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International Conference on Unmanned Aircraft Systems

作者： Kamal Saadeddin Mamoun F. Abdel-Hafez Mohammad Amin Jarrah Mechatronics Engineering Graduate Program American University of Sharjah Sharjah UAE Department of Mechanical Engineering American University of Sharjah Sharjah UAE

ISBN: (纸本)9781479908158

In this paper, a low-cost navigation system with high integrity and reliability is proposed. A high-integrity estimation filter is proposed to obtain a high accuracy state estimate. The filter utilizes a vehicle velocity constraint measurement to enhance the accuracy of the estimate. Two estimations filters, the extended Kalman filter (EKF) and the extended information filter (EIF), are designed and compared to obtain the estimate of the vehicle state. An instrumentation system that consists of a microcontroller, a GPS receiver, an IMU, velocity encoder, and a Zigbee transceiver is constructed. The microcontroller provides a vehicle navigation solution at 50 Hz by fusing the measurements of the IMU, the GPS receiver and the digital compass using the proposed filter design. Extensive experimental tests are conducted to verify the accuracy of the proposed algorithm. These results are processed with and without the velocity constraints. The estimation accuracy improvement with the addition of the velocity constraints is demonstrated. More than 16% reduction in the computational time is demonstrated when using the EIF in comparison to the EKF approach.

关键词： GPS IMU State Estimation Velocity Constraint

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Vibration Characterization Using Gaussian Laser Beam

Vibration Characterization Using Gaussian Laser Beam

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International Conference on Modeling, Simulation and Applied Optimization

作者： Naveed A. Abbasi Taha Landolsi Rached Dhaouadi Graduate Program of Mechatronics Engineering American University of Sharjah Department of Computer Engineering American University of Sharjah Department of Electrical Engineering American University of Sharjah

ISBN: (纸本)9781467358125

The objective of this research is to present a neural network based optical vibration sensor using a quad-cell photo-detector array. The proposed system uses a He-Ne laser source whose Gaussian beam impinges on the photo-detector array. The optical power distribution from the photo-detectors is fed to vibration monitoring system which maps the power distribution to the x-y position of the laser beam center. The vibration monitoring system uses artificial neural networks for function approximation to yield the correct mapping and estimate the x-y positions of the laser beam center which are then used for vibration characterization. An experimental setup of the system is developed and then trained using neural networks. The results obtained show the effectiveness of neural networks to estimate the vibration frequency and magnitude of a vibrating system.

关键词： Vibration monitoring Neural network Optical sensor Quad-cell photo detector array

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Indoor robot localization by RSSI/IMU sensor fusion

Indoor robot localization by RSSI/IMU sensor fusion

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International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Veerachai Malyavej Warapon Kumkeaw Manop Aorpimai Department of Control Instrumentation and Mechatronics Faculty of Engineering Mahanakorn University of Technology Bangkok Thailand The Electrical Engineering Graduate Program Faculty of Engineering Mahanakorn University of Technology Bangkok Thailand

Localization is the crucial problem for mobile robot navigation. For indoor mobile robot, since a global positioning system (GPS) is incapable, another promising technique to detect the position is the received signal strength indicator (RSSI) from wireless communication. To improve the precision and robustness of mobile unit localization, an inertial measurement unit (IMU) is normally used. In this report, we propose the algorithm for mobile robot localization based on sensor fusion between RSSI from wireless local area network (WLAN) and an IMU. The proposed fusion scheme is based on the extended Kalman filter (EKF). The experiment is conducted by using mobile unit equipped with low-cost IMU and a wireless communication module together with access points to evaluate the performance of our algorithm, and the result is promising.

关键词： Robot sensing systems Noise Mobile communication Wireless communication Mathematical model Sensor fusion Kalman filters

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Characterization of the radiation pattern of antennas using time-domain spherical-multipole and moment expansion

Characterization of the radiation pattern of antennas using ...

