• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2788-2790
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• 2002

In this paper, we designed neural network predictive two degree of freedom PID controller to control sway of crane Crane's trolley arrive minimum oscillation of transfer body and establishment position in minimum time. When various establishment location and surrounding disturbance were approved based on mathematical modeling of crane, controller designed to become effective control location error and oscillation angle of two control variables that simultaneously can predictive control. We wish to develop automatic travel control system through anti-sway skill of crane.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.9
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• pp.861-869
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• 2012

This paper presents a high performance position controller in a driving system using a time optimal control which is widely used to control driving systems to a desired reference position or velocity in minimum response time. The main purpose of this study is an improvement of transient response performance rather than steady-state response comparing with another various control strategies. In order to improve the performance of time optimal control, we tried to find the cause of the steady-state error in the driving system we have already made up and also suggest the newly modified type of time optimal control method in this paper.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.168-169
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• 2022

In this study, we investigates the auto-berthing problem for the underactuated surface vessel in the presence of constraints of dynamic uncertainties, finite time, transmission load, and environmental disturbance. A novel control scheme is proposed by fusing the finite time control technology and the event-triggered input algorithm. In the algorithm, differential homeomorphism coordinate the transformation is used to solve the problem of underactuation. Then, we apply the finite time technology and event triggered to save the time of the berthing vessel and relieve transmission burden between the controller and the vessel respectively. Moreover, a radial basis function network is used to approximate unknown nonlinear functions, and minimum learning parameters are introduced to lessen the computational complexity. A sufficient effort has been made to verify the stability of the closed-loop system based on the Lyapunov stability theory. Finally, simulation results display the effectiveness of the proposed scheme.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.20-27
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• 1987

The hierarchical approach method is proposed to sperate each different time scale sub-systems from linear time invariant multi-parameter singular perturbation systems. By means of this proposal, the original multi-parameter singular perturbation systems is completely separated into independent subsystems with each different time scale. It is also investigated that the controllability of the system is invariant. And this paper applies singular perturbation methods to the minimum control effort problem for linear time invariant systems with constrained controls. Also near-optimum control theory, which is based on dividing the total time interval with the time scales respectively, is proposed. As a result, the time scale separation method is show to be particularly useful in a near optimum design which can be otained through a decentralized control structure.

• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.23-29
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• 1997

In the control of crane system, the traversing time of the trolley must be reduced as much as possible and the swing must be stopped at the end point. To design the minimum time control system, Pontryagim maximum principle is applied. In order to implement the control algorithm, the dynamic equation is linearlized at an equilibrium point, so that the linear time invariant state equation can be obtained. The overall performance of the closed loop system is evaluated by means of computer simulations and practical experiments in a broad range of working conditions. The effectiveness is proved through the experimental results for the anti-sway control of the load and the position control of trolly. It is expected that the proposed system will make an important contribution to the industrial fields.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.101-107
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• 2000

A design of the global optimal sliding mode control is presented to control the second order uncertain time varying system with torque limit. With specified ranges of parametric uncertainties and torque limit, the minimum arrival time to reference inputs can be calculated. The proposed control scheme is applied to the motor system carrying loads. The merit of the proposed control scheme is that the arriving time at the reference input, which is the revolution angle, and the maximum allowable acceleration are expressed in a closed form solution. The superior performance of the proposed control scheme is validated by the computer simulation and experiments comparing with other sliding mode controllers.

• 전기의세계
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• v.20 no.2
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• pp.19-26
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• 1971

To proteting hunting of synchronus motor a new one which has two field windings is designed. One is main field winding excited constantly and the other is control field winding excited only during the load of motor changes. The oscillation of the motor is controlled by increasing or decreasing the control field excitation. To determine the optimal field excitation the Pontryagin's minimum principle is applied. Also this paper gives the optimal trajectories of the motor and it's transition time. This motor has some of better properties than the old motor with damper winding. These phroperties are (1) there is no hunting (2) the transient stability is improved (3) transition time is very short.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.371-374
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• 1990

This paper presents the speed control of dc motor based on deadbeat response. The deadbeat response is that the output reaches the final value in the minimum possible settling time and stays there. This results demonstrate that the output reaches final value in one sampling time for the unsaturated region, and in one sampling time after getting free from the saturation state for the saturated region.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1059-1066
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• 2011

This paper makes a close inquiry into ill-conditioning that may be occurred in wireless localization of the sensor nodes based on network signals in the wireless sensor network and provides the clue for solving the problem. In order to estimate the location of a node based on the range information calculated using the signal propagation time, LS (Least Squares) method is usually used. The LS method estimates the solution that makes the squared estimation error minimal. When a nonlinear function is used for the wireless localization, ILS (Iterative Least Squares) method is used. The ILS method process the LS method iteratively after linearizing the nonlinear function at the initial nominal point. This method, however, has a problem that the final solution may converge into a LM (Local Minimum) instead of a GM (Global Minimum) according to the deployment of the fixed nodes and the initial nominal point. The conditions that cause the problem are explained and an adaptive method is presented to solve it, in this paper. It can be expected that the stable location solution can be provided in implementation of the wireless localization methods based on the results of this paper.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.91-98
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• 2011

In this paper, a multi-channel speech enhancement method using the linearly constrained minimum variance (LCMV) algorithm and a variable learning rate control is proposed. To control the learning rate for adaptive filters of the LCMV algorithm, the direction of arrival (DOA) is measured for each short-time input signal and the likelihood function of the target speech presence is estimated to control the filter learning rate. Using the likelihood measure, the learning rate is increased during the pure noise interval and decreased during the target speech interval. To optimize the parameter of the mapping function between the likelihood value and the corresponding learning rate, an exhaustive search is performed using the Bark's scale distortion (BSD) as the performance index. Experimental results show that the proposed algorithm outperforms the conventional LCMV with fixed learning rate in the BSD by around 1.5 dB.