Phase-indexed ILC for control of underactuated walking robots

We propose a method for learning the nominal control input for virtual-constraints-based walking robots. The key problem in applying iterative learning control (ILC) to these systems is that the iterations are only approximately periodic. We develop a modified form of ILC that indexes previous itera...

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Bibliographic Details
Published in2015 IEEE Conference on Control Applications (CCA) pp. 1467 - 1472
Main Authors Kong, Felix H., Boudali, A. Mounir, Manchester, Ian R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2015
Subjects
Dynamics
Feedforward neural networks
Legged locomotion
PD control
Robot kinematics
Torque
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Summary:We propose a method for learning the nominal control input for virtual-constraints-based walking robots. The key problem in applying iterative learning control (ILC) to these systems is that the iterations are only approximately periodic. We develop a modified form of ILC that indexes previous iterations by a phase variable (a function of the state variables) rather than time. We show in experiments that the proposed method outperforms time-indexed ILC and a hybrid "resetting" form of ILC in terms of tracking error reduction and stability.
ISSN:1085-1992
2576-3210
DOI:10.1109/CCA.2015.7320818