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作者： Ramos, Glaucio L. Rego, Cássio G. Fonseca, Alexandre R. Federal University of São João Del-Rei Department of Telecommunications and Mechatronics Engineering Ouro Branco MG Brazil Graduate Program in Electrical Engineering Federal University of Minas Gerais Brazil Federal University of Minas Gerais Department of Electronic Engineering Belo Horizonte MG Brazil Federal University of Vales Do Jequitinhonha e Mucuri Department of Computing Diamantina MG Brazil

This paper presents results of a time-domain spherical-multipole near-to-far-field transformation together with a moment expansion applied to antenna radiation patterns. The equivalence principle is applied to the tangential fields all over the FDTD/WP-PML spatial grid and the use of the spherical-multipole expansion leads to the near-to-far-field transformation, and energy and power norms of temporal signals are used to obtain the antenna radiation patterns for transient and steady-state responses. Such approach is employed to obtain UWB antenna radiated fields and radiation patterns directly in time-domain, it being more convenient to perform an unified characterization in time and frequency domains. © 2013 SBMO/SBMag.

关键词： Directional patterns (antenna)

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Group Method of Data Handling for Modeling Magnetorheological Dampers

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Intelligent Control and Automation 2013年第1期4卷 70-79页

作者： Khaled Assaleh Tamer Shanableh Yasmin Abu Kheil Department of Computer Science and Engineering American University of Sharjah Sharjah United Arab Emirates Department of Electrical Engineering American University of Sharjah Sharjah United Arab Emirates Mechatronics Graduate Program American University of Sharjah Sharjah United Arab Emirates

This paper proposes the use of Group Method of Data Handling (GMDH) technique for modeling Magneto-Rheological (MR) dampers in the context of system identification. GMDH is a multilayer network of quadratic neurons that offers an effective solution to modeling non-linear systems. As such, we propose the use of GMDH to approximate the forward and inverse dynamic behaviors of MR dampers. We also introduce two enhanced GMDH-based solutions. Firstly, a two-tier architecture is proposed whereby an enhanced GMD model is generated by the aid of a feedback scheme. Secondly, stepwise regression is used as a feature selection method prior to GMDH modeling. The proposed enhancements to GMDH are found to offer improved prediction results in terms of reducing the root-mean-squared error by around 40%.

关键词： System Identification Magneto-Rheological Dampers Group Method of Data Handling Polynomial Classifier

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Virtual testing of buckling-restrained braces via nonlinear autoregressive exogenous neural networks

Virtual testing of buckling-restrained braces via nonlinear ...

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作者： Alhamaydeh, Mohammad Choudhary, Ibrahim Assaleh, Khaled Dept. of Civil Engineering American Univ. of Sharjah P.O. Box 26666 Sharjah United Arab Emirates Mechatronics Graduate Program American Univ. of Sharjah P.O. Box 26666 Sharjah United Arab Emirates Dept. of Electrical Engineering American Univ. of Sharjah P.O. Box 26666 Sharjah United Arab Emirates

An artificial intelligence model utilizing feedforward back-propagation (FFBP) and nonlinear autoregressive exogenous (NARX) artificial neural networks (ANNs) is presented to model the nonlinear behavior of buckling-restrained braces (BRBs). The NARX ANN is developed using normalized time-delayed inputs and outputs to predict normalized brace forces during load reversals. The values of brace forces are denormalized via an auxiliary FFBP ANN. The training and testing of the proposed model (i.e., the NARX and FFBP ANNs) are performed using experimental data from BRB specimens tested at the Pacific Earthquake engineering Research (PEER) Center. Experimental data from one specimen is used in the model developing (training) stage. In addition, three sets of data are used to test the model's learning and generalizing abilities. Brace deformations are used as the network input to estimate the resulting brace forces. The network performance with different parameters is evaluated to arrive at an optimized architecture that best models the phenomenon. The nonlinear hysteretic behavior predicted by the ANN model shows excellent agreement with the experimental results for the training sample. The generalization and prediction capability of the proposed model is further demonstrated by predicting the hysteretic behavior of the testing samples with noticeable accuracy. The presented model is a powerful tool for virtually testing BRB specimens. Such a tool supplements the traditionally available experimental tools for BRB performance investigation. The developed modeling technique facilitates the BRB design and performance investigation processes by minimizing the need for, and extent of, experimental testing. © 2013 American Society of Civil Engineers.

