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- W3140112304 abstract "Unmanned Aerial Vehicle (UAV) is an unmanned aircraft that can be controlled manually or automatically over long distances. The quadcopter UAV is rapidly developing in recent years due to various and military purposes. One of the quadcopter navigation system is facing towards coordinates by controlling vertical axis rotation angle (yaw) or bearing. In this project designed self tuning proportional integral derivative (PID) control with particle swarm optimization (PSO) method for bearing navigation and combined with global positioning system (GPS) to determine the coordinates of bearing angle to the destination. HMC5883L compass sensor used to calculate actual angle of the quadcopter from the earth electromagnetic field. Based on the test results, quadcopter success to hold the fixed coordinates with settling time at 6,4 seconds and average error after settling time is 5,4 o . Based on the test with coordinating change results, quadcopter success to reach the fixed coordinates with average error at 7,9 o . Based on the experiments with disturbance, got an average offset error of 1,89⁰ and settling time at 4,1 seconds. The best PSO self tuning limits is obtained at Kp = 0,15 to 0,3, Ki = 0,06 to 0,6, and Kd = 0,005 to Kd = 0,1. The PSO values used were C1 = 1,5, C2 = 2 and the weight of inertia from 0,7 to 1,2." @default.
- W3140112304 created "2021-04-13" @default.
- W3140112304 creator A5067936200 @default.
- W3140112304 date "2017-10-09" @default.
- W3140112304 modified "2023-09-26" @default.
- W3140112304 title "Particle Swarm Optimization (PSO) based Self Tuning Proportional, Intergral, Derivative (PID) for Bearing Navigation Control System on Quadcopter" @default.
- W3140112304 hasPublicationYear "2017" @default.
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