发酵过程组分浓度控制和优化算法设计与实现毕业论文
2022-02-06 18:56:29
论文总字数:21629字
摘 要
随着发酵行业的逐年发展,发酵工业迫切需要对发酵的过程进行在线控制及优化。由于大部分的微生物发酵过程的内部机理都非常复杂,具有比较高的非线性、滞后性、时变性等,从而导致先进的优化控制策略难以对发酵过程进行在线优化控制,无法满足相关的控制性能指标。
本文在详细研究发酵过程控制系统现状的基础上,采用基于灰箱模型的建模方法,通过对丙酮酸发酵过程进行动力学分析,然后使用Matlab的Simulink工具对丙酮酸发酵过程进行模型的搭建。随后,通过对丙酮酸发酵过程进行详细研究,提出了一种针对丙酮酸发酵过程的优化控制策略,该优化控制策略相对于传统的分批控制的发酵方式有着明显的优势,能够较好的提高发酵过程的控制性能,从而提高发酵产物的产量。接下来,提出了一种基于粒子群算法的PID控制来对丙酮酸发酵过程进行优化。
最后,在本文所搭建的丙酮酸发酵过程模型的基础上,应用本文所提出的优化控制策略,对丙酮酸发酵过程进行优化控制,然后将得到的仿真数据进行分析比较,结果表明本文所提出的针对丙酮酸发酵过程的优化控制策略能够很好地对丙酮酸发酵过程的底物浓度进行控制,基于粒子群算法的PID控制在优化控制策略中能很好地发挥其优化作用,采用了优化控制策略后发酵产物的产量、原料的利用率、菌体的最大浓度等都有明显的增加。
关键词:生物发酵 优化控制 粒子群算法
Design of fermentation component concentration control and optimization algorithm
Abstract
With the development of fermentation industry, it is urgent to control and optimize the fermentation process online.As most of the internal mechanism of microbial fermentation process is very complex, has the high nonlinearity, hysteresis, time-varying, etc. which can lead to advanced optimization control strategy is difficult to on-line optimization control of fermentation process, can not meet the control related performance metrics.
Fermentation process control system based on the detailed research status quo, on the basis of the modeling method based on mechanism, through the study of the dynamics analysis of pyruvate fermentation process, and then use Matlab Simulink tool of pyruvate fermentation process in construction of the model.Then, through the study of the detailed study of pyruvate fermentation process, this paper proposes a for pyruvate fermentation process optimization control strategy, the optimal control strategy compared with traditional way of batch control of fermentation has obvious advantages, can better improve the control performance of fermentation process, so as to improve the production of fermentation product.Next, in the full study under the premise of particle swarm optimization (pso) algorithm and PID algorithm, this paper proposes a PID control based on particle swarm algorithm to optimize the pyruvate fermentation process, the realization of the optimal control strategy to prepare.
Finally, the optimal control strategy proposed in this paper is adopted to optimize the control of pyruvate fermentation process.And then to set up by the Matlab simulation pyruvate fermentation process model, data will be analyzed, the results show that the presented for pyruvate fermentation process optimization control strategy can effectively the substrate concentration of pyruvate fermentation process control, PID control based on particle swarm algorithm can well satisfy the control requirements, using the optimal control strategy after the production of fermentation product, the utilization rate of raw materials, such as the largest concentrations of bacteria have obvious increase.
Key words: biological fermentation optimization control particle swarm optimization algorithm
目录
摘要 I
Abstract II
第一章 绪论 1
1.1课题研究背景和现状 1
1.2葡萄糖浓度检测方法概述 1
1.3发酵过程组分浓度控制技术现状 2
1.3.1基于嵌入式单片机控制器的发酵测控系统 3
1.3.2基于工控机的发酵测控系统 3
1.3.3基于现场总线技术的发酵测控系统 3
1.3.4 基于集散控制系统的发酵测控系统 4
1.4主要研究内容 4
第二章 发酵控制系统建模方法研究 5
2.1 机理建模 5
2.2 基于灰箱模型的发酵过程建模 5
2.3 丙酮酸发酵过程建模 7
第三章 发酵系统控制策略研究与优化 11
3.1 发酵方式控制 11
3.2 温度控制 12
3.2.1 最适温度选择 12
3.2.2 发酵罐温度控制模型 12
3.3 pH控制 14
3.4 优化控制策略 15
第四章 优化算法研究 17
4.1粒子群算法 17
4.2粒子群算法的数学描述 17
4.3带惯性权重的粒子群优化算法 18
4.4 粒子群优化算法流程图 19
4.5基于PSO算法的PID控制 19
第五章 实验结果与结论展望 23
5.1 实验结果 23
5.2结论 27
5.3展望 28
参考文献 29
致谢 32
附录一 PSO算法代码 33
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