AI RESEARCH
Temporal Attention for Adaptive Control of Euler-Lagrange Systems with Unobservable Memory
arXiv CS.LG
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ArXi:2605.06877v1 Announce Type: new Adaptive control of Euler-Lagrange systems is challenging when friction is governed by a finite-horizon internal state that is not directly observable from joint measurements. In this setting, the measured closed-loop state is no longer Markovian, and standard certainty-equivalence adaptive laws may lose their convergence guarantees. The paper proposes a meta-control architecture in which the gains of a computed-torque controller are generated by a self-attention block processing a short window of recent motion history.