• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.4
• /
• pp.207-210
• /
• 2012

Genetic algorithms(GA) are well known and very popular stochastic optimization algorithm. Although, GA is very powerful method to find the global optimum, it has some drawbacks, for example, premature convergence to local optima, slow convergence speed to global optimum. To enhance the performance of GA, this paper proposes an adaptive partitioning-based genetic algorithm. The partitioning method, which enables GA to find a solution very effectively, adaptively divides the search space into promising sub-spaces to reduce the complexity of optimization. This partitioning method is more effective as the complexity of the search space is increasing. The validity of the proposed method is confirmed by applying it to several bench mark test function examples and the optimization of fuzzy controller for the control of an inverted pendulum.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.5
• /
• pp.25-32
• /
• 1996

This paper will propose the direct adaptive learning control scheme based on adaptive control technique and intelligent control theory for a nonlinear system. Using the proposed learning control scheme, we will apply to on-line control an uncertain but for model perfect matching, it's structure condition is known. The effectiveness of the proposed control schem will be illustrated by simulations of a robot manipulator.

• Proceedings of the KIEE Conference
• /
• 1999.07g
• /
• pp.2879-2881
• /
• 1999

This paper presents the adaptive Active Noise Control(ANC) system using the Neuro-Fuzzy controller. In general, the character of noise is time-varing and nonlinear Thus controller must have the adaptivness so that applied in Active Noise Control system to cancel the noise. This paper propose the Neuro-Fuzzy controller trained with back-propagation teaming algorithm to optimize the parameters of controller The objects of this paper are cancel the noise, extract the original(speech) signal polluted by noise and design the Neuro-Fuzzy controller.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2441-2443
• /
• 2003

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.801-804
• /
• 2003

The autopilot system of vessel is proposed to take service safety sorority, to elevate service efficiency, to decrease labor and to improve working environment. Ultimate purpose of it is to minimize the number of crew by guaranteeing economical efficiency of shipping service. Recently, the research is being achieving to compensate various nonlinear parameters of vessel and apply it is course keeping control, track keeping control, roll-rudder stabilization, dynamic ship positioning and automatic mooring control etc. using optimizing control technique. Relation between rudder angle controlled by steering machine of vessel and ship-heading angle, and load condition of ship are nonlinear, which affect various parameters of shipping service. The speed and direction of waves, velocity and quantity of wind, which also cause the non-linearity of it. Therefore the autopilot system of ship requires the robust control algorithm can overcome various non-linearity. On this paper, we design the autopilot system of ship, which overcome nonlinear parameters and disturbance of it using Fuzzy Algorithm, evaluate the proposed algorithm and its excellence through simulation

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.7
• /
• pp.1509-1513
• /
• 2003

The autopilot system of vessel is proposed to take service safety and security, to elevate service efficiency, to decrease labor and to improve working environment. Ultimate purpose of the proposed system is to minimize the number of crew by guaranteeing economical efficiency of shipping service. Recently, the research is being achieved to compensate various nonlinear parameters of vessel and apply it to course keeping control, track keeping control, roll-rudder stabilization, dynamic ship positioning and automatic mooring control etc. using optimizing control technique. Relation between rudder angle controlled by steering machine of vessel and ship-heading angle, and load condition of ship is nonlinear, which affects various parameters of shipping service. The speed and direction of waves, velocity and quantity of wind, which also cause the non-linearity of it. Therefore the autopilot system of ship requires the robust control algorithm can overcome various non-linearity. On this paper, we design the autopilot system of ship, which overcomes nonlinear Parameters and disturbance of it using Fuzzy Algorithm, evaluate the proposed algorithm and its excellence through simulation.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.9
• /
• pp.106-121
• /
• 1993

A New fuzzy adaptive controller which is able to solve the problems of classical adaptive controllers and conventional fuzzy adaptive controllers is suggested in this paper. The architecture of a fuzzy adaptive controller using the robust property of a fuzzy controller is explained. A design procedure which can be carried out mathematically and systematically from the model of an objective system is suggested, and related mathematical theorems and their proofs are also given. The performance of the proposed adaptive control algorithm is analyzed through a design example and a DC motor control simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.41-44
• /
• 1997

본 논문에서는 뉴로퍼지제어기를 이용한 유도가열기의 시변부하에 대한 적응 정전력 제어를 하고자 한다. 유도가열기의 정전력 조절을 위해 IGBT를 사용한 위상전이형 펄스폭변조(PWM)와 PLL에 의한 부하공진주파수 추종형 펄스 주파수변수(PFM)가 조절되는 공진 고주파 인버터를 유용한 유도가열기를 설명하고, 실험 제작된 유도가열기에서의 부하에 대한 규정 전력 추종이 잘되고 있음이 실제적으로 논증되어졌다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.12
• /
• pp.1475-1483
• /
• 1992

In this paper, a Fuzzy control approach of disturbance added servo system using MWT(modified windowing technique) was proposed. Because conventional windowing techniques adjust stepwisely a series of scale factors, even small disturbances make system unstable. But the proposed MWT adjusts exponentially. Therefore a servo system which applied this technique had coped excellenlty with internal and external disturbances, and also had decreased substantially steady-state deviation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.05a
• /
• pp.113-116
• /
• 2001

This paper analyzes the evolutionary process of a fuzzy logic controller using evolutionary activity. An evolutionary algorithm is commonly used to find solutions for given problems. However, little has been done on the analysis of the evolutionary pathways to the optimal solutions. This paper uses a genetic algorithm to construct a fuzzy logic controller for a mobile robot and applies evolutionary activity to measure the adaptability quantitatively. Evolutionary activity can be defined as the rate at which useful genetic innovations are absorbed in the population. By measuring the evolutionary activities, we will show quantitatively that the optimal fuzzy logic controller is not from other genetic phenomena like chance or necessity, but from the adaptability to a given encironment.