关键词： Hysteresis

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Retraction Note

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Metals and Materials International 2014年第6期20卷 1169-1169页

作者： Chang-Suk Han Chang-Hwan Chun Seung-Oh Han Chang-Sup Oh Kyung-Wan Koo Jang-Woo Kim Young-Woo Kim Chang-Hwan Bae Ju-Hee Lee Dept. of Defense Science & Technology Hoseo University Chungnam Korea Research Center for Convergence Technology Hoseo University Chungnam Korea Reseat Program Korea Institute of Science and Technology Information Daejeon Korea Dept. of Defense Science & Technology Hoseo University Asan-si Chungnam Korea School of Display Engineering Hoseo University Chungnam Korea Dept. of Automotive Engineering Hoseo University Chungnam Korea Dept. of Mechatronics Eng. Graduate School of M. T. & M. Hoseo University Chungnam Korea

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Autonomous ground vehicle design, integration and control for the IGVC Competition

Autonomous ground vehicle design, integration and control fo...

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2012 8th International Symposium on mechatronics and its Applications, ISMA 2012

作者： Zulkifli, M. Aichour, H.Z. Chowdhury, Md.S. Ali, Naveed Khan, W. Saadeddin, K. Ukkirapandian, S. Jarrah, Mohammed A. Graduate Program of Mechatronics Engineering American University of Sharjah Sharjah United Arab Emirates Department of Mechanical Engineering American University of Sharjah Sharjah United Arab Emirates

This paper describes the design, development and testing of Unmanned Autonomous ground vehicle that was developed to participate in the International Ground Vehicle Competition (IGVC). This paper will go through the o... 详细信息

ISBN: (纸本)9781467308625

关键词： Motion planning

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Low-cost, high-accuracy, state estimation for vehicle collision prevention system

Low-cost, high-accuracy, state estimation for vehicle collis...

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2012 8th International Symposium on mechatronics and its Applications, ISMA 2012

作者： Saadeddin, Kamal Abdel-Hafez, Mamoun F. Jarrah, Mohammad Amin Mechatronics Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Mechanical Engineering American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781467308625

In this paper, a low-cost navigation system with high integrity and reliability is proposed for enhancing highway traffic safety in adverse weather situations, such as a foggy or rainy weather. A high-integrity, 15-state, estimation filter is proposed to obtain a high accuracy state estimate. The filter utilizes a vehicle velocity constraint measurement to enhance the accuracy of the estimate. Two estimations filters, the Kalman filter (KF) and the information filter (IF), are designed and compared to obtain the estimate of the vehicle state. An instrumentation system that consists of a microcontroller, a GPS receiver, an IMU, encoders, and a Zigbee transceiver is constructed. The microcontroller provides a vehicle navigation solution at 50 Hz by fusing the measurements of the IMU, the GPS receiver and the digital compass using the proposed filter design. Experimental tests, using the proposed system, are conducted and the obtained results are presented. These results are processed with and without the velocity constraints. The estimation accuracy improvement with the addition of the velocity constraints is demonstrated. Also, results of a static test are used to assess the accuracy of the low-cost navigation systems against a commercial solution. © 2012 IEEE.

关键词： Global positioning system

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Nonlinear AutoRegressive eXogenous Artificial Neural Networks for predicting buckling restrained braces force

Nonlinear AutoRegressive eXogenous Artificial Neural Network...

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2012 8th International Symposium on mechatronics and its Applications, ISMA 2012

作者： Choudhary, Ibrahim Assaleh, Khaled AlHamaydeh, Mohammad American University of Sharjah Mechatronics Graduate Program United Arab Emirates American University of Sharjah Department of Electrical Engineering United Arab Emirates American University of Sharjah Department of Civil Engineering United Arab Emirates

ISBN: (纸本)9781467308625

This paper proposes a novel approach for modeling the nonlinear dynamic behavior of Buckling-Restrained Braces (BRBs). The proposed approach is based on a combination of two architectures of Artificial Neural Networks (ANN) namely, Nonlinear AutoRegressive eXogenous (NARX) ANN and feed forward back propagation (FFBP) ANN. The proposed model predicts (outputs) the brace force at a certain time from the brace deflection and its history and the history of the brace force. The data used in training and testing of the model is acquired from the experimental testing of four BRB specimens. The proposed model is trained on data from one specimen while tested against the rest to demonstrate its learning and generalization capability. Optimum values for various network parameters are selected empirically to obtain the best network performance. The results show that the prediction error for the peak response (maximum tensile/compressive force) lies within ±5% confidence interval for all cycles. © 2012 IEEE.

关键词： Neural networks

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