obstacle avoidance trajectory planning and tracking of unmanned vehicles is integrated and controlled, and the solution is converted into a quadratic programming problem according to the constraints and rolling optimization characteristics. Finally Matlab/Prescan joint simulation is used to verify the steering and obstacle avoidance quality of the model. The results show that the model has excellent safety, stability and comfort in non-highspeed situations.

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Section: Sideways Dynamic Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Model Based Research on Intelligent Vehicle Steering and Obstacle Avoidance

Huang¹

2023

HSET

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“…The injection method has been proposed in [1][2][3][4][5], which inject AC or DC signals into the system, by detecting the signal strength to determine the fault location. Transient traveling wave based fault location methods can be found in [6][7][8][9][10][11][12][13][14], where applying Wavelet Transform and morphology to detect the traveling wave. Due to the complex structure of distribution network and Influence of interference, it is impossible to determine accurately the second the traveling wave from the point of fault.…”

Section: Introductionmentioning

confidence: 99%

A New Algorithm of Phase to Ground Fault Location for Electric Power Feeder

Wang

Liu

2013

AMM

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t is a great significance for power supply reliability and smart grid to locate feeder fault quickly and accurately for distribution network. A new ground fault traveling-wave signal time-frequency analysis method is proposed, which decomposes the aerial mode component and zero mode component of fault current based on EMD to get multi-stage stable intrinsic mode function (IMF). The first IMF contains high frequency components which can reflect the mutation of signal. Hilbert-Huang transformation is done for the first IMF to get the instantaneous frequency of signal. And then check the moment of traveling wave arrival by the instantaneous frequency in the figure of IMF time-frequency. The fault distance is computed based on the time difference between the moments of wave arrived of aerial mode component and zero mode components. Simulation shows that this method is able to accurately give the distance of fault without the influence of the random fault condition such as fault transition resistance and the moment of fault.

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Design and modeling of 1000ppi fingerprint sensor

Cited by 2 publications

References 2 publications

Dynamic Model Based Research on Intelligent Vehicle Steering and Obstacle Avoidance

Dynamic Model Based Research on Intelligent Vehicle Steering and Obstacle Avoidance

A New Algorithm of Phase to Ground Fault Location for Electric Power Feeder

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