基于静态输出反的分布式稳健模型,用于过程网络中的并行系统的预测控制
Shuzhan Zhang1, Dongya Zhao1, Sarah K Spurgeon2
1Department of Chemical Equipment and Control Engineering, College of Chemical Engineering, China University of Petroleum (East China), Qingdao, China.
ISA transactions
|August 7, 2025
概括
一个新的分布式稳健模型预测控制策略解决了并行系统中未测量的状态. 该方法使用静态输出反和线性矩阵不等式,证明过程网络的输入到状态稳定性.
科学领域:
- 控制系统工程 控制系统工程
- 化学过程网络 化学过程网络
- 强大的控制理论.
背景情况:
- 平行系统在过程网络中很常见,但由于合和约束,它们存在挑战.
- 现有的控制策略通常在这种架构中与未测量的状态作斗争.
- 强大的模型预测控制 (MPC) 是复杂系统的强大框架.
研究的目的:
- 为具有未测量状态的并行系统开发一个分布式稳健模型预测控制策略.
- 解决平行系统架构中固有的合和约束.
- 确保稳定性和验证拟议的控制方法.
主要方法:
- 在控制器设计中使用静态输出反框架.
- 制定了控制问题作为一个非凸的优化问题.
- 使用线性矩阵不等式 (LMIs) 解决了非凸问题.
- 闭环系统的输入到状态 (ISS) 稳定性的证明.
主要成果:
- 成功设计了用于并行系统的分布式强大的MPC控制器.
- 控制器有效地处理未测量的状态和系统约束.
- 线性矩阵不等式为非凸的控制问题提供了可行的解决方案.
- 对受控系统的输入到状态稳定性被严格证明.
结论:
- 提出的分布式强大的MPC策略对于具有未测量状态的并行系统是有效的.
- 基于LMI的方法提供了一种系统的方法,用于为这些系统设计强大的控制器.
- 通过模拟和实验的验证证实了该方法的实际适用性.
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