• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.5
• /
• pp.644-650
• /
• 1998

In this paper , a state space model for flexible beam is presented using the assumed-modes approach. The state space equation is derived for a flexible beam in which one end is connected to a motor and is driven by a torque equation and the other end is free. Many of the transfer function proposed thus far use the torque to the flexible beam as the input and the tip deflection of the flexible beam as the output. The Technique for the analysis and synthesis of the dual-input describing function(DIDF) is introduced here and the construction of a non-linear compensator, based on this technique, is proposed. This non-linear compensator, properly connected in the direct path of a closed-loop linear or non-linear control system. The above non-linear network is used to compensate linear and non-linear systems for instability, limit cycles, low speed of response and static accuracy. The effectiveness of the proposed scheme is demonstrated through computer simulation and experimental results.

• Proceedings of the KIEE Conference
• /
• 1993.11a
• /
• pp.304-306
• /
• 1993

In this paper, the authors show a link between a heuristic controller used in industry and a theoretical generalized controller. First, we clarify the internal structure of the generalized two-degree-of-freedom controller which yields a link between the theoretical researches and the practical applications. Secondly, we indicate how to blend identification and control together without any modification of the controller. This is in fact the problem of closed-loop identification. Thirdly, we propose a design technique of a free parameter taking into account a robust stability based on the information obtained from the identification. Finally, we apply the proposed algorithm to trajectory control of DD robot.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2305-2308
• /
• 1998

In this paper, a control algorithm which enables robot to cooperate with human is proposed. The method senses the humanbeing's intention by using force/torque sensor attached at the end effector and moves and cooperates as intended by humanbeing. The method also considers safety of the humanbeing by adjusting and limiting the robot speed automatically. The proposed method is verified its performance by computer simulation and experiments for the 2-DOF DD(Direct Drive) Arm in real-time

• Journal of Advanced Marine Engineering and Technology
• /
• v.23 no.2
• /
• pp.168-175
• /
• 1999

Unlike a general inverted pendulum system which is moved on the cart the proposed inverted pendulum system in this paper has an inverted pendulum which is moved on the two-degree-of-freedom parallelogram link. The dynamic equation of the pendulum system activated by the DD(Direct Drive)motor includes many nonlinear terms and has the high degree of freedoms. The problem is followed hat the exact mathmatical equations can not be analized by a general linear theory However the neural network trained by a simple learning method can control the dynamic system with hard nonlinearities. Learning procedure is the backpropagation algorithm with super-visory signal. The plant inputs obtained by the designed neural network in this paper can stabilize the pendu-lem and get the servo control. Experiment results have proce the effectiveness of the designed neural network controller.