Online Adaptive Compensation for Model Uncertainty Using Extreme Learning Machine-based Control Barrier Functions
Emanuel Munoz,Dvij Kalaria,Qin Lin,John M. Dolan,Emanuel Munoz,Dvij Kalaria,Qin Lin,John M. Dolan
A control barrier functions-based quadratic programming (CBF-QP) method has emerged as a controller synthesis tool to assure safety of autonomous systems owing to the appealing safe forward invariant set. However, the provable safety relies on a precisely described dynamic model, which is not always available in practice. Recent works leverage learning to compensate model uncertainty for a CBF con...
