• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.76-85
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• 1998

In this paper, a fuzzy tuning method of a control gain in the discrete-time repetitive controller is proposed for precise tracking control of a system whose reference signal is repetitive. The control gain is modified by fuzzy rules which use the magnitude and the variation ofthe maximum output error in the previous repetitive period. The proposed method is applied to a direct drive 2-axis SCARA-type robot and, it is illustratedby computer simulations and real-time experimentation that better performance can be obtained that the fixed gain-based repetitive controller.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.60-65
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• 2000

We propose a new method to deal with the optimal gain self-tuning of the PID controller which is used to industrial process control in various fields. First of all, in this method, first order delay system which was modeled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nickels method. Finally, we can find the parameters of Pm controller so as to maximize the fuzzy inferencl function which includes the maximum overshoot, damping ratio, rising time and settling time. The proposed method also shows good adaptability for variations in characteristics and dead time of the system.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.333-336
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• 2002

In many cases, fuzzy modeling has a defect that the design procedure cannot be theoretically justified. To overcome this difficulty, we suggest a new design method for fuzzy model by combining genetic algorithm(GA) and mush set theory. GA, which has the advantages is optimization, and rule base. However, it is some what time consuming, so are introduce rough set theory to the rule reduction procedure. As a result, the decrease of learning time and the considerable rate of rule reduction is achieved without loss of useful information. The preposed algorithm is composed of three stages; First stage is quasi-optimization of fuzzy model using GA(coarse tuning). Next the obtained rule base is reduced by rough set concept(rule reduction). Finally we perform re-optimization of the membership functions by GA(fine tuning). To check the effectiveness of the suggested algorithm, examples for time series prediction are examined.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.58-66
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• 2001

GPC has been reported as a useful self-tuning control algorithm for systems with unknown time-delay and parameters. GPC is easy to understand and implement, and thus has won popularity among many practicing engineers. Despite its success, GPC does not guarantee is nominal stability. So, in this paper, GPC is rederived in frequency domain instead of in the time domain to guarantee its nominal stability. Derivation of GPC in frequency domain involves spectral factorization and Diophantine equation. Frequency domain GPC control law is stable because the zeros of characteristic polynomial are strictly Schur. Recursive least square algorithm is used to identify unknown parameters. To see the effectiveness of the proposed controller, the controller is simulated for a numerical problem that changes in dead-time, in order and in parameters.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.195-195
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• 1999

This paper is Proposed a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nickels method. So we can find the parameters of PID controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of PID controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of PID controller is found by Neural-Network Program.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.21-28
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• 2007

Using multi-resolution, the mutiresolution proportional-integral-derivative(MRPID) controller functions as a filter to eliminate noise and disturbance which are included in error signals. If the sampling frequency is high, the response time will be delayed because of the remaining high frequency component although the overshoot is removed. However, if the sampling frequency is low, the response time will be enhanced by getting rid of signal components while the overshoot is increased. In this paper, the sampling frequency tuning method is used the response of the proportional integral derivative(PID) controller and the MRPID controller, and the parameter tuning method is considered the characteristic of the MRPID controller. The proposal method is verified by computer simulations.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.249-251
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• 2006

In this study, a systematic and effective tuning method of the actuator control parameters of the control loading system for aircraft based on control theory is presented. Firstly, to raise the time response of the system, the proportional gain and the integral gain of the velocity control loop is maximized within the range where vibration and noise does not occur. And then the position control loop is composed by getting the transfer function of the control loading system including the velocity control loop. With the root locus of the composed position control loop, the proportional gain of the position control loop that keeps stable transient state and leads good time response of the system is predicted, and the simulations are performed by using the predicted gain. Lastly, the actuator control parameters of actual control loading system are set to the previously obtained gain values. And the experiments to actuate the control loading system are executed. It shows that the tuning method of the actuator control parameter proposed in this study is applied to actual control loading system very well by comparing the results of the experiments with those of the simulations.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.3
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• pp.64-70
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• 1994

We propose a new method to deal with optimal auto-tuning of the PID controller which is used to process control in various fields. First of all, in this method, 1st order system which was modeled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. Finally, we can find the parameters of PID controller so as to maximize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. The Proposed method also shows good adaptability for variations in characteristics and dead m e of the system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.211-214
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• 1997

This paper applies fuzzy self-tuning PID controller in DS/CDMA cellular system. Power control is essential in DS/CDMA to compensate for the differing received powers due to both the slowly varying long-term and fast varying short-term fading processes and co-channel interference. The controller proposed is adaptable for the variations of the system dynamics and especially for the variable time delay which exists in mobile radio systems. Accordingly the results is the smaller power control error, that is, the smaller average transmitting power of mobile compared with the conventional control schemes. Because interferences to the other mobiles are reduced, the capacity of CDMA can be increased.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.345-348
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• 1991

This paper describes a new auto tuning method for the intelligent PID control system. This new method is hosed on the settling time of the process and has been introduced into auto-tuning PID controller using fuzzy logic. The performance of the controller is measured by computer simulation. Simulation shows good results that controller searches well the optimal values of PID parameters in any conditions and the response characteristic of the control system is improved.