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Optimization of resistive loading of EMI/EMC near field probe

ROBOTICS AND AUTONOMOUS SYSTEMS 2004年第3-4期49卷 245-251页

作者： Çömlekçi, S Özen, S Köklükaya, E Suleyman Demirel Univ Dept Elect & Commun Engn Isparta Turkey Tech Vocat Sch Higher Educ Dept Biomed Antalya Turkey Sakarya Univ Dept Elect & Elect Engn Sakarya Turkey

Near field studies must be carried out to insulate printed circuit boards and other circuits entirely from outer space. It can be achieved by utilizing the screen properly. These studies must always be made in the near field. The best way known to sense Radio Frequency energy is using a proper loop antenna. The loop probe can be used both as a transmitter and a receiver. If it is loaded resistively, desired flat response between low and high cut off frequency can be obtained. To get accurate results, its physical and electrical parameters must be chosen properly. The most important electrical parameter is inductance of such a loop conductor. Common inductance equations are in general form and they are derived for general calculations. However, loop probes have narrow physical range;they have diameters of a few-centimeters, a few-turn, and have a very thin conductor. So, a certain equation can be derived more accurately. It can be achieved by using conventional empirical derivations or by using modem optimization techniques. (C) 2004 Elsevier B.V. All rights reserved.

关键词： EMI/EMC EM immunity near field probe fuzzy logic algorithm

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Rolling Guide Filtering and Non-subsampled Contourlet Transform for Fusion of Visible and Infrared Images

JOURNAL OF APPLIED SCIENCE AND ENGINEERING

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JOURNAL OF APPLIED SCIENCE AND ENGINEERING 2020年第4期23卷 687-694页

作者： Wang, Xiaodong Chen, Hongyou Zhengzhou Univ Sci & Technol Sch Elect Engn Zhengzhou 450000 Peoples R China

Image fusion is essentially an image enhancement technology, which aims to generate fusion images with richer information and more features by extracting complementary information from images collect-ed by different sensors (such as infrared and visible light) or the same sensor (such as multi-focus image). For the fusion of infrared and visible images, it is easy to produce problems such as missing detail infor-mation and suppressing less noise. In this paper, we propose a Visible and Infrared Images fusion method by combining Non-subsampled Contourlet Transform (NSCT) and rolling guide filtering. First, fuzzy log-ic algorithm is used to enhance the contrast of visible image and highlight the effective information of image. Second, the enhanced visible and infrared images are decomposed by NSCT to obtain the low fre-quency and high frequency sub-bands. The improved rolling guide filter is used to enhance the edge and other details of the high frequency sub-band of infrared image. Third, mean gradient strategy and fuzzy logic strategy are used to fuse high and low frequency sub-bands, respectively. Experiments show that the proposed fusion method has better results than other state-of-the-art methods in terms of information entropy, standard deviation, and mutual information.

关键词： Image fusion NSCT Rolling guide filtering fuzzy logic algorithm

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Comparison of in-flight aircraft icing algorithms based on ECMWF forecasts

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METEOROlogicAL APPLICATIONS 2015年第4期22卷 705-715页

作者： Belo-Pereira, Margarida Inst Portugues Mar & Atmosfera Div Meteorol Aeronaut & Naut P-1749077 Lisbon Portugal

This study presents an objective verification of different icing algorithms for two periods from 5December 2012 to 17April 2013 and from 9October to 11December 2013. The predicted icing potential and severity are evaluated against pilot reports of aircraft icing below 23000feet over Eastern United States. The icing algorithms are applied to the deterministic forecasts of European Centre for Medium-Range Weather Forecasts (ECMWF). Two of these algorithms are based only on forecasts of temperature (T) and relative humidity (RH), but the first uses fixed thresholds and the second uses a fuzzy logic approach. Although the second algorithm detects less icing events, it is more efficient with respect to the warning area, i.e. it forecasts icing over a smaller percentage of the airspace than the first algorithm. The impact of adding information from cloud liquid water (CLW) content and/or vertical velocity in the fuzzy logic scheme is assessed. algorithms using T, CLW and vertical velocity as predictors are also tested. Most of the algorithms reveal a good performance in discriminating between icing and no-icing conditions, but are less skilful in forecasting the icing severity. The results also show that the use of CLW is essential to avoid issuing too many warnings. Moreover, the algorithm combining T, RH, CLW and vertical velocity attains the best performance. This algorithm, SFIPO, has been operational at the Portuguese Meteorological Watch Office since June 2013, and an example of a severe icing episode in February 2014 over mainland Portugal is presented.

