experiments/ 收集了与主笔记对应的可复现实验入口。所有脚本默认在仓库根目录运行，Python 和 MATLAB 版本尽量指向同一组图像与数值结果。
| 分组 | 目录 | 对应笔记 | 主入口 | 说明 |
|---|---|---|---|---|
foundations |
01_state_space_modeling | 01 建模基础 | python experiments/foundations/01_state_space_modeling/generate_results.py |
状态空间建模、平衡点与输入响应 |
foundations |
02_lti_stability | 02 稳定性 | python experiments/foundations/02_lti_stability/generate_results.py |
特征值判据与 Lyapunov 判据的二维验证 |
foundations |
03_controllability_observability | 03 可控可观 | python experiments/foundations/03_controllability_observability/generate_results.py |
最小能量状态转移与状态重构 |
foundations |
04_lti_control | 04 控制 | python experiments/foundations/04_lti_control/generate_results.py |
开环、状态反馈和输出反馈响应 |
foundations |
05_observer_and_separation | 05 观测器 | python experiments/foundations/05_observer_and_separation/generate_results.py |
状态估计、误差收敛与分离设计 |
foundations |
06_optimal_control | 06 最优控制 | python experiments/foundations/06_optimal_control/generate_results.py |
连续时间 LQR 与权重折中 |
foundations |
07_tracking_and_disturbance_rejection | 07 跟踪抗扰 | python experiments/foundations/07_tracking_and_disturbance_rejection/generate_results.py |
参考跟踪、积分器与常值扰动抑制 |
foundations |
08_periodic_sampling_control | 08 周期采样控制 | python experiments/foundations/08_periodic_sampling_control/generate_results.py |
采样状态与零阶保持控制输入 |
robust_control |
09_robust_control | 09 鲁棒控制 | python experiments/robust_control/09_robust_control/generate_results.py |
区间不确定系统与频域性能估计 |
nonlinear_and_delay |
10_delay_neural_network_stability | 10 时滞神经网络稳定性 | python experiments/nonlinear_and_delay/10_delay_neural_network_stability/generate_results.py |
不同时滞下的稳定性和收敛时间 |
nonlinear_and_delay |
11_chaotic_sync_and_image_encryption | 11 同步与图像加密 | python experiments/nonlinear_and_delay/11_chaotic_sync_and_image_encryption/generate_results.py |
混沌同步、图像加密和统计分析 |
Python 依赖见 requirements.txt。常用入口如下：
pip install -r requirements.txt
python experiments/foundations/01_state_space_modeling/generate_results.py
python experiments/foundations/06_optimal_control/generate_results.py
matlab -batch "run('experiments/nonlinear_and_delay/11_chaotic_sync_and_image_encryption/generate_results.m')"运行完成后，图像会写入 figures/，数值结果会写入 generated/。