【作者】 赵真非；

【导师】 孙丽萍； 张冬妍；

【作者基本信息】 东北林业大学 ， 控制理论与控制工程， 2005， 硕士

【摘要】 随着社会的发展,人们对木材干燥的需求量增加,木材的高效利用已成为科学工作者所关注的前沿课题。木材干燥是改善木材物理力学性能、合理使用木材、减少木材降等损失、提高使用效率的重要措施,也是保证木制品质量的关键技术之一。木材干燥控制系统通常采用PID控制,传统的PID控制是依赖操作人员按照工艺参数凭经验的控制方法,缺乏充分的灵活性,存在着参数修改不方便、不能进行自整定等缺点。因而,高质量的现代化控制系统已成为创新干燥设备亟待解决的问题。 木材干燥的控制过程就是控制窑内介质温度和湿度来使木材含水率降低到某一期望值的过程。针对实际干燥过程的特性,本文在课题前面工作所做的神经网络模型的基础上提出一种智能的PID参数整定方法,即将模糊控制和PID控制结合起来,构建模糊自适应PID控制器。这种控制器实现系统的最佳控制,它运用模糊数学的基本理论和方法,将操作人员长期积累的经验知识用控制规则模型化,并把这些模糊控制规则以及有关信息(如初始PID参数等)作为知识存入计算机中,然后计算机根据控制系统的实际响应情况,运用模糊推理自动实现对PID参数的最佳调整。 文中使用了MATLAB中的模糊逻辑工具箱和Simulink进行仿真研究。通过对干燥窑的PID控制和模糊自适应PID控制进行仿真、分析与比较,得出模糊自适应PID控制器的阶跃响应曲线具有上升快,调节精度提高,稳态性能好,过渡过程时间短,超调量小的优点。因而木材干燥窑的模糊自适应PID控制是可行的、有效的,它实现了参数的自整定,且优于传统PID控制。这对提高木材干燥过程的控制水平,有效地保证木材干燥质量、降低能源消耗和减少成本,具有重要的理论研究和实际指导意义。更多还原

【Abstract】 With the development of the society and increasing demands for wood drying, effective utilization of wood has become an advanced subject concerned by science researchers. Wood drying is an important measure of improving wood’s physical mechanics performance, fair use of wood, reducing loss of wood’s downgrade, increasing utilization efficiency of wood. It is also one of the key techniques of guaranteeing woodwork’s quality. Wood drying usually performs PID control, which control accuracy is not very good because of lacking adequate flexibility. The PID controller has disadvantages of inconvenient coefficient modification, incapacity of self-adjusting, etc. Therefore, modern high quality control systems are crucial problems need to be solved in the innovation of wood drying equipments.The control process of wood drying is the same as the process of controlling medium’s temperature and humidity in a kiln in order to reduce water ratio of wood to some expected value. According to actual characteristics of wood drying, this thesis proposes a new intelligent PID coefficient adjusting method based on existing neural network model. The method combines fuzzy control with PID control to construct a fuzzy adaptive PID controller, which realizes optimum control of system. It performs fundamental theories and methods of fuzzy mathematics to modeling performers’ knowledge, using control rules. At the same time, it considers these rules and related information (for example, original PID coefficients) as knowledge and stores them in computers. Then according to real response of control system, computers apply fuzzy reasoning to realize automatic optimum setting of PID coefficients.The thesis simulates by fuzzy logic toolbox and Simulink of MATLAB. Through simulation, analysis and comparison between PID control and fuzzy adaptive PID of wood drying kiln, the results show that steps response curve of the fuzzy adaptive PID controller has the advantages of rising quickly, high adjusting precision and good stabilization, short transition time and small overshoot. This is difficult for PID control to realize. For these reasons the fuzzy adaptive PID controller is feasible and effective. The controller’s coefficient self-adjusting can be realized, and its performance is better than traditional PID controllers. To effective guarantee the quality of wood drying, reduce energy use and lessen costs, these advantages have important guiding significance of theoretical and practical research.更多还原