TY - GEN
T1 - Autonomous Quadcopter Trajectory Tracking with MPC
AU - Fathani, Namira
AU - Santoso, Ari
AU - Sahal, Mochammad
AU - Arifin, Imam
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Quadcopters have a nonlinear model, multivariable systems, and six degrees of freedom (6-DOF) to control four actuators. In this study, the quadcopter used feedback linearization model to control the position and Model Predictive Control (MPC) based on Linear Parameters Varying (LPV) to control the attitude of the quadcopter. Position controller of supposed method used feedback linearization for linearized the system. The input for controlling position used in state feedback. Pole placement also used for placing the pole of the position equation into stable one. For reaching the pole, Proportional-Derivative controller used to improve the results. The attitude controller used LPV as the varying parameters contain of the acceleration of euler angles and the angular rates of each rotors. The simulation was performed to examine the performance. The simulation results show that the designed control algorithm can track the trajectory. The analysis shows that the proposed controller have RMSE 0.2225, this result based on trajectory result and reference.
AB - Quadcopters have a nonlinear model, multivariable systems, and six degrees of freedom (6-DOF) to control four actuators. In this study, the quadcopter used feedback linearization model to control the position and Model Predictive Control (MPC) based on Linear Parameters Varying (LPV) to control the attitude of the quadcopter. Position controller of supposed method used feedback linearization for linearized the system. The input for controlling position used in state feedback. Pole placement also used for placing the pole of the position equation into stable one. For reaching the pole, Proportional-Derivative controller used to improve the results. The attitude controller used LPV as the varying parameters contain of the acceleration of euler angles and the angular rates of each rotors. The simulation was performed to examine the performance. The simulation results show that the designed control algorithm can track the trajectory. The analysis shows that the proposed controller have RMSE 0.2225, this result based on trajectory result and reference.
KW - Quadcopter
KW - feedback linearization
KW - linearized parameter variable
KW - model predictive control
UR - https://www.scopus.com/pages/publications/85219527762
U2 - 10.1109/SCOReD64708.2024.10872633
DO - 10.1109/SCOReD64708.2024.10872633
M3 - Conference contribution
AN - SCOPUS:85219527762
T3 - 2024 IEEE 22nd Student Conference on Research and Development, SCOReD 2024
SP - 369
EP - 374
BT - 2024 IEEE 22nd Student Conference on Research and Development, SCOReD 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd IEEE Student Conference on Research and Development, SCOReD 2024
Y2 - 19 December 2024 through 20 December 2024
ER -