• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
• /
• pp.199-202
• /
• 2002

This parer concerns a design methodology of the observer-based output-feedback digital controller for Takagj-Sugeno (TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.

• Journal of applied mathematics & informatics
• /
• 제38권1_2호
• /
• pp.13-36
• /
• 2020

In this paper, we have presented a multispecies prey-predator harvesting system based on Lotka-Voltera model with two competing species which are affected not only by harvesting but also by the presence of a predator, the third species. We also assume that the two competing fish species releases a toxic substance to each other. We derive the condition for global stability of the system using a suitable Lyapunov function. The possibility of existence of bionomic equilibrium is considered. The optimal harvest policy is studied and the solution is derived under imprecise inflation in fuzzy environment using Pontryagin's maximal principle. Finally some numerical examples are discussed to illustrate the model.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
• /
• pp.141-144
• /
• 2001

This paper proposes a decentralized control technique for 2-dimensional experimental helicopter systems. The decentralized control technique is especially suitable in large-scale control systems. We derive the stabilization condition for the interconnected Takagi-Sugeno (75) fuzzy system using the rigorous tool - Lyapunov stability criterion and formulate the controller design condition in terms of linear matrix inequality (LMI). To demonstrate the feasibility of the proposed method, we include the experiment result as well as a computer simulation one, which strongly convinces us the applicability to the industry.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
• /
• pp.187-190
• /
• 2003

In this paper, we address the robust adaptive backstepping controller using fuzzy neural network (FHIN) for a class of uncertain output feedback nonlinear systems with disturbance. A new algorithm is proposed for estimation of unknown bounds and adaptive control of the uncertain nonlinear systems. The state estimation is solved using K-fillers. All unknown nonlinear functions are approximated by FNN. The FNN weight adaptation rule is derived from Lyapunov stability analysis and guarantees that the adapted weight error and tracking error are bounded. The compensated controller is designed to compensate the FNN approximation error and external disturbance. Finally, simulation results show that the proposed controller can achieve favorable tracking performance and robustness with regard to unknown function and external disturbance.

• 대한산업공학회지
• /
• 제24권2호
• /
• pp.223-240
• /
• 1998

The purpose of this paper is to develop the pattern recognition system with a 'Robust' concept to be applicable to flexible manufacture automation in practice. The 'Robust' concept has four meanings as follows. First, pattern recognition is performed invariantly in case the object to be recognized is translated, scaled, and rotated. Second, it must have strong resistance against noise. Third, the completely learned system is adjusted flexibly regardless of new objects being added. Finally, it has to recognize objects fast. To develop the proposed system, contouring, spectral analysis and Fuzzy ART neural network are used in this study. Contouring and spectral analysis are used in preprocessing stage, and Fuzzy ART is used in object classification stage. Fuzzy ART is an unsupervised neural network for solving the stability-plasticity dilemma.

• 한국정밀공학회지
• /
• 제23권12호
• /
• pp.46-55
• /
• 2006

A robust motion controller based on self-organizing fuzzy control(SOFC) and feed-back tracking control technique is proposed for a two-wheel driven mobile robot. The feed-back control technique of the controller guarantees the robot follows a desired trajectory. The SOFC technique of the controller deals with unmodelled dynamics of the vehicle and uncertainties. The computer simulations are carried out to verify the tracking ability of the proposed controller with various driving situations. The results of the simulations reveal the effectiveness and stability of the proposed controller to compensate the unmodelled dynamics and uncertainties.

• 한국자동차공학회논문집
• /
• 제22권1호
• /
• pp.65-70
• /
• 2014

An Integrated Dynamics Control system with four wheel Steering (IDCS) is proposed and analysed in this study. It integrates and controls steer angle of front and rear wheel simultaneously to enhance lateral stability and steerability. An active front steer (AFS) system and an active rear steer (ARS) system are also developed to compare their performances. The systems are evaluated during brake maneuver and several road conditions are used to test the performances. The results showed that IDCS vehicle follows the reference yaw rate and reduces side slip angle very well. AFS and ARS vehicles track the reference yaw rate but they can not reduce side slip angle. On split-${\mu}$ road, IDCS controller forces the vehicle to go straight ahead but AFS and ARS vehicles show lateral deviation from centerline.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.2552-2556
• /
• 2005

In general, the forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by current control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the forklift is demanded the robust drive mode. Some cases of the mode, there aretrouble in torque control following slope capacity. The control is sensitive concerning about slope angle and output speed, various control method is studied for stability of speed control. In this paper, I apply current control for the self-tuning using the fuzzy controller to obtain robust, stable speed control and use stable, high efficiency control using DSP as main controller for high speed processor, embody dynamic characteristic of control compared the PI controller to the fuzzy controller.

• Journal of Advanced Marine Engineering and Technology
• /
• 제19권2호
• /
• pp.67-80
• /
• 1995

In order to control systems which are dominantly subjected to modeling errors and uncertainties, control strategies must deal with the effect of modeling errors and uncertainties. Since most of control methods based on system mathematical model, such as LQG/LTR method, have been developed mainly focused on stability robustness, they can not smartly improve the transient response disturbed by modeling errors and/or uncertainties. In this research, a fuzzy PID control method is suggested, which can stably improve the transient responses of systems disturbed by modeling errors as well as systems not entirely using mathematical models. So as to assure the effectiveness of suggested control method, computer simulations are accomplished for some example systems, through the comparison of transient responses.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.117-122
• /
• 1992

The fuzzy-neural hybrid control system utilizing the fuzzy-neural network(FNN) will be presented in this paper. The basic structure of the controller is the parallel combination of a conventional P-controller and a FNN. Such a combination can guarantee the stability of a plant at initial stage before the rules are completely created. And a method how to automatically tunning the parameters of the FNN will be proposed with error back-propagation(BP) algorithm. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a two DOF robot manipulator.