• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.1019-1028
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• 2007

In this paper, adaptive evolutionary algorithm(AEA) is proposed, which uses both genetic algorithm(GA) with good global search capability and evolution strategy(ES) with good local search capability in an adaptive manner, when population evolves to the next generation. In the reproduction procedure, proportion of the population for GA and ES is adaptively determined according to their fitness. The AEA is used to design membership functions and scaling factors of the fuzzy logic controller(FLC). To evaluate the performance of the proposed FLC design method, we make an experiment on the FLC for the speed control of an actual DC series motor system with nonlinear characteristics. Experimental results show that the proposed controller has better performance than PD controller.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.494-500
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• 2004

The wing rock phenomenon is a high angle of attack aerodynamic motion manifested by limit cycle roll oscillations. Experimental studies reveal that direct control and manipulation of leading edge vortices, through the use of 'blowing' techniques is effective in the suppression of wing rock. This paper presents the design of a robust controller for the experimental implementation of one such 'blowing' technique - recessed angle spanwise blowing (RASB), to achieve wing rock suppression over a range of operating conditions. The robust controller employs Takagi - Sugeno fuzzy system, which is fine-tuned by experimental simulations. Performance of the controller is assessed by real-time wind tunnel experiments with an 80 degree swept back delta wing. Robustness is demonstrated by the suppression of wing rock at a range of angles of attack and free stream velocities. Numerical simulation results are used to further substantiate the experimental findings.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.155-164
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• 2006

This paper focuses on a new optimization technique of a fuzzy logic based proportional integral (FLPI) load frequency controller by the multiple tabu search (MTS) algorithm. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the MTS algorithm is proposed to simultaneously tune proportional integral gains, the membership functions and control rules of a FLPI load frequency controller in order to minimize the frequency deviations of the interconnected power system against load disturbances. The MTS algorithm introduces additional techniques for improvement of the search process such as initialization, adaptive search, multiple searches, crossover and restart process. Simulation results explicitly show that the performance of the proposed FLPI controller is superior to conventional PI and FLPI controllers in terms of overshoot and settling time. Furthermore, the robustness of the proposed FLPI controller under variation of system parameters and load change are higher than that of conventional PI and FLPI controllers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.474-478
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• 1998

This paper proposes a method which can resolve the problem of exisiting fuzzy PI controller using optimal scaling gains obtained by genetic algorithm. The new method adapt a fuzzy logic controller as a high level controller to perform scaling gain algorithm between two pre-determined sets.

• Journal of Power Electronics
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• v.10 no.3
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• pp.306-312
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• 2010

In this paper, the design of an optimum single input Fuzzy controller for application in dc to ac converters is presented. Contrary to conventional Fuzzy controllers, the proposed controller has a smaller number of rules and tuning parameters but is capable of performing identically to a conventional controller. These benefits lead to a simpler controller design. The controller is designed as a PI controller for small-signal disturbances. However, for optimum large-signal performance, heuristic tuning is used. The tuning is less complicated and hence optimum large-signal performance is achievable. The system is simulated and a hardware prototype was developed for comparison purposes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.44-49
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• 2001

For minimum phase systems, the conventional fuzzy logic controllers (FLCs) use the error and the change-of-error as fuzzy input variables. Then the control rule table is a skew symmetric type, that is, it has UNLP (Upper Negative and Lower Positive) or UPLN property. This property allowed to design a single-input FLC (SFLC) that has many advantages. But its control parameters are not automatically adjusted to the situation of the controlled plant. That is, the adaptability is still deficient. We here design a single-input direct adaptive FLC (SDAFLC). In the AFLC, some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules are adjusted by an adaptive law. The SDAFLC is designed by a stable error dynamics. We prove that its closed-loop system is globally stable in the sense that all signals involved are bounded and its tracking error converges to zero asymptotically. We perform computer simulations using a nonlinear plant and compare the control performance between the SFLC and the SDAFLC.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.785-788
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• 1993

This paper presents the prototype framework for automated integration of CMOS current-mode fuzzy logic circuits using an intelligent module approach. The library of modules representing the standard fuzzy logic operators was built. These modules were finally used to synthesized sophisticated fuzzy logic units. Fuzzy unit designs were made based upon the results of a newel methodology of the current mirror-based fuzzy logic function synthesis. This methodology is actually incorporated into the presented framework. As an example, the membership function unit was synthesized, simulated, and the final layout was generated using the presented framework. Finally, the fuzzy logic controller unit (FLC) was generated using the proposed framework. Simulation as well as measurement results show unquestionable advantages of the proposed fuzzy logic function integration system over the classical design methodology with respect to the area, relative error and performance.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2161-2163
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• 2002

The PID type controller has been widely used in industrial application doc to its simply control structure, ease of design and inexpensive cost. However control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (Fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the Fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the Fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid Fuazy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controlled is better than that of the conventional controller.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.7
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• pp.927-934
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• 2012

This paper suggests a new fuzzy PID controller with variable parameters which improves the shortage of the fuzzy PID controller with fixed parameters suggested in [9]. The derivation procedure follows the general design procedure of the fuzzy logic controller, while the resultant control law is the form of the conventional PID controller. Therefore, the suggested controller has two advantages. One is that it has only four fuzzy linguistic rules and analytical form of control laws so that the real-time control system can be implemented based on low-price microprocessors. The other is that the PID control action can always be achieved with time-varying PID controller gains only by adjusting the input and output scalers at each sampling time.

• Journal of the Korean Institute of Navigation
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• v.20 no.1
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• pp.87-96
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• 1996

In this paper, The Fuzzy Logic Controller based on T-operators is designed. Some typical T-operators and their mathematical properties are studied. A generalized fuzzy inference model is proposed by introducing the general notion of T-operators into the conventional one which is based only on the Min and Max operators. Fuzzy Logic Control algorithms based on the T-operators are suggested. Then, by computer simulations, the effect of various T-operators on the performance of the fuzzy logic controller are studied. The purpose of these simulation studies were to observe the flexibility and system responses using the processed class of T-operators in the fuzzy inference mechanisms. This observation was made on parameters such as speed of reponses, steady-state behavior and non oscillatory responses.