Fuzzy-PD Controller for behavior mixing and improved performance in quadcopter attitude control systems

Juan Augusto Paredes; Cristhian Jacinto; Renzo Ramírez; Ismael Vargas; Luis Trujillano

Fuzzy-PD Controller for behavior mixing and improved performance in quadcopter attitude control systems

Juan Augusto Paredes, Cristhian Jacinto, Renzo Ramírez, Ismael Vargas, Luis Trujillano

Sección de Ingeniería Mecánica

Pontificia Universidad Catolica del Peru

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The PID controllers featured in several commercial and industrial quadcopters present a simple framework which trivializes the control configuration process for these systems. However, since PID gains remain unchanged throughout the entire flight operation, only a single flight configuration is available for the quadcopter to move around. In order to give more flexibility to this control system, a Fuzzy-PD Controller structure based on the Sugeno fuzzy inference method is proposed. The suggested controller will be used to combine the behaviors of several PD controller configurations to control the states of a given quadcopter system and improve their individual performance.

Original language	Spanish
Title of host publication	2016 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2016 - Proceedings
State	Published - 23 Mar 2017

Cite this

@inproceedings{3458ea8827ec4b89935a0100c80c54db,

title = "Fuzzy-PD Controller for behavior mixing and improved performance in quadcopter attitude control systems",

abstract = "The PID controllers featured in several commercial and industrial quadcopters present a simple framework which trivializes the control configuration process for these systems. However, since PID gains remain unchanged throughout the entire flight operation, only a single flight configuration is available for the quadcopter to move around. In order to give more flexibility to this control system, a Fuzzy-PD Controller structure based on the Sugeno fuzzy inference method is proposed. The suggested controller will be used to combine the behaviors of several PD controller configurations to control the states of a given quadcopter system and improve their individual performance.",

author = "Paredes, {Juan Augusto} and Cristhian Jacinto and Renzo Ram{\'i}rez and Ismael Vargas and Luis Trujillano",

year = "2017",

month = mar,

day = "23",

language = "Espa{\~n}ol",

booktitle = "2016 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2016 - Proceedings",

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Fuzzy-PD Controller for behavior mixing and improved performance in quadcopter attitude control systems. / Paredes, Juan Augusto; Jacinto, Cristhian; Ramírez, Renzo et al.
2016 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2016 - Proceedings. 2017.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fuzzy-PD Controller for behavior mixing and improved performance in quadcopter attitude control systems

AU - Paredes, Juan Augusto

AU - Jacinto, Cristhian

AU - Ramírez, Renzo

AU - Vargas, Ismael

AU - Trujillano, Luis

PY - 2017/3/23

Y1 - 2017/3/23

N2 - The PID controllers featured in several commercial and industrial quadcopters present a simple framework which trivializes the control configuration process for these systems. However, since PID gains remain unchanged throughout the entire flight operation, only a single flight configuration is available for the quadcopter to move around. In order to give more flexibility to this control system, a Fuzzy-PD Controller structure based on the Sugeno fuzzy inference method is proposed. The suggested controller will be used to combine the behaviors of several PD controller configurations to control the states of a given quadcopter system and improve their individual performance.

AB - The PID controllers featured in several commercial and industrial quadcopters present a simple framework which trivializes the control configuration process for these systems. However, since PID gains remain unchanged throughout the entire flight operation, only a single flight configuration is available for the quadcopter to move around. In order to give more flexibility to this control system, a Fuzzy-PD Controller structure based on the Sugeno fuzzy inference method is proposed. The suggested controller will be used to combine the behaviors of several PD controller configurations to control the states of a given quadcopter system and improve their individual performance.

M3 - Contribución a la conferencia

BT - 2016 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2016 - Proceedings

ER -