• 한국기계가공학회지
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• 제15권2호
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• pp.131-138
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• 2016

In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2005년도 전력전자학술대회 논문집
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• pp.697-700
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• 2005

An adaptive fuzzy sliding-mode controller (SMC) for uncertain or ill-defined single-input single-output (SISO) nonaffine nonlinear systems is proposed. By using the universal approximation property of the fuzzy logic system (FLS), it is tuned on-line to cancel the unknown system nonlinearity. We adopt a self-structuring FLS to guarantee global stability of the closed-loop system rather than semi=global boundedness. The control and adaptive laws are derived so that the estimated fuzzy parameters are bounded and the sliding condition is satisfied.

• 한국지능시스템학회논문지
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• 제18권1호
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• pp.109-115
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• 2008

무인자동차에 관한 연구가 활성화되면서 무인 주차 또한 중요한 과제로 대두되고 있다. 본 논문에서는 무인차랑을 위한 주차 편의 시스템 설계를 위하여 퍼지논리시스템에 의한 주차 알고리즘 설계를 제안하고자 한다. 기존의 논문들이 제시한 장단점을 분석하여 새로운 단일 입력을 가지는 퍼지논리시스템을 통한 주차 알고리즘을 설계하고, 시뮬레이션을 통하여 그 효용성을 확인하고자 한다.