• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1636-1641
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• 2008

In this study, we introduce a new approach to Parallel Genetic Algorithms (PGA) which combines AHFCGA with crossover operator. As to crossover operators, we use three types of the crossover operators such as modified simple crossover(MSX), arithmetic crossover(AX), and Unimodal Normal Distribution Crossover(UNDX) for real coding. The AHFC model is given as an extended and adaptive version of HFC for parameter optimization. The migration topology of AHFC is composed of sub-populations(demes), the admission threshold levels, and admission buffer for the deme of each threshold level through succesive evolution process. In particular, UNDX is mean-centric crossover operator using multiple parents, and generates offsprings obeying a normal distribution around the center of parents. By using test functions having multimodality and/or epistasis, which are commonly used in the study of function parameter optimization, Experimental results show that AHFCGA can produce more preferable output performance result when compared to HFCGA and RCGA.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.308-309
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• 2007

본 논문에서는 계층적 공정 경쟁 기반 병렬 유전자 알고리즘 (Hierarchical Fair Competition Genetic Algorithm: HFCGA)을 이용하여 Ball & Beam 시스템에 최적의 Fuzzy Cascade 제어기를 설계하고자 한다. Ball & Beam 시스템은 비선형적이며 Beam의 마찰계수와 Ball의 중력 가속도를 고려하여 Ball의 위치를 조정하는 시스템이다. 이러한 Ball & Beam 시스템에 대해 Fuzzy Cascade 제어기를 설계하고, 조기 수렴에 문제가 있는 기존의 유전자 알고리즘을 개선한 HFCGA를 이용하여 제어기의 파라미터를 최적화 한다. 마지막으로 실제 플랜트에 적용하여 설계된 제어기의 성능을 평가하고, PD Cascade 제어기와 Fuzzy Cascade 제어기의 성능을 비교한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.972-980
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• 2010

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.