Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system.
Ioannis ProimadisYorick BroensRoland TóthHans ButlerPublished in: CoRR (2021)
Keyphrases
- steady state
- feed forward
- recurrent networks
- neural nets
- markov chain
- biologically plausible
- operating conditions
- state dependent
- error back propagation
- feedback loop
- queueing networks
- adaptive control
- learning algorithm
- control method
- recurrent neural networks
- special case
- reinforcement learning
- machine learning
- neural network