• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.792-795
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• 1999

Since the inception of fuzzy control, lots of methods to design fuzzy controller have been reported, However, it is admitted that these methods are tailored to special problems and cannot be used in general control situation. Therefore this paper proposes auromatic generation algorithm of fuzzy control system and develops an automatic fuzzy controller generator. For that purpose, the genetic algorithm is used and it searches for the optimal parameters to design the fuzzy controller

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1475-1482
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• 2015

In network routers, buffers are used to resolve congestion and reduce packet loss rate whenever congestion occurs at bottleneck link. Most of the existing methods to manage such buffers focus only on queue-length-based control as one loop which have some issues of low link utilization and system stability. In this paper, we propose a novel framework which exploits two-loop control method, e.g. queue-length and congestion window size, combined with optimal margin method to facilitate parameter choices. Simulation results in ns-2 demonstrate that bottleneck link performance can be improved with higher link utilization (85%) and shorter queue length (22%) than the current deployed scheme in commercial routers (RED and DropTail).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5328-5346
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• 2016

An optimal power control algorithm based on convex optimization is proposed for base stations in long term evolution networks. An objective function was formulated to maximize the proportional fairness of the networks. The optimal value of the objective function was obtained using convex optimization and distributed methods based on the path loss model between the base station and users. Field tests on live networks were conducted to evaluate the performance of the proposed algorithm. The experimental results verified that, in a multi-cell multi-user scenario, the proposed algorithm increases system throughputs, proportional fairness, and energy efficiency by 9, 1.31 and 20.2 %, respectively, compared to the conventional fixed power allocation method.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.215-228
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• 2007

By using the variational calculus of fractional order, one derives a Hamilton-Jacobi equation and a Lagrangian variational approach to the optimal control of one-dimensional fractional dynamics with fractional cost function. It is shown that these two methods are equivalent, as a result of the Lagrange's characteristics method (a new approach) for solving non linear fractional partial differential equations. The key of this results is the fractional Taylor's series $f(x+h)=E_{\alpha}(h^{\alpha}D^{\alpha})f(x)$ where $E_{\alpha}(.)$ is the Mittag-Leffler function.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1389-1391
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• 1996

In this paper, we applies two methods - Genetic Algorithm(GA) and $A^*$ Algorithm - to find the optimal path in route guidance system. Under the assumption that the traveling costs of each link are given, the task to find the optimal path becomes very complicated problem if the number of nodes or links increase. Two well-known algorithms are modified to resolve the problem and the preliminary demonstration show both optimistic result and needs to improvement.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.611-613
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• 2004

This paper is concerned with the simulation and determination of the input voltage and frequency for the optimal efficiency operation of induction motors. In general, induction motors have a specific character that operation efficiency is dropped sharply at the light roads condition. Consequently, if the induction motor is controlled by high efficiency using the VVVF(variable voltage variable frequency) control methods at optimal values, the entire system can obtain the substantial energy savings from the efficiency improvement in induction motors. In this paper, optimal slip is derived from the modeling of an induction motor and the optimal hybrid-control method is suggested by the simulation of the proposed algorithm for a 3-phase induction motor.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.149-157
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• 2008

The reduction of leakage is a major issue of the South Korea water industry. The inclusion of pressure dependent leakage terms in network analysis allows the application of optimization techniques to identify the most effective means of reducing water leakage in distribution networks. This paper proposes a method to find optimal setting and location of control valve for reducing leakage efficiently. The proposed search method differs from previous methods for addressing optimal valve location problem and improves the GA simulation time with guaranteeing for getting the global optimal solution. The strength of this method has been demonstrated by means of case studies. This allows the procedure of optimization to be more robust and computational efficient.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.147-151
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• 1991

In this paper a time-optimal path planning scheme for the multiple robot manipulators will be proposed by using hopfield neural network. The time-optimal path planning, which can allow multiple robot system to perform the demanded tasks with a minimum execution time and collision avoidance, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to rearrange the problem as MTSP(Multiple Travelling Salesmen Problem) and then apply the Hopfield network technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning of the multiple robots by using Hopfield neural network. The effectiveness of the proposed method is demonstrated by computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.241-247
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• 2011

This paper is intended to improve efficiency of two-phase BLDC motor using analytical and statistical methods, and then the stability of the starting for the designed model is investigated. The characteristics of the motor according to magnetization directions of permanent magnet are analyzed through the analytical method, and design variables that affect the efficiency are selected. Preliminary optimal design is performed using the analytical method with the design variable. The RSM (Response Surface Method) based on the FEA (Finite Element Analysis) is applied to complement errors of the analytical method. As a result, the optimal design is determined. Finally, the stability of the starting for the optimal designed model is evaluated by analyzing cogging torque, and it is verified through the FEA.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.737-742
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• 2011

Navigation problems include the task of determining the control input under various constraints for systems such as mobile robots subject to uncertain disturbance. Such tasks can be modeled as constrained stochastic control problems. In order to solve these control problems, one may try to utilize the dynamic programming(DP) methods which rely on the concept of optimal value function. However, in most real-world problems, this trial would give us many difficulties; for examples, the exact system model may not be known; the computation of the optimal control policy may be impossible; and/or a huge amount of computing resource may be in need. As a strategy to overcome the difficulties of DP, one can utilize ADP(approximate dynamic programming) methods, which find suboptimal control policies resorting to approximate value functions. In this paper, we apply recently proposed ADP methods to a class of navigation problems having complex constraints, and observe the resultant performance characteristics.