细胞培养的无模型自适应预测控制:脱环境动态和补偿干扰
Muhang Li1, Ran Tang1, ZiYao Liao1
1Center of Ultra-precision Optoelectronic Instrument engineering, Harbin Institute of Technology, Harbin 150080, China; Key Lab of Ultra-precision Intelligent Instrumentation (Harbin Institute of Technology), Ministry of Industry and Information Technology, Harbin 150080, China.
ISA transactions
|February 17, 2026
概括
这项研究引入了生物反应器的新型自适应控制方法,改善溶解氧和pH调节. 这种方法提高了系统稳定性和干扰排斥,以更好地控制生物过程.
科学领域:
- 生物技术是生物技术.
- 控制工程 控制工程 控制工程
- 工艺系统工程 工艺系统工程
背景情况:
- 生物反应器控制系统与合变量,参数变化和干扰作斗争.
- 精确调节溶解氧 (DO) 和pH对于生物过程效率至关重要.
研究的目的:
- 开发一种无动态干扰补偿模型的自适应预测控制方法.
- 提高生物反应器系统的稳定性和可控性.
主要方法:
- 使用输入-输出数据建立了一个动态线性化模型.
- 制定了一种具有适应性,时间变化的控制收益的控制方法.
- 为DO和pH误差特征设计了在线自适应性学习机制.
主要成果:
- 提出的方法证明了优越的干扰排斥能力.
- 利亚普诺夫分析证实了统一的最终边界追踪错误.
- 模拟和实验验证了增强的系统稳定性和可控性.
结论:
- 新的自适应控制方法有效地解决了生物反应器监管方面的挑战.
- 这种方法显著提高了生物反应器系统的性能.
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