• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.6-77
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• 2001

R/C helicopter has been used to several fields of military affairs, investigation, searching and toys because it has small size, hovering and vertical take-off characteristics etc. Therefore it needs more realizable control method. The paper introduces simulation and experimental results for control of a helicopter training simulator by self tuning control method. It is assumed that the helicopter is operated at the state of hovering motion and the model is induced. The self tuning control method incorporates the concepts of the well known internal model principle and annihilator polynomial for reference input and disturbance. The controller design is separated into two cases that the plant parameters are known or not. To realize ...

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.168-175
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• 1995

A robust speed control algorithm under disturbances and reference change is developed using the self tuning control method in order to control induction motors. The method incorporates the concepts of the well known internal model principle and the annihilator polynomial. The effectiveness of the method is evaluated through the speed control experimental results of an induction motor for refernce change and arbitrary distrbance.

• Journal of Aerospace System Engineering
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• v.11 no.5
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• pp.28-35
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• 2017

Magnetic Suspension and Balance System (MSBS) demonstrates the capacity to levitate an experimental model absent any mechanical contact using magnetic forces and moments. It allows precise control of position and attitude of the model, and measures external forces and moments acting on the model. For the purpose of acquisition of reliable experimental results under stable and safe conditions, the performance and robustness of the position and attitude control system of MSBS needs to be improved. To this end, Iterative Feedback Tuning (IFT) and L1 adaptive output feedback algorithm were employed to automatically increase command following performance and to ensure robust operation of MSBS with failure of electric power supply. The applicability was validated using computational simulation.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.288-291
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• 1999

The PID (Proportional-Integral-Derivative) controller is widely used in the industries for more than fifty years with the well known Ziegler-Nichols tuning method and others varieties. However, most of the PID controller being used in the real practice still require trial and error adjustment for each process after the tuning method is done, which is consuming of time and needs the operator experiences to obtain the best results for the controller parameter. In order to reduce the inconvenience in the controller tuning, this paper presents a design of an automatic PID controller parameter analyzer being used as a support instrument in the industrial process control. This analyzer is designed based on the tuning formula of Dahlin to synthesize the PID controller parameter. Using this analyzer, the time to be spent in the trial and error procedures and its complexity can be neglected. Experimental results using PID controller parameter synthesized from this analyzer to the liquid level control plant model and the fluid flow control plant model show that the responses of the controlled systems can be efficiently controlled without any difficulty in mathemathical computation.

• 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.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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• pp.678-684
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• 2015

Near-threshold computing (NTC) is now regarded as a promising candidate for innovative power reduction, which cannot be achieved with conventional super-threshold computing (STC). However, performance degradation and vulnerability to process variation in the NTC regime are the primary concerns. In this paper, we propose a voltage- and frequency-tuning methodology for mitigating the process-variation-induced problems in NTC-based manycore architectures. To implement the proposed methodology, we build up multiple-voltage multiple-frequency (MVMF) islands and apply a voltage-frequency tuning algorithm based on the critical-path monitoring technique to reduce the effects of process variation and maximize energy efficiency in the post-silicon stage. Experimental results show that the proposed methodology reduces overall power consumption by 8.2-20.0%, compared to existing methods in variation-sensitive NTC environments.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.677-680
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• 2003

The control of the SRM(Switched Reluctance Motor) is usually based on the non-linear inductance profiles with positions. So determination of optimal switching angle is very different. we present self-tuning control of SRM for maximum torque and efficiency with phase current and shaft position sensor During the sample time, micro-controller checks the number of pre-checked pulse. After micro-controller calculates between two data, it move forward or backward turn-off angle. When the turn-off angle is fixed optimal turn-off angle, turn-on angle 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 moves automatically to obtain the maximum torque and efficiency. The experimental results are presented to validate the self-tuning algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5A
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• pp.513-518
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• 2010

Improvement of phase noise characteristics in a different approach of HEMT VCO (Voltage Controlled Oscillator) with coupled microstrip lines to tune the oscillating frequency is investigated. Two HEMT VCOs of 9.8GHz are manufactured in the same configuration except for the frequency tuning circuit in order to empirically demonstrate the phase noise reduction. Experimental result shows that phase noise reduction can be enhanced 8dBc/Hz at 100KHz offset frequency from carrier by frequency tuning circuit with coupled microstrip lines over the conventional VCO.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.541-543
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• 1998

Generally, PI control is simple and easy to implement and gains of PI control are determined by specifying a dynamics of the servo driver system. However, the gain-tuning is so difficult that it is relied on an expert's effort. This paper presents a gain auto-tuning method for PI controllers based on a fuzzy inference mechanism. First, the proposed fuzzy inference system identifies a system moment of inertia and adjusts control gains by using the difference in speed responses between a real plant and a reference model. Second, this paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper PI gains with respect to the load inertia variation. To prove the validity of the proposed gain tuning algorithm and the feasibility of the servo drive, a high performance servo drive will be implemented by DSP(TMS320C31) and intelligent power module (IPM). The proposed controller is applied to the speed control of the 300W AC servo motor. Some simulations and experimental results show that the proposed fuzzy PI controller is more robust than the conventional PI controller against the load inertia variation.