Development and verification of construction method of intelligent control system based on quantity fuzzy evaluation

近年来，利用人工智能、神经网络和模糊集理论，计算机可以轻松处理技能人员的控制知识。它由数字计算机的硬件和软件支持。并将该系统应用于实际工作中，为实际系统的柔性智能控制系统的建立奠定了基础。这些智能控制系统是通过对控制经验的语言描述和对运行数据的建模来设计的。很多自由度会造成困难。该方案考虑了模糊控制及其与传统控制理论的关系。将控制方法的设计支撑系统假设为一个基底。它具有常规控制方法的设计技术。本课题旨在发展基于定量模糊评价的智能控制系统设计技术。本课题构建了以下两个主题的智能控制系统，并进行了实验评价。(1)基于粗糙系统对象模型构造PID控制器。通过模糊推理切换控制参数，提出了调整后的层次模糊控制方法。该方法已应用于一些植物模型和实验装置。仿真和实验结果表明，可以构建出能够达到设定最佳响应的控制系统。(2)建立了汽车驻车控制中的驾驶知识。基于定量目标（位置误差和方向误差）的评价构建了智能控制系统，并通过仿真对系统进行了性能评价。并将该控制系统安装在1/10比例的模型车上，进行了运行实验。结果证实，该控制系统能够实现良好的驱动。在这个项目中，响应的知识和控制工程师对一个对象系统的最佳实现目标的知识作为研究的结果得到了证实。智能控制系统的设计可以在常规控制技术的扩展中，以给定的事物作为基于模糊集的评价指标，从而对模糊性进行定量处理。少

Recently, the computer can handle easily skill person's control knowledge by using AI,Neuro and the fuzzy set theory. It is supported by digital computer's hardware and software. And application is advancing to working of the system for building in about the flexible intelligent control system for a real system. These intelligent control systems are designed from the description of the language of the control experience and modeling from the operation data. A lot of freedom degrees cause difficulty.In this project, fuzzy control and a relation to the conventional control theory were considered. The design support system of the control method was assumed to be a base. It had a design technique of the conventional control method. And this project aimed at the development of the design technique of the intelligent control system based on a quantitative fuzzy evaluation. In this project, the intelligent control system of two following themes was constructed and the experiment evaluation wa … More s done.(1) Some PID controllers were constructed based on the rough system object model. These control parameters are switched by fuzzy reasoning, and the adjusted hierarchical fuzzy control method was proposed. This method was applied to some plant models and the experiment device. As a result of the simulation and the experiment, the control system which was able to achieve the set preferable response was able to be constructed.(2) The drive knowledge in the parking control of the car was built in. The intelligent control system constructed based on the evaluation of a quantitative target (position error and direction error) , and the developed system evaluated performance by the simulation. In addition, this control system was installed in model cars of 1/10 scales and the running experiment was done. As a result, it was confirmed that the control system was able to achieve a good drive.In this project, the knowledge of the response and the control engineer's knowledge concerning the preferable attainment target with a object system as a result of this research was confirmed. Intelligent control system design was able to be confirmed in the extension of an conventional control technique by the thing given as an evaluation index based on the fuzzy set by which vagueness was able to be treated quantitatively. Less