TY - GEN
T1 - Design of Attitude Controller for Ducted Fan UAV Based on Improved Direct Adaptive Control Method
AU - Zhang, Hongyu
AU - Liu, Xiaodong
AU - Xu, Yong
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.
PY - 2023
Y1 - 2023
N2 - Ducted fan UAV system is a typical multi-channel coupled nonlinear system. To implement reliable control of it, the structure and mathematical model of UAV must first be clarified. After the system model is established, it needs to be linearized and converted into a state-space expression before the controller can be designed. Thinking about controller design, we select the Linear Quadratic Regulator (LQR) method as the basic controller at first. According to simulation analysis, it is found that its dynamic performance is excellent, but it cannot effectively fight against the influence of the external disturbance. So, we improved direct adaptive controller and combined it with Kalman filter. The simulation results show that the controller realizes the function of anti-disturbance, and improves the robustness of the system.
AB - Ducted fan UAV system is a typical multi-channel coupled nonlinear system. To implement reliable control of it, the structure and mathematical model of UAV must first be clarified. After the system model is established, it needs to be linearized and converted into a state-space expression before the controller can be designed. Thinking about controller design, we select the Linear Quadratic Regulator (LQR) method as the basic controller at first. According to simulation analysis, it is found that its dynamic performance is excellent, but it cannot effectively fight against the influence of the external disturbance. So, we improved direct adaptive controller and combined it with Kalman filter. The simulation results show that the controller realizes the function of anti-disturbance, and improves the robustness of the system.
KW - Direct Adaptive Control
KW - Ducted Fan UAV
KW - Kalman Filter
KW - LQR Control
UR - http://www.scopus.com/inward/record.url?scp=85174734072&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-6187-0_43
DO - 10.1007/978-981-99-6187-0_43
M3 - Conference contribution
AN - SCOPUS:85174734072
SN - 9789819961863
T3 - Lecture Notes in Electrical Engineering
SP - 427
EP - 436
BT - Proceedings of 2023 Chinese Intelligent Automation Conference
A2 - Deng, Zhidong
PB - Springer Science and Business Media Deutschland GmbH
T2 - Chinese Intelligent Automation Conference, CIAC 2023
Y2 - 2 October 2023 through 5 October 2023
ER -