关键词： aircraft icing ECMWF forecast fuzzy logic algorithm cloud liquid water PIREP

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Reference Slip Ratio Generation and Adaptive Sliding Mode Control for Railway Rolling Stocks

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INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING 2009年第2期10卷 39-44页

作者： Park, Sung Hwan Kim, Jong Shik Choi, Jeong Ju Pusan Natl Univ Sch Mech Engn RIMT Pusan 609735 South Korea

We propose a reference slip ratio generation algorithm that accounts for a large adhesion force to improve the braking performance of railway rolling stocks even if the rail conditions change. Our algorithm is based on fuzzy logic, the efficiency of which was evaluated by comparing the braking distances of rolling stocks using the proposed algorithm and using constant reference slip ratios under various rail conditions. Our proposed slip ratio generation algorithm was used as the basis of an adaptive sliding mode controller for a rolling stocks quarter model. In this design, an adaptive rule was developed using the Lyapunov stability theorem, and the performance of the proposed control system was evaluated by computer simulation.

关键词： Railway rolling stocks Adaptive sliding mode control fuzzy logic algorithm Adhesion force Brake systems

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Incorporating human factors into LCM using fuzzy TCI model

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TRANSPORTMETRICA B-TRANSPORT DYNAMICS 2021年第1期9卷 198-218页

作者： Li, Linbo Li, Yang Ni, Daiheng Tongji Univ Key Lab Rd & Traff Engn Minist Educ 4800 Caoan Rd Shanghai 201804 Peoples R China Univ Massachusetts Civil & Environm Engn Amherst MA 01003 USA

Incorporation of Human Factors (HF) into the mathematical car-following (CF) models has always been the research hotspot. Ignorance of such inclusion would inevitably hinder us from acquiring a comprehensive understanding of traffic flow phenomena. This paper proposed a novel CF model in order to bridge three existing research gaps: the demand for more inclusion of HF into the Longitudinal Control Model (LCM);the requirement for a more desirable underlying CF model for the Task Capability Interface (TCI) model;the ignorance of the fuzziness of human brains when modeling Task Difficulty (TD). Specifically, in order to imitate driver's natural or subjective uncertainty and ambiguity of his TD, the fuzzy logic approach is introduced, and the TD is then incorporated into the LCM. Thereafter, both numerical simulation and field-data validation have been performed. Results indicate that our proposed model is more capable of accommodating HF and exhibits better performance than its predecessor.

关键词： Car-following model human factors task capability interface model fuzzy logic algorithm

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Tire-Road-Friction-Estimation-based Braking Force Distribution for AWD Electrified Vehicles with a single Electric Machine 3

Tire-Road-Friction-Estimation-based Braking Force Distributi...

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International Conference on Sustainable Energy Engineering and Application ICSEEA

作者： Paul, Deepak Velenis, Efstathios Cao, Dongpu Cranfield Univ Ctr Automot Engn Cranfield MK43 0AL Beds England

ISBN: (纸本)9781509001934

Braking force distribution (BFD) for electrified vehicles for maximizing energy regeneration has been a challenging research topic, due to the complex operating conditions and tradeoff among different vehicle performance measures. It is known that the level of tire-road friction has a significant impact on the braking force boundaries that define the locking conditions of front and rear wheels. However, conventional BFD strategies for electrified vehicles have not taken full advantage of tire-road friction and generally preferred conservative algorithms. These suggest a potential for exploiting tire-road friction estimation for BFD so as to enhance energy regeneration of electrified vehicles while retaining vehicle stability. This study tackles this challenge by proposing a tire-road-friction-estimation-based BFD for all-wheel-drive (AWD) electrified vehicles with a single electric motor. The specific topology considered in this study is a plug-in hybrid electric vehicle that is powered by an internal combustion engine and a single electric machine. The AWD capacity is provided by a propeller differential shaft connecting the front and rear axles, which imposes a constraint on the ratio of front/rear regenerative brake forces, which is always equal on both axles for the vehicle topology considered here. For the proposed BFD strategy, a fuzzy-logic based tire-road friction estimation algorithm is developed, which uses the longitudinal wheel slip estimated from sensor measurements of vehicle acceleration and wheel speeds. The tire-road friction estimation algorithm is accordingly integrated within the braking controller for front and rear braking force generation and allocation. Simulation analyses are conducted, and the results and discussions demonstrate the effectiveness of the proposed tire-road friction estimation algorithm, and that the tire-road friction estimation-oriented BFD strategy can help to improve the braking energy recovery.

