Intelligent control for a drone by self-tunable fuzzy inference systemReport as inadecuate




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1 LDEE 2 SIBI IBISC - Informatique, Biologie Intégrative et Systèmes Complexes

Abstract : The work describes an automatically on-line Self-Tunable Fuzzy Inference System STFIS of a new configuration of mini-flying called XSF X4 Stationnary Flyer drone. A Fuzzy controller based on 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. Thus, we carried out control for the continuation of simple trajectories such as the follow-up of straight lines, and complex half circle, corner by using the STFIS technique. This permits to prove the effectiveness of the proposed control law. We studied the robustness of the two controllers used in the presence of disturbances. We presented two types of disturbances, the case of a gust of wind and taking into account white noise disturbances. A comparison between the Self-Tunable Fuzzy Inference System STFIS and Adaptive Network based Fuzzy Inference System ANFIS is given.

Keywords : Drone Self-tunable fuzzy inference system Static feedback linearization controller Tracking control





Author: Kadda Zemalache - Hichem Maaref -

Source: https://hal.archives-ouvertes.fr/



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