Control design for a helicopter is a challenging problem because of its non-affine inputs, complicated dynamics and it is an under-actuated system. To solve a control problem of the helicopter under model uncertainties and disturbance present environments, an Explicit Nonlinear Model Predictive Control (ENMPC), a dynamic inversion and an Extended High-Gain Observers (EHGO) are combined in a multi-time-scale fashion. The multi-time scaled structrue and the ENMPC provides the framework of the control design, the dynamic inversion deals with nonaffine control inputs, and the EHGO estimates the unmeasured states and uncertainties. In addition, a discretization scheme using the saturation and adding low pass filters to the control inputs is presented. Finally, the numerical simulation of a fixed sampling period has been carried out to demonstrate the validity of the proposed multi-time-scale control design and the discretization scheme.
|Title of host publication||Rapid Fire Interactive Presentations|
|Subtitle of host publication||Advances in Control Systems; Advances in Robotics and Mechatronics; Automotive and Transportation Systems; Motion Planning and Trajectory Tracking; Soft Mechatronic Actuators and Sensors; Unmanned Ground and Aerial Vehicles|
|Publisher||American Society of Mechanical Engineers (ASME)|
|Publication status||Published - 2019|
|Event||ASME 2019 Dynamic Systems and Control Conference, DSCC 2019 - Park City, United States|
Duration: 2019 Oct 8 → 2019 Oct 11
|Name||ASME 2019 Dynamic Systems and Control Conference, DSCC 2019|
|Conference||ASME 2019 Dynamic Systems and Control Conference, DSCC 2019|
|Period||19/10/8 → 19/10/11|
Bibliographical noteFunding Information:
This work has been supported by the Mid-career Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2018R1A2B6008063).
© 2019 ASME.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Mechanical Engineering
- Industrial and Manufacturing Engineering