DDPG-DQN-PD-Controller-for-VTOL

If you use this code, please cite with:

@conference paper { ejosat957216, 
journal = {Avrupa Bilim ve Teknoloji Dergisi},
eissn = {2148-2683}, 
publisher = {Osman SAĞDIÇ}, 
key = {cite}, 
year = {2021}, 
pages = {358 - 363},
doi = {10.31590/ejosat.957216}, 
title = {Deep Reinforcement Learning Based Controller Design for Model of The Vertical Take off and Landing System}, 
author = {Ağralı, Mahmut and Soydemir, Mehmet Uğur and Gökçen, Alkım and Sahin, Savas} }

• You can see the code that compares DQN, DDPG and PD based controller for the study in "compare_plot.m".

• You can see the MATLAB code that finds metrics for DQN based controller in "DQN_find_metrics.m".

• You can see the MATLAB code that trains DQN based agent in "DQN_VTOL_Plant_Matlab.m".

• You can see the Simulink model that contains DQN based controller and VTOL plant in "DQN_VTOL_Plant_Simulink.slx".

• You can see the trained agent for DQN in "DQN_Agent120".

• You can see the MATLAB code that finds metrics for DDPG based controller in "DDPG_find_metrics.m".

• You can see the MATLAB code that trains DQN based agent in "v_1_VTOL_Plant_DDPG_Matlab.m".

• You can see the Simulink model that contains DQN based controller and VTOL plant in "DDPG_VTOL_PLANT_Simulink.mdl".

• You can see the trained agent for DQN in "DDPG_Agent701".

• You can see the MATLAB code that finds metrics for PID based controller in "PID_find_metrics.m".

• You can see the Simulink model that contains PID based controller and VTOL plant in "PID_VTOL.slx".