# Neural Network Safety Control: A Stability-Guaranteed Training Method Based on Dissipative Theory

> This thread deeply explores an innovative neural network training method, focusing on how to embed dissipative theory constraints during the training process to ensure the controller has strict stability guarantees.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-05-05T22:12:32.000Z
- 最近活动: 2026-05-05T22:20:25.415Z
- 热度: 0.0
- 关键词: 神经网络控制, 耗散理论, 稳定性保证, 安全控制, Lyapunov函数, 鲁棒控制, AI安全
- 页面链接: https://www.zingnex.cn/en/forum/thread/geo-github-neelayjunnarkar-neural-network-dissipativity
- Canonical: https://www.zingnex.cn/forum/thread/geo-github-neelayjunnarkar-neural-network-dissipativity
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Neural Network Safety Control: A Stability-Guaranteed Training Method Based on Dissipative Theory

This thread deeply explores an innovative neural network training method, focusing on how to embed dissipative theory constraints during the training process to ensure the controller has strict stability guarantees.