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检索条件"机构=Advanced Vehicle Control System Engineering Department"

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A Multifunctional Self-calibrated Sensor For Brake Fluid Condition Monitoring

A Multifunctional Self-calibrated Sensor For Brake Fluid Con...

引用

IEEE SENSORS

作者： Chuantong Wang Katsunori Shida Department of Advanced System and Control Graduate School of Science and Engineering Saga University Japan

A multifunctional self-calibrated sensor is proposed for on-line monitoring of liquid level and water content of brake fluid using capacitive method. The sensor is characterized by self-calibration ability to influence factors including temperature, water content (to liquid level sensing) and variety of brake fluid without calibration arithmetic supported by database as in conventional intelligent sensor systems. By using mutual calibrated output functions and taking new brake fluid as on-line reference, the sensor is well self-calibrated to the influence factors. The prototype sensor is developed and tested. The effectiveness of sensor is conformed by experimental results.

关键词： Condition monitoring Intelligent sensors Sensor phenomena and characterization Temperature sensors Capacitive sensors Sensor systems Calibration Arithmetic Databases Prototypes

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Complete and lag synchronization of hyperchaos using nonlinear controller

Complete and lag synchronization of hyperchaos using nonline...

引用

SICE Annual Conference

作者： Mahsa Dehghani Mohammad Haeri Advanced Control System Lab Electrical Engineering Department Sharif University of Technology Tehran Iran

In this paper the complete and lag synchronization of Chen hyperchaos are considered. A nonlinear controller is designed by which the synchronization of two identical hyperchaotic systems is achieved. The synchronization is proved using the Lyapunov stability theorem. Theoretical analysis and numerical simulation are provided to show the effectiveness of the controller

关键词： Nonlinear control systems control systems Master-slave Lyapunov method Numerical simulation Communication system control Chaotic communication Nonlinear systems Delay Computer simulation

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AQM for Dynamic QoS Adaptation in DiffServ Networks Based on STAC

AQM for Dynamic QoS Adaptation in DiffServ Networks Based on...

引用

SICE Annual Conference

作者： Mehdi Farrokhian Mohammad Haeri Advanced Control System Lab Electrical Engineering Department Sharif University of Technology Tehran Iran

In this paper we propose a new paradigm for a differential service (DiffServ) network consisting of two-color marking at the edges of the network using TSW2CM coupled with self tuning adaptive controller (STAC) in the core. This scheme exploits online estimates of the network parameters in the controller parameters adjustment. The performance demonstrates that the new scheme is able to admit traffic fairly and achieve edge-to-edge QoS under heavy traffic conditions and network state changes. We illustrate our results using ns-2 simulations and demonstrate the practical impact of self tuning control on managing queue utilization and delay

关键词： Diffserv networks Traffic control Throughput Adaptive control Communication system traffic control control systems Electronic mail Programmable control Delay Telecommunication traffic

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Globally Stable Adaptive Fuzzy control for Strict-feedback Nonlinear systems

Globally Stable Adaptive Fuzzy Control for Strict-feedback N...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Jang-Hyun Park Chae-Joo Moon Seong-Hwan Kim Jin Lee Soon-Youl So Jun-Ho Choi School of Electrical Control System and Advanced Material Engineering Mokpo National University Muan South Korea Department of Electrical Engineering Chonnam National University South Korea

A new adaptive fuzzy controller for uncertain strict-feedback nonlinear systems is proposed. All the previous approximator-based adaptive control algorithms for the strict-feedback nonlinear systems are based on backstepping scheme and guarantee semi-global closed-loop system stability. This paper proposes a new globally stabilizing adaptive fuzzy controller for strict-feedback nonlinear system without backstepping. To this end, an online self-structuring adaptive fuzzy system is employed. The proposed adaptive fuzzy controller is considerably simpler than the previous ones based on backstepping. Only one FLS is employed to approximate a lumped uncertain nonlinearity, which highlights the simplicity of our proposed control scheme.

