- 期刊
Fuzzy Complementary Filtering Algorithm for Attitude Estimation
摘要
A new fuzzy complementary filtering algorithm (FCFA) is developed for Unmanned Aerial Vehicle (UAV), which is an accurate, robust and simple algorithm for attitude estimation, and can minimize the errors and reduce computation. The fuzzy complementary filtering algorithm (FCFA) combines the translation attitude estimation from the accelerometer output with the rotation attitude estimation from the gyroscope output. It uses linguistic assessments to adjust the fuzzy weight according to the feedback data from errors and their derivatives to improve the performance and overcome the limitation regarding the rigor and accuracy in traditional complementary filtering algorithm (TCFA). The performance comparisons with TCFA and Kalman filtering algorithm are investigated. Experimental results and fuzzy linguistic analysis are given to shown the good performance of the proposed filtering algorithm.
參考文獻
延伸閱讀
- 林敬達（2007）。Implementation and Application of Collaborative Filtering Algorithms〔碩士論文，淡江大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0002-3007200714125400
- Mahmoudi, A. (2014). Adaptive Algorithm for Estimation of Two-Dimensional Autoregressive Fields from Noisy Observations. International Journal of Stochastic Analysis, (2014), 47-51. https://doi.org/10.1155/2014/247274
- 黃敬庭（2023）。Design of Evolutionary Algorithm for Solving Multimodal Continuous Optimization Problems〔碩士論文，國立臺灣師範大學〕。華藝線上圖書館。https://doi.org/10.6345/NTNU202300305
- Lin, C. (2018). New Estimation Method for Multidimensional Fuzzy Regression Discontinuity Design [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU201801706
- Chen, L. W. (2001). A Two-staged Fuzzy Clustering Algorithm with Genetic Algorithm [master's thesis, Yuan Ze University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0009-0112200611304722