Meta-Adaptive Nonlinear Control: Theory and Algorithms
Authors: Guanya Shi, Kamyar Azizzadenesheli, Michael O'Connell, Soon-Jo Chung, Yisong Yue
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments show that OMAC significantly outperforms conventional adaptive control approaches which do not learn the shared representation, in inverted pendulum and 6-Do F drone control tasks under varying wind conditions1. |
| Researcher Affiliation | Academia | Caltech Purdue University {gshi,moc,sjchung,yyue}@caltech.edu, kamyar@purdue.edu |
| Pseudocode | Yes | Algorithm 1: Online Meta-Adaptive Control (OMAC) algorithm |
| Open Source Code | Yes | Code and video: https://github.com/GuanyaShi/Online-Meta-Adaptive-Control |
| Open Datasets | No | The paper describes experiments on simulated control tasks (inverted pendulum and 6-Do F quadrotor) using models, rather than relying on or providing access to publicly available datasets for training or evaluation. |
| Dataset Splits | No | The paper defines outer and inner iterations (N environments, T time steps) and uses Average Control Error (ACE) as a performance metric, but does not provide explicit train/validation/test dataset splits as it relies on simulated control environments. |
| Hardware Specification | No | The paper describes the experimental setup in terms of tasks (inverted pendulum, drone control) and controllers, but does not specify the hardware used to run these experiments (e.g., CPU/GPU models, memory). |
| Software Dependencies | No | The paper mentions algorithms and optimizers used (e.g., Adam optimizer, spectral normalization) but does not provide specific software dependencies with version numbers (e.g., 'PyTorch 1.9' or 'Python 3.8'). |
| Experiment Setup | Yes | For all methods, we randomly switch the environment (wind) c every 2 s. To make a fair comparison, except no-adapt or omniscient, all methods have the same learning rate for the inner-adapter A2 and the dimensions of ˆc are also same (dim(ˆc) = 20 for the pendulum and dim(ˆc) = 30 for the drone). |