关键词： Programmable control Adaptive control Fuzzy control Nonlinear systems Fuzzy systems Backstepping Adaptive systems Nonlinear control systems control systems Stability

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Online Detection and Classification of Disasters by a Multiple-input/single-output Sensor for a Home Security system

Online Detection and Classification of Disasters by a Multip...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： T. Ishigaki T. Higuchi K. Watanabe Department of Statistical Science The Graduate University for Advanced Studies (SOKENDAI) Tokyo Japan System Control Engineering Department Hoxi University Tokyo Japan Prediction and Knowledge Discovery Research Center Research Organization of Information and Systems Tokyo Japan System Control Engineering Department Hosei University Tokyo Japan

Conventional sensors have been designed to minimize noise effects. Any sensor that is designed to detect a certain physical variable is influenced to a certain degree by other physical variables. This suggests that any sensor is potentially tap able of detecting multiple physical variables. In the present study, we consider sensing devices that are easily influenced by several physical variables and make full use of their multi-sensing characteristics through statistical signal processing and machine learning techniques with a wide variety of prior information. The proposed sensor design approach is completely different from the conventional approach with respect to system design and has advantages in terms of cost and system simplification compared to existing approaches. This new idea can be realized by developing a novel multiple-input/single-output sensor that can detect various variables such as pressure, acceleration, temperature and light emission by a single device. The sensor is applied to monitor the symptoms of tire, earthquake and break-in for the purpose of home security. The proposed security system consists of the following three steps: (1) detection of disaster by a probabilistic outlier detection procedure using an auto-regressive model, (2) disaster feature extraction by Kalman filter on a state space model, and (3) disaster classification by multiclass support vector machine.

关键词： Sensor systems Security Sensor phenomena and characterization Temperature sensors Signal processing Machine learning Costs Acceleration Monitoring Tires

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Design of an Image Motion Compensation (IMC) algorithm for the Communication, Ocean, Meteorological Satellite (COMS)

Design of an Image Motion Compensation (IMC) algorithm for t...

引用

AIAA/AAS Astrodynamics Specialist Conference, 2006

作者： Jung, Taek-Seo Lee, Un-Seob Park, Sang-Young Choi, Yoon-Hyuk Bang, Hyo-Choong Ju, Gwanghyeok Yang, Koon-Ho Yonsei University Seoul 120-749 Korea Republic of Korea Advanced Institute of Science and Technology Daejeon 305-701 Korea Republic of Korea Aerospace Research Institute Daejeon 305-333 Korea Republic of Astrodynamics and Control Lab. Dept. of Astronomy and Space Science Flight Dynamics and Control Lab. Dept. of Aerospace Engineering Communication Satellite System Department

ISBN: (纸本)1563478226

This paper presents an Image Motion Compensation (IMC) algorithm for Korea's Communication, Ocean, and Meteorological Satellite (COMS). An IMC algorithm is a priority component of the Image Navigation and Registration (INR) system to locate and register radiometric image data. To eliminate image distortions, depointing of the imager aiming direction must be adjusted. A compensation algorithm to correct depointing caused by satellite motion is designed, and the capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by efficiently compensating for depointing of the imager aiming direction. Copyright © 2006 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Motion compensation

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A multi-variable detecting sensor and its application

A multi-variable detecting sensor and its application

引用

2006 SICE-ICASE International Joint Conference

作者： Koyama, Kenji Watanabe, Kajiro Kobayashi, Kazuyuki Kurihara, Yosuke Ishigaki, Tsukasa Higuchi, Tomoyuki Department of System Control Engineering Hosei University 3-7-2 Kajino-cho Koganei Tokyo 184-8584 Japan Department of Statistical Science Graduate University for Advanced Studies 4-6-7 Minami Azabu Minato-ku Tokyo 106-8569 Japan Institute of Statistical Mathematics 4-6-7 Minami Azabu Minato-ku Tokyo 106-8569 Japan

ISBN: (纸本)8995003855

Any sensor to detect a certain physical variable is influenced to some degree by other physical variables designated as "noise". The objective in conventional sensor design is to minimize such noise. In this study, conversely we welcome sensing devices that are easily influenced by many physical variables and make full use of their multi-sensing characteristic. We consider such devices as multiple-inputs and single-output sensors. The output signal derived from multiple input signals must be dissociated. The input signals resulting from physical realities have inherent characteristics and can be mathematically modeled. Application of a Kalman filter realized by such models can provide estimates of state variables of all input models, and thus the input signals can be dissociated. As an example, a novel sensor based on a microphone is presented. It can detect various variables such as pressure and acceleration in the frequency range of 0.1 Hz to 10 kHz, temperature, and even light emission. We use the sensor to monitor the symptoms of fire, earthquake and break-in by intruders from within a house. © 2006 ICASE.

