• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.227-230
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• 1996

The paper highlights the need for cautious least squares estimation when dealing with industrial applications of bilinear self-tuning control and indicates in qualitative terms the benefits of the approach over linear self-tuning control schemes. The cautious least squares algorithm is described and the use of cautious self-tuning in the context of both commissioning and implementation discussed.

• 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 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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• 2004.08a
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• pp.272-276
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• 2004

The conventional PID (Proportional-Integral-Derivative) control technique is widely used for the process control in many industries since it is simple in structure and provides the good response. Nowadays, this control technique has been developed on the Programmable Logic Controller (PLC) to use for the process control loop. However, using this technique is difficult when tuning the PID parameters ($K_p$, $T_i$ and $T_d$) to achieve the best response. Moreover, trial-and-error procedure along with the operator experiences are required to obtain the best results when tuning the PID controller parameters. This paper proposes the self-tuning PID controller based on PLC for the process control in the industries. The proposed self-tuning PID controller uses the PLC-based PID structures to control the process production. The proposed PID tuning utilizes the PLC to synthesize and analyze controller parameter as well as to tune for appropriate parameters using Dahlin method and extrapolation. Experimental results using a self-tuning PID controller to control temperature of the oven show that the controller developed is capable of controlling the process very effectively and provides a good response.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.160-168
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• 1997

A $H_{\infty}$self-tuning control scheme for the tip position of a flexible link robot handling unknown loads is presented here. The scheme essentially comprises a recursive least-squares identification algorithm and $H_{\infty}$self-tunning controller. The $H_{\infty}$control low is designed to be robust to uncertain parameters and the self-tunning action provides adaption to unknown parameters. Through numerical study, the performance comparison of the $H_{\infty}$self-tuning controller with a constant gain $H_{\infty}$controller as well as a LQG self-tuning controller clearly shows its superior ability in handling load changes in quiescent states.nt states.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.150-155
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using digital signal processors for robot manipulators. TMS3200C50 is used in implementing real-time adaptive control algorithms provide advanced performance for robot manipulator. In this paper an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm and controller parameters are detemined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.756-762
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• 2006

Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.388-398
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• 1998

In constructing fuzzy control systems. there are many parameters such as rule base. membership functions. inference m method. defuzzification. and I/O scaling factors. To control the system in properly using fuzzy logic. we have to consider t the correlation with those parameters. This paper deals with self-tuning of fuzzy control systems. The fuzzy controller h has parameters that are input and output scaling factors to effect control output. And we propose the looklongleftarrowup table b based self-tuning fuzy controller. We propose the PMTM(Plus-Minus Tuning Method) for self tuning method, self-tuning the initial look-up table to the appropriate table by adding and subtracting the values.