2013 18th International Conference on Methods &Amp; Models in Automation &Amp; Robotics (MMAR) 2013
DOI: 10.1109/mmar.2013.6669989
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An adaptive neuro PID for controlling the altitude of quadcopter robot

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Cited by 30 publications
(22 citation statements)
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“…The flying robot considered in this work is classified as a mini flying robot with limited weight to less than 1 kg. Integration of a homemade flying robot with altitude controlling system [3] and a small camera are required in order to have an adequate embedded image-processing platform. The prototype built to test the image processing feedback with detail is shown in Figure 3.…”
Section: Quadcopter Dynamic Modelmentioning
confidence: 99%
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“…The flying robot considered in this work is classified as a mini flying robot with limited weight to less than 1 kg. Integration of a homemade flying robot with altitude controlling system [3] and a small camera are required in order to have an adequate embedded image-processing platform. The prototype built to test the image processing feedback with detail is shown in Figure 3.…”
Section: Quadcopter Dynamic Modelmentioning
confidence: 99%
“…The prototype built to test the image processing feedback with detail is shown in Figure 3. The control of quadcopter is applied PID controller, that the coefficients of which was improved by genetic algorithm [3], which is implemented on AVR microcontroller. The performance of the overall system is valuated in real-time experiments.…”
Section: Quadcopter Dynamic Modelmentioning
confidence: 99%
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“…Penalaan nilai koefisien yang tepat akan menghasilkan kendali yang stabil. Akan tetapi, kendali PID ditujukan pada sistem yang linier untuk dapat bekerja dengan optimal [2]. Hal ini tentu merupakan salah satu kekurangan PID jika diterapkan pada quadrotor yang pada kenyataannya memiliki dinamika nonlinier [3].…”
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