posted on 2003-01-01, 00:00authored byJun Morimoto, Christopher G. Atkeson
We developed a robust control policy design method in high-dimensional
state space by using differential dynamic programming with a minimax
criterion. As an example, we applied our method to a simulated five link
biped robot. The results show lower joint torques from the optimal control
policy compared to a hand-tuned PD servo controller. Results also
show that the simulated biped robot can successfully walk with unknown
disturbances that cause controllers generated by standard differential dynamic
programming and the hand-tuned PD servo to fail. Learning to
compensate for modeling error and previously unknown disturbances in
conjunction with robust control design is also demonstrated.