Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control strategy, which has shown robustness against model uncertainties on various aerospace platforms. The sensor-based nature of the method brings attractive properties, which has made it popular in the last decade. INDI globally linearizes the system by making use of control input and state derivative feedback. Despite the enhanced robustness against parametric system uncertainties compared to traditional NDI, mitigating the effects of time lag between the control input and state derivative feedback paths represents an important challenge for INDI. Past research has shown that this can be addressed by synchronizing these feedback signals, although the method remains vulnerable to unexpected measurement delays. This paper proposes a hybrid INDI approach based on complementary filtering to further mitigate this robustness issue. The approach fuses the system model and sensor measurement to generate an estimate of the angular acceleration of the system. The estimation responds rapidly to the system input thanks to the on-board model, whereas adequate accuracy in the low-to-medium frequency range is maintained by the sensor measurement. The control law is found to retain good performance in case of model mismatches and measurement delays. To demonstrate the method, a hybrid INDI-based attitude control law is designed for a nonlinear F-16 aircraft model. The robustness properties of the resulting control system are analyzed using time-domain simulations.
|Title of host publication||AIAA SCITECH 2022 Forum|
|Number of pages||18|
|Publication status||Published - 2022|
|Event||AIAA SCITECH 2022 Forum - virtual event|
Duration: 3 Jan 2022 → 7 Jan 2022
|Conference||AIAA SCITECH 2022 Forum|
|Period||3/01/22 → 7/01/22|