关键词： Smart sensors

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Spectrum classification for early fault diagnosis of the LP gas pressure regulator based on the Kullback-Leibler kernel

Spectrum classification for early fault diagnosis of the LP ...

引用

2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, MLSP 2006

作者： Ishigaki, Tsukasa Higuchi, Tomoyuki Watanabe, Kajiro Department of Statistical Science Graduate University for Advanced Studies JST CREST 4-6-7 Minami Azabu Minato-ku Tokyo 106-8569 Japan Institute of Statistical Mathematics JST CREST 4-6-7 Minami Azabu Minato-ku Tokyo 106-8569 Japan Department of System Control Engineering Hosei University 3-7-2 Kajinocho Koganei-shi Tokyo 184-8584 Japan

ISBN: (纸本)1424406560

The present paper describes a frequency spectrum classification method for fault diagnosis of the LP gas pressure regulator using Support Vector Machines. Conventional diagnosis methods are not efficient because of problems such as significant noise and nonlinearity of the detection mechanism. In order to solve these problems, a machine learning method with the Kullback-Leibler (KL) kernel based on the KL divergence is introduced into spectrum classification. We use the normalized frequency spectrum directly as input with the KL kernel. The proposed method demonstrates a higher accuracy than popular kernels, such as polynomial or Gaussian kernels, or the conventional fault diagnosis method and Gaussian Mixture Model with the KL kernel for the examined problem. The high classification performance is achieved by using an inexpensive sensor system and the machine learning method. This method is widely applicable to other spectrum classification applications without limitation on the generality if the spectrums are normalized.

关键词： Pressure control

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Adaptive Global Terminal Sliding Mode control for Anti-Warship Missiles

Adaptive Global Terminal Sliding Mode Control for Anti-Warsh...

引用

World Congress on Intelligent control and Automation (WCICA)

作者： Xiangrong Tong Hongchao Zhao Guohu Feng Institute of Computer Science and Technology Yantai University Yantai Shandong China Department of Scientific Research Naval Aeronautical Engineering Institute Yantai Shandong China Research Institute of Flight Vehicle's Control System Naval Aeronautical Engineering Institute Yantai Shandong China

The overload control system of anti-warship missiles is researched. The output-redefinition technique is used to eliminate the nonminimum phase characteristics of missile overload output. In order to improve the robustness of the control system in the whole control process, an adaptive global terminal sliding mode (TSM) control method is proposed to control the missile's modified output. With this method, the system states lie in the global TSM at the onset of the motion, hence the reaching phase is removed from the control system. The adaptive controller is applied to estimate the upper bound of the lumped uncertainty. The validity of the proposed method is demonstrated through a simulation example

关键词： Programmable control Adaptive control Sliding mode control Missiles control systems Robust control Process control Motion control Adaptive systems Upper bound

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Spectrum Classification for Early Fault Diagnosis of the LP Gas Pressure Regulator Based on the Kullback-Leibler Kernel

Spectrum Classification for Early Fault Diagnosis of the LP ...

引用

IEEE Workshop on Machine Learning for Signal Processing

作者： Tsukasa Ishigaki Tomoyuki Higuchi Kajiro Watanabe Department of Statistical Science Graduate University for Advanced Studies and JST CREST Minato Tokyo Japan Institute of Statistical Mathematics and JST CREST Minato Tokyo Japan Department of System Control Engineering Hosei University Koganei Tokyo Japan

The present paper describes a frequency spectrum classification method for fault diagnosis of the LP gas pressure regulator using support vector machines. Conventional diagnosis methods are not efficient because of problems such as significant noise and nonlinearity of the detection mechanism. In order to solve these problems, a machine learning method with the Kullback-Leibler (KL) kernel based on the KL divergence is introduced into spectrum classification. We use the normalized frequency spectrum directly as input with the KL kernel. The proposed method demonstrates a higher accuracy than popular kernels, such as polynomial or Gaussian kernels, or the conventional fault diagnosis method and Gaussian mixture model with the KL kernel for the examined problem. The high classification performance is achieved by using an inexpensive sensor system and the machine learning method. This method is widely applicable to other spectrum classification applications without limitation on the generality if the spectrums are normalized.

关键词： Fault diagnosis Regulators Kernel Support vector machines Support vector machine classification Learning systems Vibration measurement Frequency Machine learning Data mining

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