| Abstract |
This paper presents an efficient impedance control scheme for legs of walking machines interacting
with an uncertain environment and proposes an impact control based on neural system. The proposed
method combines the technique of the indirect MRAC (Model Reference Adaptive Control) with the
properties of self-learning neural nets. Present research is focused on the optimisation of motion of
mechanical systems with constraints on the contact with the environment in order to cover given
contact quality requirements (minimal tendency to oscillations, contact stability, damping, contact
force limitation). |
