Data-Driven Linear Quadratic Regulator using LightGBM for Quadcopter Control

被引：0

作者：

Al Ghifari, Ahmad Musthafa ^{[1
]}

Mahayana, Dimitri ^{[1
]}

Harsoyo, Agung ^{[1
]}

机构：

[1] Inst Teknol Bandung, Sch Elect Engn & Informat, Bandung, Indonesia

来源：

2024 IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND INTELLIGENT SYSTEMS, I2CACIS 2024 | 2024年

关键词：

Quadcopter control system; machine learning; Linear Quadratic Regulator (LQR); LightGBM;

D O I：

10.1109/I2CACIS61270.2024.10649852

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A quadcopter is an unmanned aerial vehicle that requires a control system to stabilize it during flight. In this paper, a data-driven control algorithm, Light Gradient Boost Machine (LightGBM) is proposed to improve the quadcopter control system. The input and output data we use for the LightGBM algorithm are obtained from a closed-loop quadcopter system with a linear quadratic regulator (LQR) controller. With the expectation that the LightGBM control algorithm can replace the LQR controller on the quadcopter. Simulations have been carried out in this study, and the results of the simulations show that the proposed algorithm has similar response results as LQR control, so that the proposed algorithm can be used as a control system in the quadcopter system.

引用

页码：391 / 396

页数：6

共 17 条

[1] Deep Reinforcement Learning for Trajectory Generation and Optimisation of UAVs [J].

Akhtar, Mishma ;

Maqsood, Adnan ;

Verbeke, Mathias .

2023 10TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN AIR AND SPACE TECHNOLOGIES, RAST, 2023,

[2] Optuna: A Next-generation Hyperparameter Optimization Framework [J].

Akiba, Takuya ;

Sano, Shotaro ;

Yanase, Toshihiko ;

Ohta, Takeru ;

Koyama, Masanori .

KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2019, :2623-2631

[3] Robust Backstepping Sliding Mode Control for a Quadrotor Trajectory Tracking Application [J].

Almakhles, Dhafer J. .

IEEE ACCESS, 2020, 8 :5515-5525

[4]

Aziz Norshakirah, 2020, 2020 International Conference on Computational Intelligence (ICCI), P11, DOI 10.1109/ICCI51257.2020.9247843

[5]

Babu VM, 2017, 2017 18TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR), P167, DOI 10.1109/ICAR.2017.8023513

[6]

Deng B., 2021, 2021 CIE INT C RAD R, P1293, DOI [10.1109/Radar53847.2021.10027876, DOI 10.1109/RADAR53847.2021.10027876]

[7]

Dooraki AR, 2020, INT C CONTR AUTOMAT, P161, DOI [10.23919/iccas50221.2020.9268270, 10.23919/ICCAS50221.2020.9268270]

[8] Design, Modeling and Control of a Novel Morphing Quadrotor [J].

Hu, Dada ;

Pei, Zhongcai ;

Shi, Jia ;

Tang, Zhiyong .

IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (04) :8013-8020

[9] A Review of Quadrotor Unmanned Aerial Vehicles: Applications, Architectural Design and Control Algorithms [J].

Idrissi, Moad ;

Salami, Mohammad ;

Annaz, Fawaz .

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2022, 104 (02)

[10] Data-Driven LightGBM Controller for Robotic Manipulator [J].

Mahayana, Dimitri .

IEEE ACCESS, 2024, 12 :40883-40893

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