• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.525-529
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• 2009

Most of FLC received input data from error e and change-of-error e' with no relation with system complexity. Basic scheme follows typical PD and PI or PID Controller and that has been developed through fixed ME In this paper, We studied the relationship between MF and system response and system response through changing Fuzzy variable of consequence MF and propose the simple FLC using this relationship. The response of FLC is changed according to the width of Fuzzy variable of consequence MF. As changing the Fuzzy variable of consequence MF shows various nonlinear characteristic, we studied the relation between response and MF using analytical method. We designed the effective FLC using three-variable MF and nine rules and took simulation for verification. In this study, we propose the method to design system with FLC in stability point which is an impotent characteristic of designing system. The circle criterion which is adapted to analysis the nonlinear system is put to use for proposed method. Since SISO FLC has a time-invariant and odd characteristic we can use the critical point not disk which is generally used to determine the stability in the circle criterion, to determine the stability. Using this, we can get the maximum critical point plot of SISO FLC with changing the consequence fuzzy variables. The predetermined critical point plot of FLC can be used to decide the region of the system to be stable. This method is effectively used to design the SISO FLC.

• Journal of Navigation and Port Research
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• v.33 no.6
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• pp.387-393
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• 2009

In this paper, a 3-D simulator was developed to estimate visually the performance of propelling and integrated control system of the underwater cleaning robot. Based on the dynamics analysis of the UCR, the 3-D model of the UCR was used in the simulator in which position and velocity are included Also, an input and control system using a joystick was developed, and the simulator was applied to the input and control of the simulator. Moreover, an integrated navigation control system was designed, and its performance was validated by a way-point simulator including a PI-based fuzzy control law.