摘 要

温度作为影响生物发酵过程的一个重要因素，关系着生物发酵能不能获得最好的发酵效果，因此，生物发酵罐需要很高的温度控制精度。当前，在生物发酵罐温度控制设计中，传统PID（Proportion Integration Differentiation）控制器应用最广泛，其拥有操作简单和适用性强的特点，但是其参数整定比较复杂，需要大量的参数调试，如果被控对象的数学模型不能精确建立，根据传统PID设计的控制系统的所得控制参数将无法保证温度控制系统的控制精度。

针对生物发酵罐温度控制具有一阶惯性、非线性、时变性等特性，本文设计了一种基于模糊PID参数自整定的生物发酵罐温度控制系统，实现了对PID参数的实时调整，并进行了对温控系统的软硬件开发和模糊PID控制算法的设计。硬件方面采用STC89C52单片机，设计了包括系统电源部分、温度采集部分、制冷加热部分、显示部分和遥控部分。软件方面采用模块化设计，具有良好的通用性、抗干扰强等优点。

实验表明，模糊PID控制方法比传统PID控制方法稳定快，超调小，温度控制精度高，能更好的达到实验要求。

关键词：温度控制，模糊PID，控制精度，非线性，超调

Intelligent temperature control in biological fermentation process

Abstract

Temperature is an important factor affecting the biological fermentation process,It is related to whether biological fermentation can obtain the best fermentation effect,so,Biological fermentation tanks require high temperature control accuracy.The current,In the design of temperature control of biological fermentation tank,Traditional PID (Proportion Integration Differentiation) controller has the most extensive application,It has the characteristics of simple operation and strong applicability,But its parameter setting is more complex,A lot of parameter debugging is required,If the mathematical model of the controlled object cannot be built accurately,According to the traditional PID design of the control system control parameters will not be able to ensure the temperature control system control precision.

The temperature control of biological fermenter has the characteristics of inertia, nonlinearity and time-varying,In this paper, a biological fermentation tank temperature control system based on fuzzy PID parameter self-tuning is designed,The real-time adjustment of PID parameters is realized,The software and hardware of the temperature control system are developed and the fuzzy PID control algorithm is designed.In terms of hardware, STC89C52 single-chip microcomputer is adopted, including the system power supply, temperature acquisition, refrigeration and heating, display and remote control.The modular design of the software has the advantages of good universality and strong anti-interference.

Experiments show that,Compared with the traditional PID control method, the fuzzy PID control method has the advantages of stability, small overshoot and high precision of temperature control,Can better meet the experimental requirements.

Key words：Temperature control, fuzzy PID, control accuracy, nonlinear, overshoot

目 录

引言………………………………………………………………………………………1

1 绪论………………………………………………………………………………………2

1.1 课题研究背景和意义………………………………………………………………2

1.2 国内外生物发酵研究现状……………………………………………………………………2

1.3 温度控制系统中智能控制算法的应用………………………………………………………3

1.4 课题的设计目标主要内容……………………………………………………………………4

2 系统总体设计方案……………………………………………………………………………5

2.1 系统性能要求……………………………………………………………5

2.2 模糊控制器设计………………………………………………………………5

2.3 系统硬件方案设计………………………………………………………………5

2.4 系统软件方案设计………………………………………………………………6

3 模糊PID参数自整定控制算法研究……………………………………………………………………7

3.1 PID控制…………………………………………………………………………7

3.1.1 传统PID控制原理………………………………………………………………7

3.1.2 PID参数整定……………………………………………………………………8

3.1.3 PID控制的局限性和发展………………………………………………………9

3.2 模糊PID控制…………………………………………………………………………9

3.2.1 模糊PID控制原理………………………………………………………………10

3.2.2 模糊PID控制的基本分类………………………………………………………10

3.2.3 模糊PID控制规则………………………………………………………………10

3.3 本章小结……………………………………………………………………………11

4 基于模糊PID控制算法的生物发酵罐的温度控制…………………………………………12

4.1 参数自整定控制设计……………………………………………………………………12

4.1.1 输入输出的模糊化………………………………………………………………12

4.1.2 隶属函数…………………………………………………………………………12

4.1.3 确定隶属函数语言变量赋值……………………………………………………13

4.1.4 建立模糊规则表…………………………………………………………………14

4.1.5 模糊控制与传统PID控制结合………………………………………………15

4.2 本章小结……………………………………………………………………………17

5 生物发酵罐温度控制系统硬件设计………………………………………………19

5.1 电源模块设计………………………………………………………………19

5.2 温度采集电路设计…………………………………………………………20

5.3 制冷加热模块设计…………………………………………………………21

5.4 显示模块设计………………………………………………………………21

5.5 本章小结……………………………………………………………………22

6 生物发酵罐温度控制系统软件设计………………………………………………24

6.1 系统软件主程序设计……………………………………………………24

6.2 温度及设定值的显示子程序……………………………………………25

6.3 键盘管理子程序…………………………………………………………26

6.4 定时中断应答子程序……………………………………………………27

6.5 本章小结…………………………………………………………………28

7 结论与展望………………………………………………………………………………29

7.1 论文总结………………………………………………………………………………29

7.2 后续工作展望………………………………………………………………………………29