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| 1 | +# Changelog |
| 2 | + |
| 3 | +All notable changes to this project will be documented in this file. |
| 4 | + |
| 5 | +The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), |
| 6 | +and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). |
| 7 | + |
| 8 | +## [1.0.0] - 2025-07-25 |
| 9 | + |
| 10 | +### Added |
| 11 | +- Initial release of SRF FC RL (Superconducting RadioFrequency cavity Frequency Control by Reinforcement Learning) |
| 12 | +- PPO-based reinforcement learning agent for RF cavity frequency control |
| 13 | +- Physics-based RF cavity environment simulation with: |
| 14 | + - 4D observation space (cavity voltage amplitude, reflected voltage amplitude, cavity voltage phase, frequency detuning) |
| 15 | + - 1D continuous action space (piezo control signal) |
| 16 | + - Realistic cavity dynamics including mechanical modes and beam loading |
| 17 | +- Real-time control interfaces: |
| 18 | + - Command line interface with keyboard controls |
| 19 | + - GUI interface with real-time plotting and interactive controls |
| 20 | +- Comprehensive configuration system through `configs/config.py` |
| 21 | +- Training and evaluation scripts with: |
| 22 | + - Tensorboard logging support |
| 23 | + - Early stopping mechanism |
| 24 | + - Model checkpointing |
| 25 | + - Performance visualization |
| 26 | +- Batch files for Windows users for easy operation |
| 27 | +- Complete documentation: |
| 28 | + - Detailed README.md with installation and usage instructions |
| 29 | + - Comprehensive user manual in ReStructuredText format |
| 30 | + - Contributing guidelines |
| 31 | +- GitHub Actions CI/CD pipeline for automated testing |
| 32 | +- Cross-platform support (Windows, Linux, macOS) |
| 33 | +- MIT License |
| 34 | + |
| 35 | +### Features |
| 36 | +- **Environment**: Physics-based RF cavity simulation |
| 37 | +- **Algorithm**: PPO (Proximal Policy Optimization) with optimized hyperparameters |
| 38 | +- **Real-time Control**: Both command line and GUI interfaces |
| 39 | +- **Monitoring**: Tensorboard integration for training visualization |
| 40 | +- **Configuration**: Highly configurable through centralized config file |
| 41 | +- **Platforms**: Windows, Linux, and macOS support |
| 42 | +- **Python**: Compatible with Python 3.8+ |
| 43 | + |
| 44 | +### Dependencies |
| 45 | +- gymnasium >= 0.29.0 |
| 46 | +- stable-baselines3 >= 2.0.0 |
| 47 | +- torch >= 1.13.0 |
| 48 | +- numpy >= 1.21.0 |
| 49 | +- matplotlib >= 3.5.0 |
| 50 | +- scipy >= 1.7.0 |
| 51 | +- tensorboard >= 2.8.0 |
| 52 | + |
| 53 | +### Known Issues |
| 54 | +- LLRF libraries need to be installed separately (platform-specific) |
| 55 | +- Large memory usage during training with default settings |
| 56 | +- GUI interface may require additional setup on some Linux distributions |
| 57 | + |
| 58 | +### Performance |
| 59 | +- Training typically achieves < 1 kHz mean absolute frequency detuning |
| 60 | +- Optimized for CPU training (recommended over GPU for this use case) |
| 61 | +- Supports parallel environments for faster training |
| 62 | + |
| 63 | +## [Unreleased] |
| 64 | + |
| 65 | +### Planned Features |
| 66 | +- [ ] Noise models for more realistic simulation |
| 67 | +- [ ] Multi-objective optimization (stability + efficiency) |
| 68 | +- [ ] Support for different cavity configurations |
| 69 | +- [ ] Transfer learning between different cavities |
| 70 | +- [ ] Web-based monitoring dashboard |
| 71 | +- [ ] Advanced control algorithms comparison (PID, LQR, MPC) |
| 72 | +- [ ] Distributed control for multiple cavities |
| 73 | +- [ ] Fault detection and diagnosis capabilities |
| 74 | + |
| 75 | +--- |
| 76 | + |
| 77 | +For detailed information about each version, see the [releases page](https://github.com/iuming/SRF_FC_RL/releases). |
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