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Flight Motion Controller Design using Genetic Algorithm for a Quadcopter
Author(s) -
Huu Khoa Tran,
Thành Tâm Nguyên
Publication year - 2018
Publication title -
measurement and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.286
H-Index - 21
eISSN - 2051-8730
pISSN - 0020-2940
DOI - 10.1177/0020294018768744
Subject(s) - quadcopter , control theory (sociology) , waypoint , genetic algorithm , operability , controller (irrigation) , computer science , tracking (education) , motion control , fitness function , stability (learning theory) , motion (physics) , simulation , control engineering , algorithm , engineering , control (management) , artificial intelligence , real time computing , robot , aerospace engineering , agronomy , pedagogy , biology , psychology , machine learning , software engineering
In this study, the Genetic Algorithm operability is assigned to optimize the proportional–integral–derivative controller parameters for both simulation and real-time operation of quadcopter flight motion. The optimized proportional–integral–derivative gains, using Genetic Algorithm to minimum the fitness function via the integral of time multiplied by absolute error criterion, are then integrated to control the quadcopter flight motion. In addition, the proposed controller design is successfully implemented to the experimental real-time flight motion. The performance results are proven that the highly effective stability operation and the reliable of waypoint tracking.

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