E-resources
-
Holmes, Grant; Chowdhury, Mozammal; McKinnis, Aaron; Keshmiri, Shawn
2022 International Conference on Unmanned Aircraft Systems (ICUAS), 2022-June-21Conference Proceeding
Vertical take-off and landing (VTOL) aircraft leverage the performance and efficiency of fixed-wing aircraft with the operational flexibility of rotary-wing aircraft. However, their complex dynamics and the inherent multi-mode of operation often make sufficiently robust controller design difficult, time consuming, and expensive. Transitioning between flight modes (e.g. vertical takeoff to cruise or cruise to landing) risks instability, oscillations, and high-G maneuvers. These challenges have been traditionally solved by relying on multi-modal PID design patterns and gain scheduling, necessitating the development of a different controller for each flight mode. Modern VTOL flight controller methods (e.g. Model Predictive Control) are often heavily model dependent and lack robustness to large uncertainties in the aircraft dynamic model. Such dependency eliminates any opportunity for flight controller to be transferable between different aircraft platforms without labor intensive practices. This paper presents simulation results of a deep learning based model-agnostic quad mode VTOL controller that is trained and optimized with the Proximal Policy Optimization (PPO) algorithm in simulation. Our controller is fully policy based rather than dynamic model dependent (e.g. LQR, H2, MPC, etc.) and thus is fully transferable between models without any retraining. Flight controller performance and robustness against perturbation is shown through a rigorous test suite that leverages data generated from real flight tests and the Dryden wind turbulence model.
![loading ... loading ...](themes/default/img/ajax-loading.gif)
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year | Impact factor | Edition | Category | Classification | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
Database name | Field | Year |
---|
Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.