242 research outputs found

    Design of an adaptive state feedback controller for a magnetic levitation system

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    This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controller in terms of the operating point. The results of the simulation show that the operating point has significant effect on the performance of nonadaptive SFC, and this performance may degrade as the operating point deviates from the equilibrium point, while the ASFC achieves the required design specification for any operating point and outperforms the state feedback controller from this point of view

    Self-motion control of kinematically redundant robot manipulators

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    Thesis (Master)--Izmir Institute of Technology, Mechanical Engineering, Izmir, 2012Includes bibliographical references (leaves: 88-92)Text in English; Abstract: Turkish and Englishxvi,92 leavesRedundancy in general provides space for optimization in robotics. Redundancy can be defined as sensor/actuator redundancy or kinematic redundancy. The redundancy considered in this thesis is the kinematic redundancy where the total degrees-of-freedom of the robot is more than the total degrees-of-freedom required for the task to be executed. This provides infinite number of solutions to perform the same task, thus, various subtasks can be carried out during the main-task execution. This work utilizes the property of self-motion for kinematically redundant robot manipulators by designing the general subtask controller that controls the joint motion in the null-space of the Jacobian matrix. The general subtask controller is implemented for various subtasks in this thesis. Minimizing the total joint motion, singularity avoidance, posture optimization for static impact force objectives, which include maximizing/minimizing the static impact force magnitude, and static and moving obstacle (point to point) collision avoidance are the subtasks considered in this thesis. New control architecture is developed to accomplish both the main-task and the previously mentioned subtasks. In this architecture, objective function for each subtask is formed. Then, the gradient of the objective function is used in the subtask controller to execute subtask objective while tracking a given end-effector trajectory. The tracking of the end-effector is called main-task. The SCHUNK LWA4-Arm robot arm with seven degrees-of-freedom is developed first in SolidWorks® as a computer-aided-design (CAD) model. Then, the CAD model is converted to MATLAB® Simulink model using SimMechanics CAD translator to be used in the simulation tests of the controller. Kinematics and dynamics equations of the robot are derived to be used in the controllers. Simulation test results are presented for the kinematically redundant robot manipulator operating in 3D space carrying out the main-task and the selected subtasks for this study. The simulation test results indicate that the developed controller’s performance is successful for all the main-task and subtask objectives

    The Impact of Property Management on the Value of Residential Product in Saudi Arabia

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    This paper discusses the impact of property management in maintaining the value of residential product in Saudi Arabia. The paper reviewed a comparison of two property models: the first is managed by the property management system, and the second is managed by the owner only. In addition, the field questionnaire was used and distributed to a sample of the study community consisting of 125 real estate management institutions and real estate office in Riyadh. The results of the analysis indicate that property management contributes to raising the quality of the residential product and maintaining its market value. The residential product which managed by the property management system loses 10% of its value after 5 years. On the other hand, the product that managed by the owner loses more than 50% of its real value after 5 years. The paper proposes to strengthen cooperation between governmental and private institutions to establish a Real Estate Data Center (REDC) for the classification of residential properties subject to the criteria of management, quality and economic cost

