• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.258-262
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• 1990

Several optimum control algorithms have been proposed to minimize the robot cycle time by velocity scheduling. Most of these algorithms assume that the dynamic and kinematic characteristics of a manipulator are fixed. This paper presents the study of a minimum-time optimum control for robotic manipulators considering parameter changes. A complete set of solutions for parameter identification of the robot dynamics has been developed. The minimum-time control algorithm has been revised to be updated using estimated parameters from measurements.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.23-24
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• 2007

Ethernet passive optical network (EPON) is a technology to solve the access network bottleneck and to realize fiber to the home (FTTH). In EPON, the dynamic bandwidth allocation (DBA) is important because all users share common line in upstream. In this paper, we propose new DBA named as modified EPON dynamic scheduling algorithm (MEDSA) and simulate new DBA using Matlab.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.148-149
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• 2014

This paper evaluates performance of a pipelined dynamic bandwidth allocation scheme for XG-PON (10-Gbps-capable passive optical network) system for power saving. Under self-similar traffic and balanced input loads, we evaluate performance of XG-PON systems using computer simulations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.866-874
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• 2006

This paper proposes a new Dynamic Voltage Scaling(DVS) algorithm to achieve low-power scheduling of aperiodic hard real-time tasks. Aperiodic tasks schedulingcannot be applied to the conventional DVS algorithm and result in consuming energy more than periodic tasks because they have no period, non predictable worst case execution time, and release time. In this paper, we defined Virtual Periodic Task Set(VTS) which has constant period and worst case execution time, and released aperiodic tasks are assigned to this VTS. The period and worst case execution time of the virtual task can be obtained by calculating task utilization rate of both periodic and aperiodic tasks. The proposed DVS algorithm scales the frequency of both periodic and aperiodic tasks in VTS. Simulation results show that the energy consumption of the proposed algorithm is reduced by 11% over the conventional DVS algorithm for only periodic task.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.711-713
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• 1996

This paper proposes a unit commitment scheduling method based on Genetic Algorithm(GA). Due to a variety of constraints to be satisfied, the search space of the UC problem is highly nonconvex, so the UC problem cannot be solved efficiently only using the standard GA To efficiently deal with the constraints of the problem and greatly reduce the search space of the GA, the minimum up and down time constraints are embedded in the binary strings that are coded to represent the on-off states of the generating units. The violations of other constraints arc handled by integrating penalty factors. To show the effectiveness of the GA based unit commitment scheduling, test results for system of 5 units are compared with results obtained using Lagrangian Relaxation and Dynamic Programming.

• ETRI Journal
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• v.30 no.2
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• pp.183-193
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• 2008

In this paper, we propose quality of service mechanisms for flow-based routers which have to handle several million flows at wire speed in high-speed networks. Traffic management mechanisms are proposed for guaranteed traffic and non-guaranteed traffic separately, and then the effective harmonization of the two mechanisms is introduced for real networks in which both traffic types are mixed together. A simple non-work-conserving fair queuing algorithm is proposed for guaranteed traffic, and an adaptive flow-based random early drop algorithm is proposed for non-guaranteed traffic. Based on that basic architecture, we propose a dynamic traffic identification method to dynamically prioritize traffic according to the traffic characteristics of applications. In a high-speed router system, the dynamic traffic identification method could be a good alternative to deep packet inspection, which requires handling of the IP packet header and payload. Through numerical analysis, simulation, and a real system experiment, we demonstrate the performance of the proposed mechanisms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.6 s.336
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• pp.33-40
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• 2005

In this paper, we analyzed the DRMA(Dynamic Reservation Multiple Access) protocol with Rayleigh fading, shadowing, and capture effect for the Broadband fireless Access System. We consider the TDMA-based protocols, since these are based on the standard for IEEE 802.16 WMAN, IEEE 802.20 MBWA, and ETSI HIPERLAN//2. The results of analytical model will be apply the development of collision resolution algorithm, scheduling algorithm and the dynamic change of system parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3B
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• pp.264-273
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• 2009

For IEEE 802.15.3 HR-WPAN, we propose the DABL algorithm that PNC can allocate the channel times to the DEV in super frame in order that system frame throughput is increased and the delay is decreased. In detail, the DABL algorithm allows to dynamically allocate channel time as well as to adaptively apply the modulation and coding scheme based on the link quality of the DEV. In addition, due to the facts that QoS is quite different depending on service types, we provide the DABL algorithm taking into account RT(Real Time) traffic and Non-RT traffic respectively. Finally, we show simulation results of the DABL algorithm compared to the conventional algorithm that the PNC equally allocates channel times to the DEV regardless of the link quality of the DEV.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.161-172
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• 2007

Vehicles transporting hazardous materials can make huge damage to people, properties and environment by traffic accidents. Therefore, transporting hazardous materials is a big issue with the cutting edge technology of communications in these days. However, despite this situation, Korean government gives limited efforts for systematic management, research and investment about hazardous materials. Accordingly, this research suggests the key path finding algorithm about management of real-time schedule and routes for vehicles transporting hazardous materials. Besides, the case study is progressed in transportation networks of Seoul in order to evaluate the reality of algorithm. Specifically, time-space network transformation is performed for time window attributes. In addition, this study proposes the techniques searching for non-dominated paths considering schedule by the multiobjective shortest path algorithm based on dynamic programming in dynamic transportation networks including multiobjective attributes.