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유전알고리즘을 이용한 로봇 매니퓰레이터의 동적제어기 설계

Design of a Dynamic Controller for Robot Manipulators Using Genetic Algorithm

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키워드

주제분류기계공학

초록

Robot manipulators are highly nonlinear system with multi-inputs multi-outputs, and various control methods for the robot manipulators have been developed to acquire good trajectory tracking performance and improve the system stability lately. The computed torque controller has nonlinear feedforward control elements and so it is very effective to control robot manipulators. If the control gains of the computed torque controller is adjusted according the payload, then more precise control performance is attained. This paper extends the conventional computed torque controller in the joint space to the Cartesian space, and optimize the control gains for some specified payloads in both joint and Cartesian spaces using genetic algorithms. Also a neural network is employed to have proper control gains for arbitrary payloads using generalization properties of the neural network. Computer simulation results show that the proposed control system for robot manipulators has excellent performance in various conditions.

Abstract

Robot manipulators are highly nonlinear system with multi-inputs multi-outputs, and various control methods for the robot manipulators have been developed to acquire good trajectory tracking performance and improve the system stability lately. The computed torque controller has nonlinear feedforward control elements and so it is very effective to control robot manipulators. If the control gains of the computed torque controller is adjusted according the payload, then more precise control performance is attained. This paper extends the conventional computed torque controller in the joint space to the Cartesian space, and optimize the control gains for some specified payloads in both joint and Cartesian spaces using genetic algorithms. Also a neural network is employed to have proper control gains for arbitrary payloads using generalization properties of the neural network. Computer simulation results show that the proposed control system for robot manipulators has excellent performance in various conditions.

참고문헌 (13)

  1. 오연택, "산업용 스카라 로봇의 구조해석에 관한 연구", 한국기계기술학회지, 19(6), pp.866~871 (2017), 한국기계기술학회[DOI]
  2. K. J. Astrom, "The future of PID control", Control Engineering Practice, 9, pp.1163~1175 (2001)
  3. J. E. Slotine, "Adaptive manipulator control : a case study", IEEE transactions on automatic control, 33(11), pp.995~1003 (1988)
  4. T. Ozaki, "Trajectory control of robotic manipulator using neural networks", IEEE Transactions on Industrial Electronics, 38(3), pp.195~202 (1991)
  5. 이현철, "PID제어기와 퍼지제어기를 이용한 유연한 로봇팔끝 지점 위치와 진동제어에 관한 연구", 한국기계기술학회지, 18(4), pp.529~535 (2016), 한국기계기술학회[DOI]
  6. Sangdani, M. H., "Genetic algorithm-based optimal computed torque control of a vision-based tracker robot : Simulation and experiment", Engineering Applications of Artificial Intelligence, 67, pp.24~38 (2018)
  7. Ullah, M. I., "Modeling and computed torque control of a 6 degree of freedom robotic arm", Robotics and Emerging Allied Technologies in Engineering (iCREATE), pp.133~138 (2014)
  8. Qu Z., "Robust control of robots by the computed torque law", Systems & control letters, 16(1), pp.25~32 (1991)
  9. Gilbert, Elmer G., "An approach to nonlinear feedback control with applications to robotics", IEEE transactions on systems, man, and cybernetics, 6, pp.879~884 (1984)
  10. Chen, Y., "Adaptive fuzzy computed-torque control for robot manipulator with uncertain dynamics", International Journal of Advanced Robotic Systems, 9(6), pp.237~245 (2012)
  11. J. Lin, "Pseudo-inverse Jacobian control with grey relational analysis for robot manipulators mounted on oscillatory bases", Journal of Sound and Vibration, 326(3-5), pp.421~437 (2009)
  12. L. Sciavicco, "Modelling and Control of Robot Manipulators" (2000), Springer-Verlag New York, Inc
  13. Mohammed, Reham H., "Trajectory tracking control for robot manipulator using fractional order-fuzzy-PID controller", International Journal of Computer Applications, 134(15) (2016)

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