    Reconfigurable Vision Processing for Player Tracking in Indoor Sports

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    Ibraheem OW. Reconfigurable Vision Processing for Player Tracking in Indoor Sports. Bielefeld: Universität Bielefeld; 2018.Over the past decade, there has been an increasing growth of using vision-based systems for tracking players in sports. The tracking results are used to evaluate and enhance the performance of the players as well as to provide detailed information (e.g., on the players and team performance) to viewers. Player tracking using vision systems is a very challenging task due to the nature of sports games, which includes severe and frequent interactions (e.g., occlusions) between the players. Additionally, these vision systems have high computational demands since they require processing of a huge amount of video data based on the utilization of multiple cameras with high resolution and high frame rate. As a result, most of the existing systems based on general-purpose computers are not able to perform online real-time player tracking, but track the players offline using pre-recorded video files, limiting, e.g., direct feedback on the player performance during the game. In this thesis, a reconfigurable vision-based system for automatically tracking the players in indoor sports is presented. The proposed system targets player tracking for basketball and handball games. It processes the incoming video streams from GigE Vision cameras, achieving online real-time player tracking. The teams are identified and the players are detected based on the colors of their jerseys, using background subtraction, color thresholding, and graph clustering techniques. Moreover, the trackingby-detection approach is used to realize player tracking. FPGA technology is used to handle the compute-intensive vision processing tasks by implementing the video acquisition, video preprocessing, player segmentation, and team identification & player detection in hardware, while the less compute-intensive player tracking is performed on the CPU of a host-PC. Player detection and tracking are evaluated using basketball and handball datasets. The results of this work show that the maximum achieved frame rate for the FPGA implementation is 96.7 fps using a Xilinx Virtex-4 FPGA and 136.4 fps using a Virtex-7 device. The player tracking requires an average processing time of 2.53 ms per frame in a host-PC equipped with a 2.93 GHz Intel i7-870 CPU. As a result, the proposed reconfigurable system supports a maximum frame rate of 77.6 fps using two GigE Vision cameras with a resolution of 1392x1040 pixels each. Using the FPGA implementation, a speedup by a factor of 15.5 is achieved compared to an OpenCV-based software implementation in a host-PC. Additionally, the results show a high accuracy for player tracking. In particular, the achieved average precision and recall for player detection are up to 84.02% and 96.6%, respectively. For player tracking, the achieved average precision and recall are up to 94.85% and 94.72%, respectively. Furthermore, the proposed reconfigurable system achieves a 2.4 times higher performance per Watt than a software-based implementation (without FPGA support) for player tracking in a host-PC.Acknowledgments: I (Omar W. Ibraheem) would like to thank the German Academic Exchange Service (DAAD), the Congnitronics and Sensor Systems research group, and the Cluster of Excellence Cognitive Interaction Technology ‘CITEC’ (EXC 277) (Bielefeld University) not only for funding the work in this thesis, but also for all the help and support they gave to successfully finish my thesis

    A comparative study on application of decomposition method in function generation synthesis of over-constrained mechanisms

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    Double-spherical six-bar linkage is one of the Bennett over-constrained 6R linkages. Kinematic synthesis of such linkages can be tedious and impossible to solve for analytically. In order to cope with higher number of unknowns in these types of linkages, decomposition method is a valuable tool. This paper focuses on the function generation synthesis of double-spherical six-bar linkage. Two procedures for applying decomposition method are explained. Two numerical studies are conducted for both procedures to evaluate the performance of each procedure

    The Effect of Grain Size of Reinforcing Material (Corn Cob) on Some Mechanical Properties of the Composite Material.

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    Corn cob (CC) is an agricultural waste that can be recycled and used to reinforce unsaturated polyester resin, which can be utilized to produce low-cost structural sections, as well as reduce the risk resulting from the disposing of these wastes by traditional methods, such as landfilling or burning. The purpose of this research is to study the grain size effect of the reinforcing material particles on the mechanical properties of the composite material represented by (hardness, impact resistance, and compressive strength). The experimental work is carried out by preparing a polymeric mixture of unsaturated polyester resin (UPE) reinforced by corn cob particles using two different grain sizes of (53) µm and (710) µm with different volumetric fractions of (0, 5, 10, 20, and 30)%. The manual molding method was used in preparing the molds as follows: The first group consists of a polymeric mixture reinforced with corn cobs with a granular size of (53) µm using the same volumetric ratios mentioned above, while the second group consists of a polymeric mixture reinforced with corn cobs with a granular size of (710) µm using the same volumetric fractions of the first group. The results suggested that the reinforcement of the matrix by these particles led to improving the mechanical properties of the composite material by increasing the reinforcement ratios

    Modeling Of Construction Firms Sustainability

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    Sustainability is a hot debatable issue over the world, constantly being discussed by huge number of professionals’

    Learning Generic Solutions for Multiphase Transport in Porous Media via the Flux Functions Operator

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    Traditional numerical schemes for simulating fluid flow and transport in porous media can be computationally expensive. Advances in machine learning for scientific computing have the potential to help speed up the simulation time in many scientific and engineering fields. DeepONet has recently emerged as a powerful tool for accelerating the solution of partial differential equations (PDEs) by learning operators (mapping between function spaces) of PDEs. In this work, we learn the mapping between the space of flux functions of the Buckley-Leverett PDE and the space of solutions (saturations). We use Physics-Informed DeepONets (PI-DeepONets) to achieve this mapping without any paired input-output observations, except for a set of given initial or boundary conditions; ergo, eliminating the expensive data generation process. By leveraging the underlying physical laws via soft penalty constraints during model training, in a manner similar to Physics-Informed Neural Networks (PINNs), and a unique deep neural network architecture, the proposed PI-DeepONet model can predict the solution accurately given any type of flux function (concave, convex, or non-convex) while achieving up to four orders of magnitude improvements in speed over traditional numerical solvers. Moreover, the trained PI-DeepONet model demonstrates excellent generalization qualities, rendering it a promising tool for accelerating the solution of transport problems in porous media.Comment: 23 pages, 11 figure
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