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.
|Journal||IOP Conference Series: Materials Science and Engineering|
|Publication status||Published - 2017 Mar 23|
|Event||2016 2nd International Conference on Mechanical and Aeronautical Engineering, ICMAE 2016 - Hong Kong, Hong Kong|
Duration: 2016 Dec 28 → 2016 Dec 30
All Science Journal Classification (ASJC) codes
- Materials Science(all)