• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.80-89
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• 1996

This paper proposes a new COA (center of area) defuzzifier that is working in the accurate and fast manner. The proposed COA defuzzifier involves both membership values and the spans of membership functions in clauclating a crisp value. In additon, it avoid division by replacing the COA calculation with the searching of the momentum equilibrium point. The moment equilibrium point is searched in the coarse-to-fine manner such that the moment computing points during the coarse searching are moved in the interval of fuzzy terms until they are reached at two adjacent fuzzy terms searching method accerlates the finding of the moment equilibrium point by O(M) mazimally when compared iwth the equal interval searching method of ruitz. In order to verify the accuracy of the proposed COA defuzzifier, the crisp values obtained form the proposed coarse-to-fine searching are compared with the precise crisp values from the arithmetic calculation. Application to the truck backer-upper control problem of the proposed COA defuzzifier is presented. The control performance is compared with that of the conventional COA defuzzifier in tems of the average tracing distance.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.578-580
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• 1998

The paper presents an approach to the structure identification based on the CART (Classification And Regression Tree) algorithm and to the parameter identification by hybrid learning method in neuro-fuzzy system. By using the CART algorithm, the proposed method can roughly estimate the numbers of membership function and fuzzy rule using the centers of decision regions. Then the parameter identification is carried out by the hybrid learning scheme using BP (Back-propagation) and RLSE (Recursive Least Square Estimation) from the numerical data. Finally, we will show it's usefulness for fuzzy modeling to truck backer upper control.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.223-231
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• 2006

In high-speed fuzzy control systems applied to intelligent systems such as robot control, one of the most important problems is the improvement of the execution speed of the fuzzy inference. In particular, it is more important to have high-speed operations in the consequent part and the defuzzification stage. To improve the speedup of fuzzy controllers for intelligent systems, this paper presents an integer line mapping algorithm to convert [0, 1] real values of the fuzzy membership functions in the consequent part to a $400{\times}30$ grid of integer values. In addition, this paper presents a method of eliminating the unnecessary operations of the zero items in the defuzzification stage. With this representation, a center of gravity method can be implemented with only integer additions and one integer division. The proposed system is analyzed in the air conditioner control system for execution speed and COG, and applied to the truck backer-upper control system. The proposed system shows a significant increase in speed as compared with conventional methods with minimal error; simulations indicate a speedup of an order of magnitude. This system can be applied to real-time high-speed intelligent systems such as robot arm control.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.7
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• pp.38-50
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• 1997

This paper concerns a VHDL design and simulation of an accurate and cost-effective fuzzy logic controller (FLC). The accurcy of the proposed FLC is obtained by using the center of gravity (COG) defuzzifier that considers both membership values and spans of membership functions in calculating a crisp value. The cost-effectiveness of the proposed FLC is obtained by restructuring the conventional FLC in the following ways: Firstly, the MAX-MIN inference is inference is replaced by a read-modify-write operation that can be implemented economically in the structure of register files. Secondly, the division in the COG defuzzifier is avoided by finding the moment equilibrium point. The proposed COG defuzzifier has two disadvantages that it requires additional multipliers and it takes a lot of computation time to find the moment equilibrium point. The first disadvantage is overcome by replacing the mulitpliers with stochastic AND operations and the second disadvantage is alleviated by using a coarse-to-fine searching algorithm. The proposed FLC is described in VHDL structurally and behaviorally and whether it is working well or not is checked on SYNOPSYS VHDL simulator by using the truck backer-upper control problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.194-202
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• 2000

In this paper, an efficient fuzzy rule generation scheme for Adaptive Network-based Fuzzy Inference System(ANFIS) using the conditional fuzzy-means(CFCM) and fuzzy equalization(FE) methods is proposed. Usually, the number of fuzzy rules exponentially increases by applying the gird partitioning of the input space, in conventional ANFIS approaches. Therefore, CFCM method is adopted to render the clusters which represent the given input and output fuzzy and FE method is used to automatically construct the fuzzy membership functions. From this, one can systematically obtain a small size of fuzzy rules which shows satisfying performance for the given problems. Finally, we applied the proposed method to the truck backer-upper control and Box-Jenkins modeling problems and obtained a better performance than previous works.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.70-81
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• 1998

This paper proposes an accurate and cost-effective COA defuzzifier of fuzzy logic controller (FLC). The accuracy of the proposed COA defuzzifier is obtained by involving both membership values and spans of membership functions in calculating a crisp value. The cost-effectiveness of the proposed COA defuzzifier is obtained by replacing the division in the COA defuzzifier by finding an equilibrium point of both the left and right moments. The proposed COA defuzzifier has two disadvantages that it ncreases the hardware complexity due to the additional multipliers and it takes a lot of computation time to find the moment equilibrium point. The first disadvantage is overcome by replacing the multipliers with the stochastic AND operations. The second disadvantage is alleviated by using a coarse-to-fine searching algorithm that accelerates the finding of moment equilibrium point. Application of the proposed COA defuzzifier to the truck backer-upper control problem is performed in the VHDL simulation and the control accuracy of the proposed COA defuzzifier is compared with that of the conventional COA defuzzifier in terms of average tracing distance.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.634-643
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• 1999

This paper concerns an implementation of f~rry logic controller (FLC') on a reconfigurahle FP

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.5
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• pp.83-97
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• 1998

This paper developes an integrated environment CAD system that can design and implement an accurate and cost-effective FLC automatically. For doing this, an integrated development environment (IDE) (called FADIS; FLC Automatic Design and Implementation Station) is built by the seemless coupling of many existing. CAD tools in an attempt to the FADIS performs various functions such that (1) i~utomatically generate the VHDL components appropriate for the proposed FLC architecture from the various design parameters (2) simulate the generated VHDL code on the Synopsys's VHDL Simulator, (3) automatically compiler, (4) generate the optimized, placed, and routed rawbit files from the synthesized modules by Xilinx's XactStep 6.0, (5) translate the rawbit files into the downloadable ex- [:cution reconfigurable FPGA board (VCC's EVCI), and (7) continuously monitor the control status graphically by communicating the FLC with the controlled target via S-bus. The developed FADIS is tested for its validity by carrying out the overall procedures of designing and implementing the FLC required for the truck-backer upper control, the reduction of control execution time due to the controller's FPGA implementation is verified by comparing with other implementations.