TY - JOUR
T1 - System Identification and Control Design of an Unmanned Helicopter Using a PI-MPC Controller
AU - Le Tri, Quang
AU - Lai, Ying Chih
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/3/23
Y1 - 2017/3/23
N2 - This paper presents the study of the system identification and controller design for an unmanned helicopter using the integration of Proportional Integral (PI) and Model Predictive Control (MPC). Since the dynamic model of a helicopter is highly nonlinear and contains many uncertainties, the system identification and control are challenging and complicated. To accelerate the development, the autonomous flight and trajectory tracking of an unmanned helicopter, this study first setup a software simulation environment of the helicopter using the X-Plane flight simulator. The prediction-error minimization (PEM) and subspace methods were applied in this study to identify the dynamic model of the interested flight trim conditions. The lateral, longitudinal, heave, and yaw dynamic models were predicted by using the System Identification Toolbox of MATLAB. To enhance the stability and eliminate the uncertainty of the control system, the Integration of Proportional Integral (PI) and MPC were introduced. The developed control system was then applied to perform the trajectory tracking of a helicopter. The simulation results show that the performance of the proposed approach can track the desired trajectory.
AB - This paper presents the study of the system identification and controller design for an unmanned helicopter using the integration of Proportional Integral (PI) and Model Predictive Control (MPC). Since the dynamic model of a helicopter is highly nonlinear and contains many uncertainties, the system identification and control are challenging and complicated. To accelerate the development, the autonomous flight and trajectory tracking of an unmanned helicopter, this study first setup a software simulation environment of the helicopter using the X-Plane flight simulator. The prediction-error minimization (PEM) and subspace methods were applied in this study to identify the dynamic model of the interested flight trim conditions. The lateral, longitudinal, heave, and yaw dynamic models were predicted by using the System Identification Toolbox of MATLAB. To enhance the stability and eliminate the uncertainty of the control system, the Integration of Proportional Integral (PI) and MPC were introduced. The developed control system was then applied to perform the trajectory tracking of a helicopter. The simulation results show that the performance of the proposed approach can track the desired trajectory.
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U2 - 10.1088/1757-899X/187/1/012020
DO - 10.1088/1757-899X/187/1/012020
M3 - Conference article
AN - SCOPUS:85017409707
VL - 187
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
SN - 1757-8981
IS - 1
M1 - 012020
T2 - 2016 2nd International Conference on Mechanical and Aeronautical Engineering, ICMAE 2016
Y2 - 28 December 2016 through 30 December 2016
ER -