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http://dx.doi.org/10.5916/jkosme.2007.31.5.599

System Identification by Real-Coded Genetic Algorithm  

Ahn, Jong-Kap (한국항만연수원)
Lee, Yun-Hyung (한국해양대학교 대학원 메카트로닉스공학부)
Jin, Gang-Gyoo (한국해양대학교 IT공학부)
So, Myung-Ok (한국해양대학교 선박전자기계공학부)
Publication Information
Journal of Advanced Marine Engineering and Technology / v.31, no.5, 2007 , pp. 599-605 More about this Journal
Abstract
This paper presents a method for identifying various systems based on input-output data and a real-coded genetic algorithm(RCGA). The advantages of this technique are, first, it is not dependent on the deterministic or stochastic nature of the systems and, second, the globally optimized models for the original systems can be identified without the need of a differentiable measure function of linearly separable parameters. Under suitable hypotheses, the estimation error is shown to converge in probability to zero. The performance of the proposed algorithm is demonstrated through several simulations.
Keywords
System identification; Parameter estimation; Real-coded genetic algorithm;
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