基于神经网络的自适应式去中心化安全控制,用于具有时间延迟的相互连接非线性系统.
Chong Liu1, Leiming Wang2, Zhousheng Chu2
1College of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, Shaanxi, PR China; School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore.
ISA transactions
|July 26, 2025
概括
本研究介绍了一种使用适应式动态编程的分散式动态事件触发控制器,用于具有时间延迟和输入约束的非线性系统. 该方法确保了系统稳定性和高效的控制,即使有非零平衡点.
科学领域:
- 控制系统工程 控制系统工程
- 非线性动力学是一种非线性动力学.
- 人工智能的人工智能
背景情况:
- 互连的非线性系统具有时间延迟和不对称的输入约束,这给安全控制带来了重大挑战.
- 现有的控制方法通常假定零平衡点,限制它们对更广泛的系统动态的适用性.
- 分散控制策略对于高效管理大规模互联系统至关重要.
研究的目的:
- 为相互连接的非线性系统开发一个分散的动态事件触发 (DET) 控制器,具有非零平衡点,时间延迟和不对称的输入约束.
- 将一个受约束的控制问题转换为一个不受约束的最佳控制问题 (OCP),使用一个包含折扣因子,屏障函数和Lyapunov-Krasovskii (L-K) 函数的成本函数.
- 为了解决基于自适应动态编程 (ADP) 的控制中的计算效率和持续激发的需求.
主要方法:
- 对于具有非零平衡点,时间延迟和约束的系统,构建了一个新的成本函数.
- 一个基于事件的汉密尔顿-雅各比-贝尔曼 (HJB) 方程是用ADP来制定和解决的.
- 为了提高计算效率,提出了一个分散的动态事件触发 (DET) 机制.
- 神经网络 (NN) 权重通过梯度下降和体验重播 (ER) 技术进行优化,消除了对连续系统激发的需求.
主要成果:
- 拟议的DET控制器有效地处理具有非零平衡点,时间延迟和不对称输入约束的相互连接的非线性系统.
- 适应式动态编程方法与ER相结合,可确保高效的学习和控制.
- 理论分析证实了系统状态和NN权重的统一终极边界性 (UUB),同时也排除了Zeno行为.
- 该方法的有效性通过一个实际的弹摆形系统示例来证明.
结论:
- 开发的分散式动态事件触发自适应动态编程控制器为复杂的非线性系统提供了强大而高效的解决方案.
- 该方法成功地解决了与非零平衡点,时间延迟和输入约束相关的挑战.
- 这些发现有助于推进大规模互联系统的安全控制方法.
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