• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.249-254
• /
• 2001

Abstract In this paper, we propose a method of cooperative control based on artifical intelligent system in distributed autonomous robotic system. In general, multi-agent behavior algorithm is simple and effective for small number of robots. And multi-robot behavior control is a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. However when the number of robot goes on increasing, this becomes difficult to be realized because multi-robot behavior algorithm provide on multiple constraints and goals in mobile robot navigation problems. As the solution of above problem, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for obstacle avoidance. Here, we propose an architecture of fuzzy system for each multi-robot speed control and fuzzy-neural network for their direction to avoid obstacle. Our focus is on system of cooperative autonomous robots in environment with obstacle. For simulation, we divide experiment into two method. One method is motor schema-based formation control in previous and the other method is proposed by this paper. Simulation results are given in an obstacle environment and in an dynamic environment.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.1
• /
• pp.72-78
• /
• 2003

A new self-organizing neuro-fuzzy network based rate control algorithm for MPEG-4 video encoder is proposed in this paper. Contrary to the traditional methods that construct the rate-distorion (RD) model based on experimental equations, the proposed method effectively exploits the non-stationary property of the video date with neuro-fuzzy network that self-organizes the RD model online and adaptively updates the structure. The method needs not require off-line pre-training; hence it is geared toward real-time coding. The comparative results through the experiments suggest that our proposed rate control scheme encodes the video sequences with less frame skip, providing good temporal quality and higher PSNR, compared to VM18.0.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.153-156
• /
• 2001

Fuzzy controllers also show good performance In case of the systems being nonlinear and difficult to solve. But these fuzzy controllers have problems which have to decide suitable rules and membership functions. In general we decide those using the heuristic methods or the experience of experts. Therefore, many researchers have applied genetic algorithms to make fuzzy rule automatically. In this paper, we suggest a new coding method and a new crossover method to maintain the good fuzzy rule base and the shape of membership

• Proceedings of the KIEE Conference
• /
• 1992.07b
• /
• pp.1238-1241
• /
• 1992

The series type DC motor is normally nonlinearly modeled, but in this paper, the nonlinear model is linearized for the speed control. The proposed algorithm is constructed by the fuzzy logic controllers. Then the system is investigated for the effects of changes by the scale factor, and fuzziness of fuzzy variables.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.2033-2034
• /
• 2006

In this paper, we applied genetic algorithm to current control for robust control and stability. In conclusion, we prove that current control of genetic algorithm can be high efficiency.

• Proceedings of the SAREK Conference
• /
• 2004.11a
• /
• pp.34-34
• /
• 2004

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.10a
• /
• pp.217-220
• /
• 2004

Controller that is designed in this paper is form that apply PID controller about Fuzzy algorithm. Fuzzy Controller that using this paper is can speak that compensation style fuzzy controller as form to solidify action of PID controller for plant. This is not form that autotuning the each PID coefficient. We Apply and examined the response character to AGC(Automatic Generation Control) system using designed controller.

• Proceedings of the IEEK Conference
• /
• 2000.06e
• /
• pp.55-58
• /
• 2000

Previous works using a Multi-population Genetic Algorithm have divided chromosome into two components, rule sets and membership functions. However, in this case bad rule sets disturb optimization in good rule sets and membership functions. A new method for a Multi-population Genetic Algorithm suggests three components, good rule sets, bad rule sets, and membership functions. To show the effectiveness of this method, fuzzy controller is applied in a Truck Backing Problem. Results of the computer simulation show good adaptation of the proposed method for a Multi-population Genetic Algorithm.

• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.583-586
• /
• 1995

In this paper, a nor fuzzy control algorithm for the target tracking system is proposed, and its characteristics are analyzed and compared with those of the traditional PID controller. Fuzzy rules are generated experimentally using Mamdani's minimum operation and the center of area method. The experimental results prove that the proposed fuzzy algorithm is excellent in our tracking system and its performance is superior to that of the PID controller.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1993.04a
• /
• pp.213-217
• /
• 1993

This paper presents an end-point of 1-link flexible robot arm with a tip-mass by using self-turning fuzzy algorithm. The arm is mounted on a translational mechanism driven by a ballscrew, whose rotation is controlled by CD servomotor. Tip position is controlled so that it follows a desired position. A feedback signal is composed of both the tip-displacement error and change in error. This paper gives the experimental tip responses according to the variations of tip-mass and beam-length, and also showes the effects of reducing the residual vibrations occuring at the end-point.