• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.04a
• /
• pp.359-362
• /
• 1996

Our unicycle robot has simple mechanical structure. But unicycle's dynamical system is a very sensitive unstable system. Equation of motion of this simple unicycle robot was derived using Lagrange's method. In this paper a human inference control mechanism was established throughout an inquiry into hyman riding a unicycle, and we developed a hybrid controller to control our unicycle robot. Our controller is consisted with the PD and fuzzy controller containing fuzzy gain scheduling technique. Computer simulation shows good results.

• Journal of Industrial Technology
• /
• v.20 no.B
• /
• pp.155-162
• /
• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance, FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and to increase efficiency. a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy PI and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and the resultant rule base is Macvicar-Whelan type. And the membership function is a Gaussian function. The frequency response information is used in tuning of the membership functions. Also a tuning strategy for the scaling factors is proposed based on the relationship between PID gain and the scaling factors. Simulation results show better performance and the effectiveness of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.2
• /
• pp.342-348
• /
• 2009

This paper introduces a novel denoising algorithm for the partial-discharge(PD) signals from power apparatuses. The developed algorithm includes three kinds of specific denoising sub-algorithms. The first sub-algorithm uses the fuzzy logic which classifies the noise types in the magnitude versus phase PD pattern. This sub-algorithm is especially effective in the rejection of the noise with high and constant magnitude. The second one is the method simply removing the pulses in the phase sections below the threshold count in the count versus phase pattern. This method is effective in removing the occasional high level noise pulses. The last denoising sub-algorithm uses the grouping characteristics of PD pulses in the 3D plot of the magnitude versus phase versus cycle. This special technique can remove the periodical noise pulses with varying magnitudes, which are very difficult to be removed by other denoising methods. Each of the sub-algorithm has different characteristic and shows different quality of the noise rejection. On that account, a parameter which numerically expresses the noise possessing degree of signal, is defined and evaluated. Using the parameter and above three sub-algorithms, an adaptive complex noise rejection algorithm for the on-line PD diagnosis system is developed. Proposed algorithm shows good performances in the various real PD signals measured from the power apparatuses in the Korean plants.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1628-1631
• /
• 2005

Ship Autopilots are usually designed based on the PD and Pill controllers because of simplicity, reliability and easy to construct. However their performance in various environmental conditions is not as good as desired. This disadvantage can be overcome by adjusting works or constructing adaptive controllers. But those methods are complex and not easy to do. This paper presents a new method for constructing a Ship Autopilot based on the combination of Fuzzy Logic Control (FLC) and Linear Control Theory (Pill control). The new Ship Autopilot has the advantages of both the Pill and FLC control methodologies: easy to construct, and optimal control laws can be established based on ship masters' knowledge. Therefore, the new ship autopilot can be well adapted with parameter variations and strong environment effects. Simulation using MATLAB software for a ship with real parameters shows high effectiveness of the Fuzzy Pill autopilot in course keeping and course changing manoeuvres in comparison with the ordinary Pill ship autopilots.

• Journal of Advanced Marine Engineering and Technology
• /
• v.30 no.6
• /
• pp.760-769
• /
• 2006

This paper proposes an autopilot system using a fuzzy PID controller to satisfy performances required for the automatic navigation of ships under various marine circumstances. The existing autopilot system using a PD type controller has difficulties in eliminating a steady-state error and compensating nonlinear characteristics of ships. The autopilot system using the proposed fuzzy PID controller has a self-tuning ability, an ability to compensate nonlinear characteristics, and an ability to turn at constant angular velocity. Therefore. it can naturally make a steady-state error zero, compensate nonlinear dynamic effect of ships, have an adaptability to parameter variation owing to shallow water effect, and have an ability to turn ship's course rapidly without overshoot through procedures of acceleration, constant, and deceleration of angular velocity for large course-changing.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1995.10b
• /
• pp.59-70
• /
• 1995

Output performance improvement using fuzzy logic to the conventional control scheme for a magnetic levitation system is presented in this paper, Adverse characteristics of nonlinearity, unstability, system parameter variation, etc, in the levitation system are partially overcome by the general fuzzy control action. Using a PD type compensator, a coarse framework of output performance is provided to the levitation system. Then a fine regulation to the output performance requirement is obtained by the natural description of the control action in the form of fuzzy logic controller. This control action soothes the adverse characteristics of the levitation system. In this way a better output performance can be obtained in a real time experiment.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.485-488
• /
• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of ruler from human operators. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.308-309
• /
• 2007

본 논문에서는 계층적 공정 경쟁 기반 병렬 유전자 알고리즘 (Hierarchical Fair Competition Genetic Algorithm: HFCGA)을 이용하여 Ball & Beam 시스템에 최적의 Fuzzy Cascade 제어기를 설계하고자 한다. Ball & Beam 시스템은 비선형적이며 Beam의 마찰계수와 Ball의 중력 가속도를 고려하여 Ball의 위치를 조정하는 시스템이다. 이러한 Ball & Beam 시스템에 대해 Fuzzy Cascade 제어기를 설계하고, 조기 수렴에 문제가 있는 기존의 유전자 알고리즘을 개선한 HFCGA를 이용하여 제어기의 파라미터를 최적화 한다. 마지막으로 실제 플랜트에 적용하여 설계된 제어기의 성능을 평가하고, PD Cascade 제어기와 Fuzzy Cascade 제어기의 성능을 비교한다.

• Journal of the Korean Institute of Navigation
• /
• v.5 no.2
• /
• pp.59-88
• /
• 1981

Many studies have been done in the field of fuzzy logic theory, but it's application is not so much, and particularly, there isn't any application to the ship's steering system, until now. This paper is to survey the effect of application of fuzzy logic control to the ship's steering system. The controller is made up of a set of Linguistic Control Rules which are conditional linguistic statements connecting the inputs and the output, and take the inputs derived from the errors, that is, deviation angle and it's angular velocity. These two variables together give information about the state of the steering system, and the Linguistic Control Rules are implemented on the digital computer. The characteristics of this system were investigated through the computer simulation and satisfactory results compared with that of the conventional PD controller were obtained.

• Proceedings of the KIEE Conference
• /
• 2000.11d
• /
• pp.650-652
• /
• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.