【作者】 胡磊；

【导师】 夏红霞；

【作者基本信息】 武汉理工大学 ， 计算机科学与技术， 2010， 硕士

【摘要】 模糊控制是模糊理论在控制领域的应用,是智能控制的主要方法之一。概括地说,模糊控制模仿操作人员的控制过程,包括控制经验和知识,用语言规则来描述控制规律。模糊控制系统以语言的形式表示知识,其机理符合人们对过程控制的直观描述和思维逻辑,具有较强的鲁棒性,可用于非线性、时变、时滞系统的控制。现在,模糊控制正朝着自适应、自组织、自学习方向发展,使得模糊控制参数、控制规则在控制过程中自动地调整、修改和完善,从而不断完善系统的控制性能,达到更好的控制效果。将神经网络、遗传算法、混沌理论等软计算方法与模糊控制相融合已成为模糊控制的发展趋势。粒计算是信息处理的一种新的概念和计算范式.粒计算摒弃了求精确解的传统模式,用好的近似解对不确定的、模糊的、海量的现实问题加以研究,改变了传统的计算观念,使信息的处理更科学、合理、经济和易于操作。本文运用粒计算理论,研究模糊控制器中输入与输出之间关系的拟合。利用粗糙集理论提出了基于二进制粒矩阵的决策表属性约简算法,对模糊控制器的输入空间进行属性降维,解决了模糊控制器规则指数爆炸问题,实现了控制器设计的简化,为后续的规则提取建立了良好的基础。利用商空间理论将模糊控制与PID控制结合起来,实行粗粒度层次采用模糊控制,细粒度层次采用PID控制,可以提高整个控制系统的精度与速度。本文还将模糊控制应用于城市公路隧道排水系统中,将水位和水位变化率综合考虑,作为模糊控制系统的输入变量,水泵启动台数作为模糊控制系统的输出变量,运用Matlab进行仿真实验,获得了水泵台数的输出曲面。更多还原

【Abstract】 Fuzzy control is the application of fuzzy theory in the field of control, and it is a primary method of intelligent control. Generally speaking, fuzzy control imitates the operator’s control procedure, including the control experience and knowledge, and describes control law with language. Because fuzzy control presents knowledge in the form of language, its mechanism accords with people’s direct description and logic towards the process control. Fuzzy control has strong robustness, and can be used for non-linear, time-varying, time-delay system’s control. Now, fuzzy control is developing towards self-adaptation, self-organization, and self-learning, allowing control parameters and rules can adjust, modify, and improve automatically, then the control performance could be improved constantly. To combine neural network, genetic algorithm, chaos theory, or other soft computing methods with fuzzy control has become fuzzy control’s trend.Granular computing is a new concept and computing paradigm of information processing. It abandons the traditional model which always tries to find the exact solution. Granular computing uses good approximate solution to research the uncertain, fuzzy and a mass of real problems, changes the traditional computing concept, and makes the information processing more scientific, more reasonable, more economic and easier to operate.This paper researches the relationship between input and output of fuzzy controller with the help of granular computing. It uses the rough set theory to establish the attribute reduction algorithm based on granular matrix, reduces dimensions of fuzzy controller’s input space, solves the fuzzy controller rule’s exponential explosion problem, simplifies the fuzzy controller’s design and lays a good foundation of subsequent rule extraction. I use quotient space theory to combine fuzzy control and PID control. Through adopting fuzzy control on coarse granularity and PID control on fine granularity, the whole control system’s accuracy and speed could be improved. This paper also applies fuzzy control into the drainage system of city highway tunnel. Water level and water level’s change rate are input parameters of the fuzzy control system, and they should be taken into account together. The number of water pump which should be turned on is output parameter of the system. I use Matlab to simulate the fuzzy control system and get the surfview of the fuzzy controller.更多还原