Control augmentation systems based on Incremental Nonlinear Dynamic Inversion (INDI) are able to provide high-performance nonlinear control without the need for a model of the complete system. Considering a pitch rate control law for a fixed-wing aircraft, only a model for the elevator control effectiveness (CE) and sensor feedback of the pitch acceleration are required for the model inversion. Despite the increased robustness against model error due to the decreased model dependency, control laws based on INDI could still show performance variation when the on-board CE model deviates from the actual CE. This thesis will put this in the context of the control performance of high-performance aircraft. Furthermore, multiple adaptive INDI control techniques are investigated as possible solutions. This study revealed that adaptive control based on Least-Mean-Square (LMS) parameter estimation has the most potential. A second analysis using handling quality and stability (HQ&S) requirements showed that this approach is able to decrease variation in the HQ&S as well. However, the results also show that HQ&S variation for large centre of gravity shifts could not always be fully mitigated by adaptive control as it is possible that the time-scale separation assumption becomes impaired.