The work describes an automatically on-line Self-Tunable Fuzzy Inference System (STFIS) of a mini-flying called XSF drone. A Fuzzy controller based on an on-line optimization of a zero order Takagi-Sugeno fuzzy inference system (FIS) by a back propagation-like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic error term and a weight decay term that prevents an excessive growth of parameters. Simulation results and a comparison with a Static Feedback Linearization controller (SFL) are presented and discussed. A path-like flying road, described as straight-lines with rounded corners permits to prove the effectiveness of the proposed control law. © 2007 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Maaref, H., Zemalache, K. M., & Beji, L. (2007). Self-tunable fuzzy inference system: A comparative study for a drone. Advances in Soft Computing, 41, 780–789. https://doi.org/10.1007/978-3-540-72432-2_78
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