Adaptive Nonlinear Tracking for Robotic Walking

This article deals with online adaptation of control strategy for nonlinear tracking of a walking like motion of bipedal robot. Adaptation of the control rule is done according to results of online parameter estimation. Parameter estimation was realized by an extended Kalman filter due to recursive nature of the estimation problem and abundant a priori information. Proposed estimation strategy yields at least three advantages. By utilization of extensive knowledge about the system in consideration a multi-variable estimation problem was reduced to estimation problem involving one parameter only. A heavy computation burden required for recomputation of reference trajectory and feed-forward controller is removed. This approach can also be used to eliminate the modeling mismatch. A practical situation when a robot has to carry a load of an unknown weight is demonstrated.