• 제어로봇시스템학회논문지
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• 제17권8호
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• pp.739-746
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• 2011

Recently, recommender systems have been widely applied in E-commerce websites to help their customers find the items what they want. A recommender system should be able to provide users with useful information regarding their interests. The ability to immediately respond to the changes in user's preference is a valuable asset of recommender systems. This paper proposes a novel recommender system which aims to effectively adapt and respond to the immediate changes in user's preference. The proposed system combines IEC (Interactive Evolutionary Computation) with a content-based filtering method and also employs data grouping in order to improve time efficiency. Experiments show that the proposed system makes acceptable recommendations while ensuring quality and speed. From a comparative experimental study with an existing recommender system which uses the content-based filtering, it is revealed that the proposed system produces more reliable recommendations and adaptively responds to the changes in any given condition. It denotes that the proposed approach can be an alternative to resolve limitations (e.g., over-specialization and sparse problems) of the existing methods.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.256-263
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• 1998

Among process synthesis problems, the heat exchanger network (HEN) has been subjected to the most concentrated effort because this kind of problems was well defined for solving it and 20-30% energy savings could be realized in the present chemical processes. In this paper, we use an evolutionary approach for HEN synthesis because this approach can overcome the local optimum and combine some heuristic rules. The basic evolutionary approach is composed of three parts, that is, initialization step, growth step and mutation step, as in the simulated annealing and genetic algorithm. This algorithm uses the ecological rule that a better cell will live and worse cell should decompose after repeated generations. With this basic concept, a new procedure is developed and a more efficient method is proposed to generate initial solutions. Its effectiveness is shown using test examples.

• 제어로봇시스템학회논문지
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• 제12권4호
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• pp.328-338
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• 2006

A new evolutionary computation technique, called particle swarm optimization(PSO), has been proposed and introduced recently. PSO has been inspired by the social behavior of flocking organisms, such as swarms of birds and fish schools and PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. In this paper, characteristics of PSO such as mentioned are reviewed and compared with GA which is based on the evolutionary mechanism in natural selection. Also dimensionalities of PSO and GA are compared throughout numeric experimental studies. The comparative studies demonstrate that PSO is characterized as simple in concept, easy to implement, and computationally efficient and can generate a high-quality solution and stable convergence characteristic than GA.

• 제어로봇시스템학회논문지
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• 제15권6호
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• pp.604-611
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• 2009

Modular snake-like robots are robust for failure and have flexible locomotion for environments, but are difficult to control. Various phase and evolutionary approaches for modular robots have been studied for many years, but there are few comparisons among these methods. In this paper, Phase, GAps, GA and GP approaches are implemented and compared for flat, stairs, and slope environments. In addition, simulations of the locomotion evolution for modular snake-like robot are executed in Webots environments.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.616-623
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• 1998

Holland가 제안한 단순 유전자 알고리즘은 다원의 자연선택설을 기본으로 한 군 기반의 최적화 방법으로서, 이론적 기반으로는 스키마 정리와 빌딩블록 가설이 있다. 단순 유전자 알고리즘(SGA)이 이러한 이론적 기반에도 불구하고 여전히 일부 문제에 있어서 최적해로의 수렴을 보장하지 못하고 있다. 따라서 최근에 두 개의 집단이 서로 상호작용을 하며 진화하는 공진화 방법에 의해 이러한 문제를 해결하려고 하는데 많은 관심이 모아지고 있다. 본 논문에서는 이러한 공진화 방법이 잘 동작하는지에 대한 이론적 기반으로 확장 스키마 정리를 제안하고, SGA에서는 해결하지 못하는 최적화 문제, 예를 들면 deceptive function,에서 SGA와 공진화에 의한 방법을 비교함으로써 확장된 스키마 정리의 유효성을 확인한다.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.242-248
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• 2007

In this paper, we implement the internet-based remote control system for intelligent robot. For remote control of the robot, it uses the socket communication of the TCP/IP. It consists of the user interface and the robot control interface. Robot control interface transmits the navigation and environmental informations of the robot into the user interface. In order to transmit the large environmental images, a JPEG compression algorithm is used. User interface displays the navigation status of the robot and transmits the navigation order into the robot control interface. Also, we propose the design method of the fuzzy controller using navigation data acquired by expert's knowledge or experience. To do this, we use virus-evolutionary genetic algorithm(VEGA). Finally, we have shown the proposed system can be operated through the real world experimentations.

• 제어로봇시스템학회논문지
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• 제19권10호
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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.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.322-329
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• 2005

This paper considers the application of mobile robot to the herding problem. The herding problem involves a ‘pursuer’ trying to herd a moving ‘evader’ to a predefined location. In this paper, two mobile robots act as pursuer and evader in the fenced area, where the pursuer robot uses a fuzzy cooperative decision strategy (FCDS) in the herding algorithm. To herd evader robot to a predefined position, the pursuer robot calculates strategic herding point and then navigates to that point using FCDS. FCDS consists of a two-level hierarchy: low level motion descriptors and a high level coordinator. In order to optimize the FCDS, we use the multi­thread evolutionary programming algorithm. The proposed algorithm is implemented in the real mobile robot system and its performance is demonstrated using experimental results.

• 제어로봇시스템학회논문지
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• 제3권3호
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• pp.259-264
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• 1997

널리 쓰이는 진화 알고리즘은 크게 두가지가 있다. 유전 알고리즘과 진화 기법이 그것이다. 이들 알고리즘은 실행 전에 사용자가 정해주어야 하는 변수들을 가지고 있다. 본 논문에서는 이 두 알고리즘을 일반화시키고 집단의 크기, 교차변이 연산자 적용 확률 그리고 돌연변이 연산자 적용 확률과 같은 변수들을 알고리즘이 수행되는 동안 스스로 정하는 일반화된 자기 형성 진화 알고리즘을 제안한다. 제안된 알고리즘의 타당성과 효용성은 시스템 동정화와 다개체 시스템 제어의 두가지 복잡한 제어 문제에 대한 적용을 통해 보여진다.

• 제어로봇시스템학회논문지
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• 제16권2호
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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.