Adaptive complementary filter using fuzzy logic and simultaneous perturbation stochastic approximation algorithm

Shen, Xiaowei; Mao, Yao; Jia, Weimin; Yuan, Ding

doi:10.1016/j.measurement.2012.01.011

Cited by 24 publications

(22 citation statements)

References 21 publications

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“…where  is the cut-off frequency and  is damping ratio which is fixed to 0.707 to provide a good transient response [8,14].…”

Section: Adaptive Complementary Kalman Filtermentioning

confidence: 99%

“…where ω is the cut-off frequency and ζ is damping ratio which is fixed to 0.707 to provide a good transient response [8,14]. The complementary filter using fixed cut-off frequency is difficult to satisfy acceptable performance in dynamic condition because attitude error caused by vision data disturbance is added to the filter.…”

Section: Fuzzy Logic For Adaptive Complementary Filtermentioning

confidence: 99%

“…14, it is confirmed that the cut-off frequency of the proposed algorithm (red dot line) is adjusted by the fuzzy rules in order to reduce the effect of the bias type fault in the vision data. Whereas the cut-off frequency of the adaptive complementary filter which have no fault detection rules in the fuzzy rules [8] does not change when the bias type fault occurs. In the case of dynamic situation (27~30 time index), both of the adaptive complementary filter adjust the cut-off frequency through the fuzzy rules (rule 1~6) in table 1.…”

Section: Fig 8 Experimental Setupmentioning

confidence: 99%

“…Thus, accelerometer can be used as a compensating sensor for correcting the drift of the gyroscope. In general case, data fusion algorithms are implemented to integrate two information sources from the gyroscope and accelerometer, respectively by using extended Kalman filter [4,5] or complementary filter [6,7,8]. However, accelerometer cannot clearly distinguish inclination and acceleration.…”

Section: Introductionmentioning

confidence: 99%

“…By using the output of the fuzzy logic, the cut-off frequency of the complementary filter is adjusted as (8) and the output of the fuzzy logic is called weighting factor and is decided by (9).…”

mentioning

confidence: 99%

See 4 more Smart Citations

An Adaptive Complementary Filter For Gyroscope/Vision Integrated Attitude Estimation

Park¹,

Kang²,

Hwang³

et al. 2016

International Journal of Aeronautical and Space Sciences

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An attitude estimation algorithm which integrates gyroscope and vision measurements using an adaptive complementary filter is proposed in this paper. In order to make the filter more tolerant to vision measurement fault and more robust to system dynamics, fuzzy interpolator is applied. For recognizing the dynamic condition of the system and vision measurement fault, the cut-off frequency of the complementary filter is determined adaptively by using the fuzzy logic with designed membership functions. The performance of the proposed algorithm is evaluated by experiments and it is confirmed that proposed algorithm works well in the static or dynamic condition.

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“…where  is the cut-off frequency and  is damping ratio which is fixed to 0.707 to provide a good transient response [8,14].…”

Section: Adaptive Complementary Kalman Filtermentioning

confidence: 99%

Section: Fuzzy Logic For Adaptive Complementary Filtermentioning

confidence: 99%

Section: Fig 8 Experimental Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%