 The  proposed approach is more general than existing methods as it is able to handle unmatched uncertainties while only requiring the system be nominally contracting in closed-loop. Additionally, it can be used with learned feedback policies that are known to be contracting in some metric , facilitating transfer learning and bridging the sim2real gap.
<meaning-changed>  The  proposed approach is more general than existing methods as it is able to handle unmatched uncertainties while only requiring the system be nominally contracting in closed-loop. Additionally, it can be used with learned feedback policies that are known to be contracting in some metric , facilitating transfer learning and bridging the sim2real gap.
 The proposed approach is more general than existing methods as the uncertainties can be unmatched and the system only needs to be stabilizable. The developed algorithm can be combined with learned feedback policies that are known to be contracting in some metric , facilitating transfer learning and bridging the sim2real gap.