Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Optimal Control of Time and Energy for Mobile Robots Using Genetic Algorithm

유전알고리즘을 이용한 이동로봇의 시간 및 에너지 최적제어

  • Park, Hyeon-jae (Department of Electrical and Computer Engineering, Pusan National University) ;
  • Park, Jin-hyun (Dep. of Mechatronics Engineering, Kyeongnam National University of Science and Technology) ;
  • Choi, Young-kiu (Department of Electrical Engineering, Pusan National University)
  • Received : 2016.11.29
  • Accepted : 2016.12.19
  • Published : 2017.04.30
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Abstract

It is very difficult to solve mathematically the optimal control problem for non - linear mobile robots to move to target points with minimum energy related to velocity, acceleration and angular velocity in minimum time. This paper proposes a method to obtain optimal control gains with which mobile robots move with minimum energy related to velocity, acceleration and angular velocity in minimum time using genetic algorithms. Mobile robots are non - linear systems so that their optimal control gains depend on initial positions. Hence initial positions are divided into some partition points and optimal control gains are obtained at each partition point with genetical algorithms. These optimal control gains are used to train neural networks that generate proper control gains at arbitrary initial position. Finally computer simulation studies have been conducted to verify the effectiveness of the method proposed in this paper.

비선형 시스템의 이동 로봇을 원하는 목표점으로 속도, 가속도 그리고 각속도 관련 에너지를 최소한으로 사용하여 최단시간 안에 이동시키는 최적의 제어 문제를 수학적으로 푸는 것이 매우 어렵다. 본 논문에서는 유전알고리즘을 이용하여 이동 로봇의 속도, 각속도 관련 에너지를 최소화하면서 최단시간 안에 이동할 수 있는 최적제어이득을 구한다. 이동 로봇은 비선형시스템이므로 초기위치에 따라 최적제어이득이 다르게 결정된다. 따라서 초기위치 분할 점들을 설정하고 각 분할 점에서 유전알고리즘을 이용하여 최적제어이득을 구한다. 각 분할 점에서 구한 최적제어 이득으로 신경회로망을 학습시켜서 임의의 초기위치에 대한 제어이득을 구할 수 있다. 마지막으로 본 연구의 유용성을 컴퓨터 시뮬레이션 연구로 확인한다.

Keywords

References

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