• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.73-83
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• 1995

In this paper, we propose a generating method for the optimal rules of the fuzzy rule base using evolution algorithms. With the aid of evolution algorithms optimal rules of fuzzy logic system can be automatic designed without human expert's priori experience and knowledge. can be intelligent control. The a, pp.oach presented here generating rules by self-tuning the parameters of membership functions and searchs the optimal control rules based on a fitness value which is the defined performance criterion. Computer simulations demonstrates the usefulness of the proposed method in non-linear systems.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.10
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• pp.457-463
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• 2001

This paper presents a simple and new digital redesign algorithm for fuzzy-model-based controllers. In the first stage, a continuous-time TS fuzzy model is constructed for a given continuous-time nonlinear system and a corresponding continuous-time fuzzy-model-based controller is established based on the existing controller synthesis algorithms. In the second stage, the continuous-time fuzzy-model-based controller is converted to equivalent discrete-time fuzzy-model-based controller, aiming at maintaining the property of the analogue controlled system, which are called intelligent digital redesign. Finally, the proposed method is applied to the digital control of inverted pendulum system to shows the effectiveness and the effectiveness and the feasibility of the method.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.3
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• pp.14-22
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• 1994

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1159-1162
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• 1993

We describe six important defuzzification methods and their respective merits and shortcomings, dependent on the rules, domains, etc. Furthermore, we present an alternative approach, the so called ξ-Quality defuzzification method, for the case that the output fuzzy sets have different shape or are asymmetric.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.7
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• pp.1010-1024
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• 1995

An intelligent trajectory control method that controls a direction and a average velocity for a prosthetic arm by force and direction estimations using EMG signals is proposed. 3 stage linear filters are used as a real time joint trajectory planner to minimize the impact to human body induced by arm motions and to reduce muscle fatigues. We use combination of MLP and fuzzy filter for a limb direction estimation and a time model of force for determining a cartesian trajectory control parameter. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. Simulation results of the proposed method show that the arm is effectively followed the desired trajectory by estimated foreces and directions. This method reduces the number of electrodes and attatched sites compared with the method using Hogan's impedance control.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.16-24
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• 2022

This paper presents a method that can reduce the computational cost of the hierarchical quadratic programming (HQP)-based robot controller. Hierarchical controllers can effectively manage articulated robots with many degrees of freedom (DoFs) to perform multiple tasks. The HQP-based controller is one of the generic hierarchical controllers that can provide a control solution guaranteeing strict task priority while handling numerous equality and inequality constraints. However, according to a large amount of computation, it can be a burden to use it for real-time control. Therefore, for practical use of the HQP, we propose a method to reduce the computational cost by decreasing the size of the decision variable. The computation time and control performance of the proposed method are evaluated by real robot experiments with a 15 DoFs dual-arm manipulator.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.25-30
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• 2010

This paper is proposed about three axis motion control camera design method based on wires. Original motion control camera consists of track, boom, L-Head, Camera and so on and is enormous and expensive. But proposed motion control camera adjusts wire length using encoders and motors. And position control use position based straight line of straight-line move method for moving precise position. Proposed simple design is able to use various place and inexpensive than original motion control camera. But, camera was vibrated and rotated due to basic property of wire. So we proposed solutions that connected method of wire and using a tensional object for reducing rotation. For proposed algorithm verification, we realized three axis motion control camera based on wire and measured oscillation while moving same trace. We confirmed the results that standard deviation of oscillation was reduced 4.93 degree than before design method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.493-496
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• 2000

In this paper, an adaptive neuro-fuzzy controller using the conditional fuzzy c-means(CFCM) methods is proposed. Usually, the number of fuzzy rules exponentially increases by applying the grid partitioning of the input space, in conventional adaptive neuro-fuzzy inference system(ANFIS) approaches. In order to solve this problem, CFCM method is adopted to render the clusters which represent the given input and output data. Finally, we applied the proposed method to the water path temperature control system and obtained a better performance than previous works.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.435-438
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• 1997

This paper presents the process generating a SAC(Sectional Area Cure) by using ASMOD(Adaptive Spline Modeling of Observation Data). That is, we define SACs of real ships as B-spline curves by a hybrid cure approximation(which is the combination method of a B-spline fitting method and a genetic algorithm) and accumulate a database of control points. Then we let ASMOD learn from the correlation principal dimensions with control points.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.98-103
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• 1995

In this paper, a method is presented for finding an optimal temperature control pattern in microwaveoven using genetic algorithm. Power spectrum of temperature variance of charcoal is obtained and oven system modeling with fuzzy-neural-network is explained. Fan on/off timing is converted to strings in gene pool and then genetic iterations make the power spectrum of simmulated temperature variance of microwave oven closer to that o charcoal.