• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.166-168
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• 1996

This paper presents an power system optimization method which solves real and reactive power dispatch problems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP), and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods, applied to the IEEE 30-bus system, were run for 12 other exogenous parameters. Each simulation result, by which evolutionary computations are compared and analyzed, shows the possibility of applications of evolutionary computation to large scale power systems.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.893-896
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• 1998

A new evolutionary programming technique using multiple subpopulations with completely differnt evolution mechanisms is propsed to solve the optimization problems. Three subpopulations, each has different evolution charcteristics and uses different EP algorithms such as SAEP, AEP and FEP, are cooperating with synergy effect in which it increases the possibility to quickly find the global optimum of continuous optimization problems. Subpopulations evolve in differnt manner and the interaction among these leads to global minimum quickly.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.7
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• pp.318-323
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• 2001

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at KwangYang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC), which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.116-118
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• 2000

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at Kwangyang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC) which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.302-305
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• 1996

This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.259-262
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• 1997

This paper presents a visual servoing of RV-M2 robot manipulators to track and grasp moving object, using pruned dynamic recurrent neural networks(DRNN). The object is stationary in the robot work space and the robot is tracking and grasping the object by using CCD camera mounted on the end-effector. In order to optimize the structure of DRNN, we decide the node whether delete or add, by mutation probability, first in case of delete node, the node which have minimum sum of input weight is actually deleted, and then in case of add node, the weight is connected according to the number of case which added node can reach the other nodes. Using evolutionary programming(EP) that search the struture and weight of the DRNN, and evolution strategies(ES) which train the weight of neuron, we pruned the net structure of DRNN. We applied the DRNN to the Visual Servoing of a robot manipulators to control position and orientation of end-effector, and the validity and effectiveness of the pro osed control scheme will be verified by computer simulations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.211-217
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• 1995

Conventional linear control fails to provide precise positioning of a control object under the influence of friction, deadzone, saturation, etc. This paper proposes a high-precision control scheme for a precise point-to-point positioning system, called an X-Y table, even under the same influences above. The proposed scheme is composed of a fuzzy precompensator and a PD controller. The fuzzy precompensator is employed to improve the performance of the PD controller. Its fuzzy rules are obtained from experimental evolutionary programming (EP), not from an expert. The effectiveness of the scheme is demonstrated by experiments on the X-Y table. with a positioning error of within 1$\mu\textrm{m}$.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.12
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• pp.584-590
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• 2001

This paper presents a windows program package for solving security constrained OPF in interconnected Power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SYC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to IEEE 14 buses and 10 machines 39 buses model system.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.239-242
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• 2001

This paper presents a windows program package for solving security constrained OPF in interconnected power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SVC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow. In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to 10 machines 39 buses model system.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1269-1271
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• 1996

This paper presents a visual servoing combined by evolutionary algorithms and neural network for a robotic manipulators to control position and orientation of the end-effector. Using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we generate the control input to agree the target image, to realize the visual servoing. The validity and effectiveness of the proposed control scheme will be verified by computer simulations.