• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2476-2478
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• 2000

Fuzzy Systems which are based on membership functions and rules, can control nonlinear, uncertain, complex systems well. However, Fuzzy logic controller(FLC) has problems: It is some difficult to design the stable FLC for a beginner. Because FLC depends mainly on individual experience. Sliding control is a powerful robust method to control nonlinearities and uncertain parameters systems. But it has a chattering problem by discontinuous control input according to sliding surface. Therfore it needs to be smoothed to achieve an optimal input. In this paper, To solve problems desinged Fuzzy Sliding Control. The effictiveness of result is shown by the simulation and the experimental test for Truck Backer-Upper Control.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.6
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• pp.638-645
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• 2002

This paper presents a scheme for integrating PID control, gain scheduling and emerging techniques in the field of artificial intelligence, such as fuzzy logic and genetic algorithms for the speed control of a marine diesel engine. At first, local PID controllers are designed based on a local model obtained at each speed mode, whose parameters are optimally tuned using a real-coded genetic algorithm. Then, fuzzy "if-then" rules combine the local controllers as a consequence part to implement fuzzy gain scheduling. To demonstrate the performance of the proposed fuzzy PID controller on overall operating conditions, a set of simulation works on B'||'&'||'W's 4L80MC diesel engine are carried out.t.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.238-242
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• 2001

In this paper, we proposed an optimal identification method of the membership functions and the numbers of fuzzy rule base for the stabilization controller of the Thermal process control system by RVEGA. Although fuzzy logic controllers and expert systems have been successfully applied in many complex industrial process, they must rely on experts knowledges. So it is difficult in determination of the linguistic state space, definition of the membership functions of each linguistic term and the derivation of the control rules. To verify the validity of this RVEGA-based fuzzy controller, Thermal process control system, with strong nonlinear dynamics, was selected for application of this algorithm and compare with PI controller, and the empirically improved fuzzy controller.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.353-358
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• 2002

A feature-based inspection planning system is proposed in this research to develop more efficient measuring methodology for the OMM (On-machine measurement) for complicated workpiece having many primitive form features. This paper focuses on the development of the CAIP (computer-aided inspection system) methodologies. The optimum inspection sequences for the features are determined by analyzing the feature information such as the nested relations and the possible probe approaching directions of the features, and forming feature groups. A series of heuristic rules are developed to accomplish it. Also, each feature is decomposed into its constituent geometric elements, and then the number of sampling points, the locations of the measuring point, the optimum probing path are determined by applying the fuzzy logic, Hammersley's method, and the TSP algorithm. To verify the proposed methodologies, simulations are carried out and the results are analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.205-209
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• 1998

A synthesis of fuzzy variable structure control is proposed to design a high-angle-of-attack flight system for a modification version of the F-18 aircraft. The knowledge of the proportional, integral, and derivative control is combined into the fuzzy control that addresses both the highly nonlinear aerodynamic characteristics of elevators and the control limit of thrust vectoring nozzles. A simple gain scheduling method with multi-layered fuzzy rules is adopted to obtain an appropriate blend of elevator and thrust vectoring commands in the wide operating range. Improving the computational efficiency, an accelerated kernel for on-line fuzzy reasoning is also proposed. The resulting control system achieves the good flying quantities during a high-angle-of- attack excursion. Thus the fuzzy logic can afford the control engineer a flexible means of deriving effective control laws in the nonlinear flight regime.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.652-658
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• 1997

Coagulant feeding control is very important in the water treatment process. Coagulant feeding is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and so on. However, since the process of chemical reaction has not been clarified so far, coagulant dosing rate has been decided by jar-test. In order to overcome the difficulty mentioned above, Fuzzy Neural Network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to the automatic determination of coagulant dosing rate. This algorithm can automatically identify the if-then rules, tune the membership functions by utilizing expert's experimental data. The proposed scheme is evaluated by computer simulation and interfaced with coagulant feeder operated by magnetic flowmeter, control valve and PLC. It is shown that coagulant feeding according to real time sensing of water quality is very effective.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.496-508
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• 1999

Fuzzy System which are based on membership functions and rules can control nonlinear uncertain complex systems well. However Fuzzy logic controller(FLC) has problems; It is difficult to design the stable FLC and FLC depends mainly on individual experience. Although FLC can be designed using the error back-propagation algorithm it takes long time to converge into global optimal parameters. Well-developed linear system theory should not be replaced by FLC but instead it should be suitably used with FLC. A new methodology is introduced for designing THEN-PART membership functions of FLC based on its well-tuned state feedback controller. A example of inverted pendulum is given for demonstration of the robustness of proposed methodology.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.87-93
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• 2008

In this paper, we propose a hierarchical fuzzy based nutrition evaluation system that can analyze the individuals' nutrition status through the inference results generated by each layer. Moreover, a method to minimize the uncertainty of inference in the evaluated nutrition status is discussed. To show the effect of the uncertainty in fuzzy inference, we compared the results of nutrition evaluation with/without the certainty factor of rules on 132 people over the age of 65. From the experimental results, we can see that the evaluation method with the modified certainty factor provides better reliability than that of the general evaluation method without the certainty factor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1319-1329
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• 2012

Globally stabilizing adaptive fuzzy state- and output-feedback controllers for the fully nonaffine pure-feedback nonlinear system are proposed in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controllers require no backstepping design procedures. Avoiding backstepping makes the controller structure and stability analysis to be considerably simplified. For the global stabilty of the clossed-loop system, the self-structuring fuzzy system whose memebership functions and fuzzy rules are automatically generated and tuned is adopted. The proposed controllers employ only one fuzzy logic system to approximate unknown nonlinear function, which highlights the simplicity of the proposed adaptive fuzzy controller. Moreover, the output-feedback controller of the considered system proposed in this paper have not been dealt with in any literature yet.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1122-1124
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• 1996

Depth between the robot and the target is an essential information in the robot control. However, in case of eye-in-hand robot with one camera, it is not easy to get an accurate depth information in real-time. In this paper, the techniques of depth-from-motion and depth-from-focus are combined to accomplish the real-time requirement. Integration of the two approaches are accomplished by appropriate use of confidence factors which are evaluated by fuzzy rules. Also a fuzzy logic based calibration technique is proposed.