Learning-based feedforward augmentation for steady state rejection of residual dynamics on a nanometer-accurate planar actuator system.
Ioannis ProimadisYorick BroensRoland TóthHans ButlerPublished in: L4DC (2021)
Keyphrases
- steady state
- feed forward
- recurrent networks
- neural nets
- markov chain
- dynamical systems
- back propagation
- explicit expressions
- recurrent neural networks
- learning algorithm
- artificial neural networks
- search algorithm
- reinforcement learning
- state dependent
- feedback loop
- biologically plausible
- adaptive neural
- error back propagation
- machine learning