• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.621-624
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• 2002

The purpose of this paper is a study on getting proper gain set of PID controller which satisfies multi-performance specifications of the control system. The multi-objective optimization method is introduced to evaluate specifications, and the genetic algorithm is used as an optimal problem solver. To enhance the performance of genetic algorithm itself, adaptive technique is included. According to the proposed method in this paper, finding suitable gain set can be more easily accomplishable than manual gain seeking and tuning.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.7
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• pp.1003-1011
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• 2009

This study aims at precise control of oil outlet temperature in the oil cooler system of machine tools for enhancement of working speed and processing accuracy. PID control logic is adopted to obtain desired oil outlet temperature of the oil cooler system with hot-gas bypass method. We showed that the gains of PID controller could be easily determined by using gain tuning methods to get the gain of PID controller without any mathematical model. We also investigated various gain tuning methods to design the gains of PID and compared each control performance for selecting the optimal tuning method on the hot gas bypass method through experiments. Moreover, we confirmed excellent control performance with proposed PI controller gain even though disturbances were abruptly added to the experimental system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.698-706
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• 2016

In order to move mobile robots to desired locations in a minimum time, optimal control problems have to be solved; however, their analytic solutions are almost impossible to obtain due to robot nonlinear equations. This paper presents a method to get optimal control gains of mobile robots using genetic algorithms. Since the optimal control gains of mobile robots depend on the initial conditions, the initial condition range is discretized to form some grid points, and genetic algorithms are applied to provide the optimal control gains for the corresponding grid points. The optimal control gains for general initial conditions may be obtained by use of neural networks. So the optimal control gains and the corresponding grid points are used to train neural networks. The trained neural networks can supply pseudo-optimal control gains. Finally simulation studies have been conducted to verify the effectiveness of the method presented in this paper.

• 전기의세계
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• v.28 no.2
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• pp.55-60
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• 1979

In this paper, a new method of the optimal control of the regulator and tracking control problem concerning the dimension of the velocity is derived and applied for the second order plant. The output position, output velocity and the control effort are plottcd with time applying analog computer simulation. And it is compared with the output of the ordinary optimal control law in case the reference input is given by velocity function, and studied about the gain of this method.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.589-596
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• 2001

In this paper, a new design methodology for the optimal control of nonlinear systems described by the TS(Takagi-Sugeno) fuzzy model is proposed. First, a new theorem concerning the optimal stabilizing control of a general nonlinear dynamic system is proposed. Next, based on the proposed theorem and the inverse optimal approach, an optimal controller synthesis procedure for a TS fuzzy system is given, Also, it is shown that the optimal controller can be found by solving a linear matrix inequality problem. Finally, the proposed method is applied to the attitude control of a rigid spacecraft to demonstrate its validity.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3127-3135
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• 1994

An approach to the simultaneous optimal design of structure and control system for large free-free flexible beam is presented. The flexible beam is modeled by the finite element method. And the reduced model of small degree of freedom is constructed by use of modal analysis. The tapered beam is considered so that the number of design variables is not dependent on the increasing number of finite elements. The width of several points of tapered beam and control gain are taken as design variables. The shape of beam and control gain are optimized simultaneously for the minimum weight of total structure including control system subject to the constraints of the magnitude of displacement of beam. It is shown that the simultaneous optimal design of structure and control systems is indeed useful.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.221-229
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• 2022

Sliding mode control (SMC) is a robust control method to control a robot arm with nonlinear properties. A high switching gain of SMC causes chattering problems, although the SMC allows the adequate control performance by giving high switching gain, without the exact robot model containing nonlinear and uncertainty terms. In order to solve this problem, SMC with sliding perturbation observer (SMCSPO) has been researched, where the method can reduce the chattering by compensating the perturbation, which is estimated by the observer, and then choosing a lower switching control gain of SMC. However, optimal gain tuning is necessary to get a better tracking performance and reducing a chattering. This paper proposes a method that the Q-learning automatically tunes the control gains of SMCSPO with an iterative operation. In this tuning method, the rewards of reinforcement learning (RL) are set minus tracking errors of states, and the action of RL is a change of control gain to maximize rewards whenever the iteration number of movements increases. The simple motion test for a 7-DOF robot arm was simulated in MATLAB program to prove this RL tuning algorithm. The simulation showed that this method can automatically tune the control gains for SMCSPO.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.759-764
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• 1987

The design and application of optimal control technique to the rotary shearing system is mentioned in this paper. To maximize the accuracy in both shearing length and blade speed at shearing, time-varying gain patterns for closed loop control are designed on the basis of fixed terminal time constrained optimal regulator. The performance accuracy in real application has greatly improved than the conventional way of shearing control.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.25-35
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• 1999

This paper presents a control gain tuning scheme for multi-axis PID control systems by Taguchi method. As an experimental set-up, a parallel mechanism machine tool has been selected. This machine has eight servodrives and each servodrive has four control gains, respectively. Therefore, total 32 control gains have to be tuned. Through a series of design of experiments, an optimal and robust set of PID control gains is tuned. The index of the sum of position error and velocity error is reduced to 61.4% after the experimental gain tuning regardless of the feedrate variation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1185-1191
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• 2008

This paper presents an approach to define an optimal piezoactuator length to actively control structural vibration. The optimal ratio of the piezoactuator length against the beam length when a pair of piezoceramic actuator and accelerometer is used to suppress unwanted vibration with direct velocity feedback(DVFB) control strategy is not clearly defined so far. It is well known that DVFB control can be very useful when a pair of sensor and actuator is collocated on structures with a high gain and excellent stability. It is considered that three different collocated Pairs of piezoelectric actuators (20, 50 and 100 mm long) and accelerometers installed on three identical clamped-clamped beams($30{\times}20{\times}1mm$). The response of each sensor-actuator pair requires strictly positive real(SPR) property to apply a high feedback gain. However the length of the piezoactuator affects the SPR property of the sensor-actuator response. Intensive simulation and experiment show the effect of the actuator length variation is strongly related with the frequency range of the SPR property. Thus an optimal length ratio was suggested to obtain relevant performance with a good stability under the DVFB strategy.