https://github.com/baggepinnen/iterativelearningcontrol2.jl

Like reinforcement learning, but it works in practice

https://github.com/baggepinnen/iterativelearningcontrol2.jl

Science Score: 13.0%

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  • Scientific vocabulary similarity
    Low similarity (8.6%) to scientific vocabulary

Keywords

adaptive-control control-systems controls controlsystems feedback-systems optimal-control reinforcement-learning
Last synced: 5 months ago · JSON representation

Repository

Like reinforcement learning, but it works in practice

Basic Info
  • Host: GitHub
  • Owner: baggepinnen
  • License: mit
  • Language: Julia
  • Default Branch: main
  • Homepage:
  • Size: 11.4 MB
Statistics
  • Stars: 9
  • Watchers: 2
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Topics
adaptive-control control-systems controls controlsystems feedback-systems optimal-control reinforcement-learning
Created about 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

IterativeLearningControl2

Build Status Documentation, latest

Iterative-Learning Control (ILC) for linear and nonlinear systems.

What is ILC?

ILC can be thought of as either - a simple reinforcement-learning (RL) strategy, or - a method to solve open-loop optimal control problems.

ILC is suitable in situations where a repetitive task is to be performed multiple times, and disturbances acting on the system are also repetitive and predictable but may be unknown. Multiple versions of ILC exists, of which we support a few that are listed below. When ILC iterations are performed by running experiments on a physical system, ILC resembles episode-based reinforcement learning (or adaptive control), while if a model is used to simulate the experiments, we can instead think of ILC as a way to solve optimal control problems (trajectory optimization).

See the documentation for more details.

Owner

  • Name: Fredrik Bagge Carlson
  • Login: baggepinnen
  • Kind: user
  • Location: Lund, Sweden

Control systems, system identification, signal processing and machine learning

GitHub Events

Total
  • Delete event: 5
  • Push event: 4
  • Pull request event: 2
  • Create event: 21
Last Year
  • Delete event: 5
  • Push event: 4
  • Pull request event: 2
  • Create event: 21

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 37
  • Total Committers: 1
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 37
  • Committers: 1
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Fredrik Bagge Carlson b****n@g****m 37

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 1
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 39 minutes
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 39 minutes
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
  • baggepinnen (2)
Top Labels
Issue Labels
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Dependencies

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.github/workflows/CompatHelper.yml actions
.github/workflows/TagBot.yml actions
  • JuliaRegistries/TagBot v1 composite
.github/workflows/docs.yml actions
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