• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.412-419
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• 2008

Genetic algorithms are efficient techniques for searching optimum solution but have the premature convergence problem getting stuck in the local optimum according to the evolutionary operator. In this paper we analyzed the reason for converging to the local optimum and proposed the method which able transit to the global optimum from the local optimum. In these methods we used the variable evolutionary operator with the average hamming distance, to maintain the genetic diversity of the population for getting out of the local optimum. The theoretical results are proved by the simulation experiments.

• 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 KIEE Conference
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• 1999.07b
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• pp.550-552
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• 1999

This paper describes a control technique of coupled tank level using Evolutionary Neural Network. In general, the control of tank level without a dangerous overflow and with a high accuracy is difficult because of higher order time delay and nonlinearity. Nonetheless, proposed Evolution Neural Network controller in this paper was successfully implemented and simulation results of the superiority over a conventional PID one was investigated.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.33.1-33
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• 2001

We address a novel approach to identify a nonlinear dynamic system for Wiener models, which are composed of a linear dynamic system part followed by a nonlinear static part. The aim of system identification here is to provide the optimal mathematical model of both the linear dynamic and the nonlinear static parts in some appropriate sense. Assuming the nonlinear static part is invertible, we approximate the inverse function by a piecewise linear function. We estimate the piecewise linear inverse function by using the evolutionary computation approach such as genetic algorithm (GA) and evolution strategies (ES), while we estimate the linear dynamic system part by the least squares method. The results of numerical simulation studies indicate the usefulness of proposed approach to the Wiener model identification.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.867-872
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• 2013

Many practical processes in industry have nonlinearities of some forms. One commonly encountered form is actuator saturation which can cause a detrimental effect known as integrator windup. Therefore, a strategy of attenuating the effects of integrator windup is required to guarantee the stability and performance of the overall control system. In this paper, optimal tuning of a PID (Proportional-Integral-Derivative) controller with an anti-windup scheme is presented to enhance the tracking performance of the PID control system in the presence of the actuator saturation. First, we investigate effective anti-windup schemes. Then, the parameters of both the PID controller and the anti-windup scheme are optimally tuned by an EA (Evolutionary Algorithm) such as the IAE (Integral of Absolute Error) is minimized. A set of simulation works on two high-order processes demonstrates the benefit of the proposed method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.216-217
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• 2011

The problem of automated stacking cranes (ASC) dispatching in container terminals is addressed in this paper. We propose a heuristic-based ASC dispatching approach which adopts multi-criteria decision strategy. By aggregating different criteria the proposed strategy can consider multiple aspects of the dispatching situation and make robust decision in various situations. A multi-objective evolutionary algorithm (MOEA) is adopted to tune the weights associated to each criteria to minimize both the quay crane delay and external truck delay. The proposed approach is validated by comparison with different dispatching heuristics and simulation results obtained confirms its effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.107-113
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• 2010

In this paper, a prototype of cooperative work model for multi-robots system is introduced and the evolutionary approach is applied to generate the motions for the cooperative works of multi-robots system using genetic algorithm. The cooperative tasks can be performed by a humanoid robot and a mobile robot to deliver objects from shelves. Generation of the humanoid motions such as pick up, rotation, and place operation for the cooperative works are evolved. Modeling and computer simulation for the cooperative robots system are executed in Webots environments. Experimental results show the feasible and reasonable solutions for humanoid cooperative tasks are obtained.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.149-150
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• 2008

Generally, the propeller shaft rate (PSR) estimation algorithm for the classification of the sonar target has the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family from the frequency spectrum, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.83-89
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• 2001

This paper provides a short description of the COMPASS-model which is a concept for the simulation of multiway systems. The focus of the COMPASS-model is to offer an opportunity to investigate the effects of redistribution strategies on logistic and monetary values in a system of returnable transport items (RTI). The modeling concept consists of five modules: topology, system load, distribution, redistribution, cost. It includes the integration of highly sophisticated evolutionary algorithms for the optimal solving of complex capacitated vehicle routing problems (CVRP) which are typical for RTI-systems. The results of first experiments with a COMPASS-based prototype are repeated. They reveal some basic regularities in RTI-systems.

• Korean System Dynamics Review
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• v.5 no.1
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• pp.73-97
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• 2004

This paper explores the relationship between technological characteristics within process innovation and selection of the firms of different organizational forms in the evolution of an industry. For this purpose, this paper develops a simulation model for industrial change that replicates dynamic competition for process innovation. The simulation analysis found the following causal relationship. First, the stronger innovation impact in terms of productivity jump tends to enlarge the productivity difference among the incumbent firms and increase the speed of productivity catch-up by the large diversified firms, Second, the possibility of entry, and eventual dominance by the large diversified firms increase when the innovation-productivity linkage is stronger and there is less cumulativeness in productivity determination. These results imply that technological characteristics are important factors that have influence on whether or not the large diversified firms can enter and succeed in an industry.