• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.209-211
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• 1986

The continuous time linear quadratic problem (LQP) has been applied to the control of a 8-tray distillation column using the code VASP. The weighting matrices for the state variables and control variables were adjusted iteratively. The simulation results of the optimal control with 2 inputs and 2 outputs showed that the LQP method is very satisfactory for a rapid response and feedback control, and any desired response could be obtained by adjusting the weighting matrices Q under = and R under =. The feedback gain matrix K under = was also determined.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.37-42
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• 2004

This paper presents an optimal and robust tuning method of decentralized PI controller for the TITO second order systems to be formulated as LQR. The procedure is developed by establishing relationships between the closed-loop state equation including the decentralized PI tuning parameter and the . closed-loop state equation of LQR and by selecting the weighting factors Q and R of the cost function in order to satisfy the design specifications In frequency domain which the stability robustness and satisfied the performance guaranteed.

• Journal of the Korean Institute of Navigation
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• v.21 no.1
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• pp.109-118
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• 1997

In this paper, applications of multilayer neural networks to control of flexible robot beam are considered. The multilayer nerual networks can be used to approximate any continuous function to a desired degree of accuracy and the weights are updated by Gradient Method. When a flexible beam is rotated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlled insuch a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipulators so that is arrested as soon as possbile at the end of rotation. Accurate control of lightweight beam during the large changes in configuration common to robotic tasks requires dynamic models that describe both rigid body motions, as well as the flexural vibrations. Therefore, a linear dynamic state-space model of for a single link flexible robot beam is derived and PD controller, LQP controller, and inverse dynamical neural networks controller are composed. The effectiveness the proposed control system is confirmed by computer simulation.