IEEE Trans Neural Netw Learn Syst
May 2024
Flexible robots (FRs) are generally designed to be lightweight to achieve rapid motion. However, accompanying vibrations and modeling errors influence tracking control, especially in situations involving reference signal loss. This article develops a two-time scale primal-dual inverse reinforcement learning (PD-IRL) framework for FRs to perform tracking tasks with incomplete reference signals.
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