• Journal of Power System Engineering
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• v.3 no.4
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• pp.69-78
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• 1999

In the single-input and single-output system, the parameter of plant is scalar polynomial, but in the multiple input and multiple output, it accompanies, being matrix polynomial, the consideration of observable controlability index or problems non-commutation in matrix polynomial as well as degree, and it is more complex to deal with. Therefore, it is thought that a full research on the single-input and single-output system is not sufficient. This paper proposes that problems of minimum variance self-tuning regulator by using numerical calculation example of multivariable system and pole assignment self-tuning regulator.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.226-231
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• 2016

Researching and developing mobile robot are quite important. Autonomous driving of mobile robot is important in various working environment. For its autonomous driving, mobile robot detects obstacles and avoids them. Purpose of this thesis is to analyze kinematics model of the mobile robot and show the efficiency of type-2 fuzzy self-tuning PID controller used for controling steering angle. Type-2 fuzzy is more flexible in verbal expression than type-1 fuzzy because it has multiple values unlike previous one. To compare these two controllers, this paper conduct a simulation by using MATLAB Simulink. The result shows the capability of type-2 fuzzy self-tuning PID is effective.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.139-147
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• 1996

PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.68-75
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• 1998

The Intelligent Cruise Control system, ICC, is a driver assisting system for controlling relative speed and distance between two vehicles in the same lane. The ICC may be considered as an extension of a traditional cruise control, not only keeping a fixed speed of the vehicle, but correcting the speed also to that of a slower one ahead. This paper presents a real-time self-tuning fuzzy control algorithm to develop ICC. The self-tuning fuzzy control law is adopted to reduce the effects of nonlinearities of the vehicle and various road environments. In the self-tuning algorithm an interior penalty method is applied to preserve the inherent order of membership functions and is modified as an on-line algorithm for real time application. Via simulations, the performance of the suggested control algorithm is compared with a PID and a fuzzy control without self-tuning. The suggested control algorithm is implemented on PRV III and the results of the test driving on a local road are given.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.25-28
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• 1995

A Practical application of self-tuning fuzzy controller to a multi-input multi-output complex system of a vehicle engine is investigated. The ovjective is to design a controller to improve the transient performance in torque and RPM mode changes. For the performance improvement in the multivariable comples system, the self-tuning function of internal parameters is essential and practical. The measured output variables using different control schemes are compared the advanteges of the self-tuning fuzzy logic controller are better output performances and the effectiveness in the controller design using many parameters.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.40-46
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• 1999

A self-tuning FPID(Fuzzy Proportional Intergral Derivative) controller fo load frequency control of 2-area power systemis proposed in this paper. The paramters of the proposed self-tuning FPID controller are self-tuned by the proposed fuzzy inference technique. Therefore in this paper the fuzzy inference technique of PID gains using PSGM(Product Sum Gravity Method) is presented and is applied to the load frequency control of 2-area power system. The computer simulation results show that the proposed controller give better more control characteristics than convention-al PID, FLC under load changes.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.11
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• pp.69-75
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• 2009

In this paper, a self-tuning regulator for a speed control of a permanent magnet type stepping motor is proposed. The self-tuning theory provides a nonlinear modeling of a stepping motor drive system and can provide the controller with information regarding the reference variation and parameter variation of the stepping motor through the on-line estimation. The proposed self-tuning regulator organize the positive feedback loop and IP(Integral-Proportional) type. Therefore, the proposed self-tuning regulator has a robust control capabilities during dynamic operation. The availability of the proposed controller is verified through experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.78-82
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• 1986

In the process control applications of self tuning control, a major concern of the control problem is to handle an offset caused by load disturbances and random steps occuring at random instance of time. Conventionally an integrator is incorperated in the forward path of the controller to eliminate such an offset. But this approach causes a difficulty if the adaptive part of the resultant controller is to be evaluated. In this paper a method of analyzing the adaptive system and improving the offset effect is suggested for a class of referance model method in the self tuning adaptive control system.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.214-217
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• 1987

In this paper self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in multiple ARMA process. This process is simplified as independent SISO ARMA process having offset terms. This offset was considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the parameter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results considers well with the analysis in case of linear interconnection.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.87-95
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• 1998

This paper presents the method for the automatic tuning of a design weighting polynomial parameter of a generalized minimum-variance stochastic self tuning controller which adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design weighting polynomial parameters. The proposed self tuning method is simple and effective compared with other existing self tuning methods. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.