关键词： Tire-road friction estimation Braking force distribution (BFD) electrified vehicles fuzzy logic algorithm regenerative braking

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Design of Integrated Scheduling and Automated Controlling for Surface Treatment Process using Supervisory Control and Data Acquisition (SCADA)

Design of Integrated Scheduling and Automated Controlling fo...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Damayanti, D. D. Rachmat, H. Atmaja, D. S. Inst Teknol Telkom Dept Ind Engn Bandung Indonesia

ISBN: (纸本)9781479909865

This paper aims to design a model of integrated scheduling and automated controlling for a surface treatment process in an aircraft manufacturing company, where in this case aircraft parts are dyed into chemical liquid to be corrosion-proof. In the existing plant, parts dyeing processes (moving the crane and monitoring the tanks temperature) are done manually. Integrated scheduling and automation control system is proposed to improve planning, control and safety issues in the dyeing process. The scheduling system is developed using fuzzy logic algorithm to minimize makespan and the automation system is designed based on Supervisory Control and Data Acquisition (SCADA). A case study has shown that the simulation of proposed model can result in reducing makespan of about 51,3 % and the schedule can be implemented automatically in the surface treatment prototype.

关键词： Scheduling fuzzy logic algorithm SCADA Automation

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On Control and Performance Evaluation of Active Suspension System

On Control and Performance Evaluation of Active Suspension S...

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IEEE International Conference on Mechatronics and Automation

作者： Yang, Qingmei Sun, Jiammin Beijing Union Univ Coll Automat Beijing 100101 Peoples R China Beijing Univ Civil Engn & Architecture Sch Mech Elect & Automobile Engn Beijing 100044 Peoples R China

ISBN: (纸本)9781424426928

For the riding comfort and handling safety of vehicle, an active suspension system with adjustable fuzzy controller is advanced. According to the evaluation method of vehicle vibration performance, the acceleration of the sprung mass, dynamic tire load between wheels and road and dynamic deflection between the sprung mass and the unsprung mass are determined as the evaluation targets of suspension performance. For two degree-of-freedom (DOF) vehicle model, the simulation of vehicle performance in road signal is studied. Its results show the active suspension controller can reduce the acceleration of the sprung mass by a factor of 20. On the experiment study of vehicle model, the results further prove that the active suspension controller can effectively control the vibration of vehicle system.

关键词： Active control Vehicle suspension system Performance evaluation fuzzy logic algorithm

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Sensor Fault Diagnosis Using an Indirect fuzzy Feedback Linearization and Decision Trees 12

Sensor Fault Diagnosis Using an Indirect Fuzzy Feedback Line...

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12th International Conference on ICT Convergence (ICTC) - Beyond the Pandemic Era with ICT Convergence Innovation

作者： TayebiHaghighi, Shahnaz Koo, Insoo Univ Ulsan Dept Elect Elect & Comp Engn Ulsan South Korea

ISBN: (纸本)9781665423830

Sensor fault diagnosis is a cutting-edge research area in recent years. In the paper, an indirect fuzzy feedback linearization technique is suggested for sensor fault diagnosis. The proposed scheme has three main steps as following: The preprocessing unit is the first step to design an indirect observer in which the feature extraction technique is used to extract the root means square (RMS) data from resampled fuel to air ratio signals. The normal RMS resampled data is modeled using the nonlinear data identification technique. The combination of autoregressive with external input, Laguerre input-output filter, and fuzzy algorithm, FAL, is suggested for normal resampled RMS data modeling. After modeling the data, the combination of the FAL modeling method, feedback linearization technique, and fuzzy estimator, FAL-FF, is suggested for RMS resampled data estimation. The fuzzy technique is used to estimate the nonlinear function in feedback linearization observer and improve the accuracy of estimation for data classification. Next, the residual resampled RMS fuel to air ratio data is generated using the difference between original and estimated data. Finally, the decision tree is used to classify the resampled RMS residual sensors data for fault diagnosis. Regarding the results, the accuracy of sensor fault diagnosis using the proposed scheme is 96.7%.

关键词： Sensor fault diagnosis machine learning autoregressive with external input modeling fuzzy logic algorithm feedback linearization observer decision tree

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The Research of Motion Planning for Humanoid Robots

The Research of Motion Planning for Humanoid Robots

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Lu Xueqin Qiu Rongfu Shanghai Univ Elect Power Dept Informat & Control Engn Shanghai Peoples R China

ISBN: (纸本)9780769538167

This paper presents research advances in motion planning for humanoid robots, which has been a focus of robotics research in recent years. The twelve-link model of humanoid robot is analyzed. Then the intelligent control techniques on path planning and gait planning have been introduced. The three algorithms of gait planning are fuzzy logic algorithm, neural network algorithm and genetic algorithm. The analysis and estimation aim to provide a typical overview on motion planning for humanoid robots.

关键词： humanoid robot path planning gaits planning fuzzy logic algorithm neural network algorithm genetic algorithm

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