• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.351-354
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• 2001

In this paper, we present self-tuning control of switched reluctance motor for maximum torque with phase current and shaft position sensor. Determination method of turn-on/off angle is realized by using self-tuning control method. During the sampling time, micro-controller checks the number of pulse from encoder and compare with the number of pre-checked pulse. After micro-controller calculates between two data, it moves forward or backward turn-off angle. When the turn-off angle is fixed optimal turn-off angle, the turn-on angle automatically moves forward or backward by a step using self-tuning control method. And then, optimal turn-off angle is searched once again. As such a repeating process, turn-on/off angle is moved automatically to obtain the maximum torque. The experimental results are presented to validate the self-tuning algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1560-1564
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• 2008

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-Self Tuning control method for motor control system as a compensation method solving this problem is presented. If the PID control system is stable in the sense that the error is inside the constraint set, the supervisory control is idle. If the error hits the boundary of the constraint, the supervisory controller begins operation to force the error back to the constraint set. We prove that the PID-Self Tuning control system is globally stable in the sense that the error is guaranteed to be within the tolerance limits specified by the system designer.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.194-199
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• 1989

In this paper, using the direct drive arm for plant, the controller is developed to track the desired trajectory in high speed and precision. For the purpose of this, through extending self-tuning pole-placement algorithm, we developed self-tuning pole-shift algorithm which is fast in response and good tracking for the reference tracking change. Developed controller is applied a three-link direct drive arm with the varing payload to track the desired tracking. And, through the computer simulation, the performance of developed controller is compared with the performance of the computed torque method and the self-tuning pole placement algorith.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.704-707
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• 1997

In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.188-193
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• 1992

The PID controllers which is widely used in the process industry are poorly damped when the dynamic process contains significant dead time or when there are random disturbances acting on the plant. GPC is known to be more superior than conventional self-tuning algorithm in overcoming above problem and prior choice of model order. In this paper, we propose the method which determine the parameter of PID controller from minimization of GPC criterion. The controller has emplicit scheme which is comprised of parameter estimation and PID control design. Simulation results show the performance of the proposed self-tuning PID controller.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.379-387
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• 2004

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.199-207
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• 2002

In this paper, a self-tuning gain-scheduled skyhook control for semi-active suspension systems is investigated. The dynamic characteristics of a continuously variable damper including electro-hydraulic pressure control valves is analyzed. A 2-d.o.f. time-varying quarter-car model that permits variations in sprung mass and suspension spring coefficient is considered. The self-tuning skyhook control algorithm proposed in this paper requires only the measurement of body acceleration. The absolute velocity of the sprung mass and the relative velocity of the suspension deflection are estimated by using integral filters. The skyhook gains are gain-scheduled in such a way that the body acceleration and the dynamic tire force are optimized. An ECU prototype is discussed. Experimental results using a 1/4-ear simulator are discussed. Also, a suspension ECU prototype targeting real implementation is provided.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.914-922
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• 1999

A study on the improvement of tracking performance of a 3 DOF planar parallel manipulator is performed. A class of adaptive tracking control sheme is designed using self tuning adaptive fuzzy logic control theory. This control sheme is composed of three classical PD controller and a multi learning type self tuning adaptive fuzzy logic controller set. PD controller is tuned roughly by manual setting a priori and fuzzy logic controller is tuned precisely by the gradient descent method for a global solution during run-time, so the proposed control scheme is tuned more rapidly and precisely than the single learning type self tuning adaptive fuzzy logic control sheme for a local solution. The control performance of the proposed algorithm is verified through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.48.5-48
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• 2002

$\textbullet$ Contents 1 Introduction $\textbullet$ Contents 2 Crane Description $\textbullet$ Contents 3 Self-tuning Controller Design $\textbullet$ Contents 4 Result of Experiments $\textbullet$ Contents 5 Conclusions $\textbullet$ Contents 6 References

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.66-77
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• 1997

This paper presents an automatic tuning method for parameters of a multivaiable self-tuning velocity-type PID controller which adapts to changes in the system parameters with time delays and noises. The velocity-type PID control structure is determined in the process of minimizing the variance of the auxiliarly output, and 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 optiminzing the design parameters of the controller. The proposed PID type multivariable self-tuning method is simple andeffective compared with other esisting multivariable self-tuning methods. Computer simulation has shown that the proposed algorithm is beter than the trial-and-error method in the tracking performance.