• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.303-308
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• 2004

Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy-neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.583-588
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• 1989

In this paper, a modelling methodology for a robotic workcell is proposed and compared with the conventional Petri nets model. Also, a method for managing the cell operation is described through the knowledge base. The knowledge bases for state transition and assembly job information are obtained from the state transition map(STM) and the assembly job tree(AJT), respectively. Using the knowledge base, the system structure is discussed in both managing the cell operation and evaluating the various performance. Finally, a simulation algorithm is presented with the simulation results to show the effectiveness of the proposed modelling approach.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.455-464
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• 1994

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan's method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMG signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• Journal of Internet Computing and Services
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• v.8 no.2
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• pp.137-146
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• 2007

This paper presents a way to integrate a task planner with a plan executive for efficient control of intelligent robots. For this purpose, it first surveys several types of the existing task planners and plan executives. And then it introduces a new approach that combines a BDI-based executive with an on-demand task planner, and it explains a control architecture of intelligent robots based upon this integrating paradigm. Finally it analyzes the flexibility and robustness of both the proposed integrating paradigm and the control architecture through implementation of a demo system using AIBO robots.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.297-303
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• 2005

In this paper, I developed an intelligent multi agents based softPLC(IMPLC). In IMPLC, the standard IEC 1131-3 PLC languages(LD, SFC, FBD, ST) programmed by a user are converted to IL, which is one of intermediate codes, in order to make them interactions. And then the IL is converted to the standard C code regarding some extension and transplanting, which can be used in a commercial editor such as visual C++. In IMPLC, the logical errors and syntax errors occurred by users are detected, so that the optimal PC control based softPLC can be possible. IMPLC provide easy programming platform to such beginner as well as professionals. The study of code conversion is firstly tried in the world as well as KOREA. I applied IMPLC to 3 steps conveyer belt system. The simulation results say that the debugging steps by IMPLC using multi agents are decreased than the conventional softPLC's.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.346-349
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• 2003

For a traveling crane, various control methods such as neural network predictive control and TDOFPID(Two Degree of Freedom Proportional Integral Derivative) are studied. So in this paper, we proposed improved navigation method to reduce transfer time and sway with anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the NNPPID(Neural Network Predictive PID) controller to control the precise move and speedy navigation. The proposed predictive control system is composed of the neural network predictor, TDOFPID controller, and neural network self-tuner. We analyzed ASC(Automated Stacking Crane) system and showed some computer simulations to prove excellence of the proposed controller than other conventional controllers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.438-442
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• 1998

The helicopter system is non-linear and complex. Futhermore, because of absence of an accurate mathematical model, it is difficult accurately to control its attitude. But we can control the non-modeled system with the uncertainty and unstructure using the fuzzy control algorithm. Therefore, we apply optimized fuzzy controllers for the control of its elevation angle and azimuth one using expert's intuitions and knowledges. The simulation and experimental results of the hellicopter simulator CE150 with MATLAB shall be introduced.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.141-144
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• 2003

A composite adaptive dual fuzzy controller combining the approximate mathematical model, linguistic model description, linguistic control rules and identification modeling error into a single adaptive fuzzy controller is developed for a nonlinear system. It ensures the system output tracks the desired reference value and excites the plant sufficiently for accelerating the parameter estimation process so that the control performances are greatly improved. Using the Lyapunov synthesis approach, proposed controller is analyzed and simulation results verify the effectiveness of the proposed control algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.49-53
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• 2011

Path following of the mobile robot is one research hot for the mobile robot navigation. For the control system of the wheeled mobile robot(WMR) being in nonhonolomic system and the complex relations among the control parameters, it is difficult to solve the problem based on traditional mathematics model. In this paper, we presents a simple and effective way of implementing an adaptive following controller based on the PID for mobile robot path following. The method uses a non-linear model of mobile robot kinematics and thus allows an accurate prediction of the future trajectories. The proposed controller has a parallel structure that consists of PID controller with a fixed gain. The control law is constructed on the basis of Lyapunov stability theory. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity and orientation tracking control of the nonholonomic WMR. The simulation results of wheel type mobile robot platform are given to show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.141-144
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• 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.