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小島, 宏行 ; 板垣, 修 ; 小林, 敏雄
概要:
application/pdf<br />Journal Article<br />In this paper, the equations of motion of the non-contact hold and transfer co
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ntrol system of a spherical magnetic body using a one-pole-type magnetic robot hand system are derived. The robot hand system consists of a two-link robot arm and a one-pole-type magnetic hand. The Iinearized state equation and the linearized output equation of the magnetic robot hand, are derived and the controllability and observability are then clarihed. The non-contact hold control system by the magnetic robot hand is then constructed using H_∞ control based on the normalized coprime factorization method, and the tracking control system of the robot arm is constructed using the disturbance observer. It is confirmed from the experimental results that the non-contact hold and transfer control of the spherical magnetic body can be implemented well using the present control system.
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小島, 宏行 ; 木村, 仁次郎 ; 小林, 敏雄
概要:
application/pdf<br />Journal Article<br />In this paper, the magnetic levitation neuro-adaptive control method of a body by use of an electromagnet attached to a vertical robot with a prismatic joint is presented, and the usefulness of the
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present control method is confirmed by experiment and numerical simulation. When the gap between the levitated body and the electromagnet hand varies, an adaptive control method to compensate the nonlinear characteristics of the magnetic attracting force is desirable. The magnetic levitation neuro-adaptive control system consists of a PD feedback control loop and an adaptive mechanism based on a neural network. From the experimental results and the numerical simulation results, it is confirmed that the levitated body can be controlled successfully by the present magnetic levitation neuro-adaptive control method.
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劉, 英男 ; 小島, 宏行 ; 金, 元甲 ; 小林, 敏雄
概要:
application/pdf<br />Journal Article<br />This paper describes the swing-up trajectory learning and motion control of an inverted pendulum control robot based on fuzzy logic. The learning algorithm obtaining the optimal swing-up
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trajectory of the inverted pendulum is constructed based on fuzzy logic. From the experimental results, it is confirmed that the optimal swing-up trajectory can be obtained by the present fuzzy learning algorithm. The swing-up and stabilizing fuzzy control system is constructed with the variable-gain fuzzy logic controller and the velocity feedback loops. Then the experimental results for the swing-up and stabilizing fuzzy control are shown, and the excellent performance of the present fuzzy motion control system is clarified. Furthermore, a numerical simulation has been carried out, and the numerical simulation results agree well with the experimental results.
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