• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.134-139
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• 2001

This paper presents a new scheme of neural network controller to improve the robustuous of robot manipulator using digital signal processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.1077-1081
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• 2004

In this Paper we discuss an algorithm for a real-time transmission of moving color image on the TCP/IP network using wavelet transform and neural network. The Image frames received from the camera are two-level wavelet-transformed in the server, and are transmitted to the client on the network. Then, the client performs the inverse wavelet-transform using only the received pieces of each image frame within the prescribed time limit to display the moving images. When the TCP/IP network is busy, only a fraction of each image frame will be delivered. When the line is free, the whole frame of each image will be transferred to the client. The receiver warns the sender of the condition of traffic congestion in the network by sending a special short frame for this specific purpose. The sender can respond to this information of warning by simply reducing the data rate which is adjusted with a neural network or fuzzy logic. In this way we can send a stream of moving images adaptively adjusting to the network traffic condition.

• Korean Journal of Computational Design and Engineering
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• v.11 no.3
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• pp.223-233
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• 2006

Layered manufacturing(LM) is emerging as a new technology that enables the fabrication of three dimensional heterogeneous objects such as Multi-materials and Functionally Gradient Materials (FGMs). Among various types of heterogeneous objects, more attention has recently paid on the fabrication of FGMs because of their potentials in engineering applications. The necessary steps for LM fabrication of FGMs include representation and process planning of material information inside an FGM. This paper introduces a new process planning algorithm that takes into account the processing of material information. The detailed tasks are discretization (i.e., decomposition-based approximation of volume fraction), orientation (build direction selection), and adaptive slicing of heterogeneous objects. In particular, this paper focuses on the discretization process that converts all of the material information inside an FGM into material features like geometric features. It is thus possible to choose an optimal build direction among various pre-selected ones by approximately estimating build time. This is because total build time depends on the complexity of features. This discretization process also allows adaptive slicing of heterogeneous objects to minimize surface finish and material composition error. In addition, tool path planning can be simplified into fill pattern generation. Specific examples are shown to illustrate the overall procedure.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.751-755
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• 1997

This paper presents a new scheme of neural network controller to improve to improve the robustuous of robot manipulator using digital signal processors. Digital processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and producrs of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fist in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exits relativly little gensral theoral for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..

• Journal of Korean Society for Quality Management
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• v.30 no.1
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• pp.74-96
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• 2002

The objectives of this study is to suggest the rectifying sampling inspection plan considering quality cost. Limiting quality level(LQL) plans(also called LTPD plans) and outgoing quality(OQ) plans are considered. The Hald's linear cost model is discussed with and without a beta prior for the distribution of the fraction of nonconforming items in a lot. It is assumed that the sampling inspection is error free. We consider the design of reliability acceptance sampling plan (RASP) for failure rate level qualification at selected confidence level. The lifetime distribution of products is assumed to be exponential. MIL-STD-690C and K C 6032 standards provide this procedures. But these procedures have some questions to apply in the field. The cost of test and confidence level(1-$\beta$ risk) are the problem between supplier and user. So, we suggest that the optimal life test sampling inspection plans using simple linear cost model considering product cost, capability of environment chamber, environmental test cost, and etc. Especially, we consider a reliability of lots that contain some nonconforming items. In this case we assumed that a nonconforming item fail after environmental life test. Finally, we develope the algorithm of the optimal sampling inspection plan based on minimum costs for rectifying inspection and RASP. And computer application programs are developed So, it is shown how the desired sampling plan can be easily found.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.7 s.94
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• pp.1649-1657
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• 1993

This paper reports on a proof-of-concept experimental investigation focused on evaluating the vibration characteristics and control of smart hollow cantilever beams filled with an electro-rheological(ER) fluid. The beams are considered to be of uniform viscoelastic materials and modelled as a viscously-damped harmonic oscillator. Electric field-dependent natural frequencies, loss factors and complex moduli are evaluated and compared among three different beams : two types of different volume fraction of ER fluid and one type of different particle concentration of ER fluid by weight. Modal characteristics of the beams are observed in both the absence and the presence of electric potentials. It is also shown that by constructing active control algorithm the removal of structural resonances and the suppression of tip deflection are obtained. This result provides the feasiblility of ER fluids as an active vibration control element.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.162-169
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• 1999

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital Signal Processors. Digital signal processors DSPs. are micro-processors that are particularly developed for variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a biable computatinal tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for implementation of real-time control of robot system by the simulation and experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8A
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• pp.601-611
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• 2012

In this paper, we first study the spatial multiplexing gain for the 3-cell interfering broadcast channels (IFBC) where all base stations and mobile users are equipped with multiple antennas. Then, we present the IA scheme in conjunction with user selection which outperforms the TDMA technique in the IFBC environment. The optimal scheduling method utilizes multiuser diversity to achieve a significant fraction of sum capacity by using an exhaustive search algorithm. To reduce the computational complexity, a suboptimal scheduling method is proposed based on a coordinate ascent approach.

• Education of Primary School Mathematics
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• v.8 no.2 s.16
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• pp.97-113
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• 2004

The purpose of this study is to develop instructional methods for the formalized algorithm through informal knowledge in teaching division of fractions. The following results have been drawn from this study: First, before students learn formal knowledge about division of fractions, they knowledge or strategies to solve problems such as direct modeling strategies, languages to reason mathematically, and using operational expressions. Second, students could solve problems using informal knowledge which is based on partitioning. But they could not solve problems as the numbers involved in problems became complex. In the beginning, they could not reinvent invert-and-multiply rule only by concrete models. However, with the researcher's guidance, they can understand the meaning of a reciprocal number by using concrete models. Moreover, they had an ability to apply the pattern of solving problems when dividend is 1 into division problems of fractions when dividend is fraction. Third, instructional activities were developed by using the results of the teaching experiment performed in the second research step. They consist of student's worksheets and teachers' guides. In conclusion, formalizing students' informal knowledge can make students understand formal knowledge meaningfully and it has a potential that promote mathematical thinking. The teaching-learning activities developed in this study can be an example to help teachers formalize students' informal knowledge.